US20210398088A1 - System, Method, and Computer-Readable Medium for Comparing Automatically Determined Crash Information to Historical Collision Data to Estimate Repair Costs - Google Patents

System, Method, and Computer-Readable Medium for Comparing Automatically Determined Crash Information to Historical Collision Data to Estimate Repair Costs Download PDF

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US20210398088A1
US20210398088A1 US17/465,088 US202117465088A US2021398088A1 US 20210398088 A1 US20210398088 A1 US 20210398088A1 US 202117465088 A US202117465088 A US 202117465088A US 2021398088 A1 US2021398088 A1 US 2021398088A1
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vehicle
damaged
crash
damaged vehicle
information
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US17/465,088
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William J. Leise
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State Farm Mutual Automobile Insurance Co
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State Farm Mutual Automobile Insurance Co
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Priority to US17/465,088 priority Critical patent/US20210398088A1/en
Assigned to STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY reassignment STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: LEISE, WILLIAM J.
Publication of US20210398088A1 publication Critical patent/US20210398088A1/en
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Definitions

  • the present disclosure generally relates to a system and a method for treating a vehicle damaged in a crash, and more particularly, to determining a repair cost estimate based on historical collision data.
  • a first example embodiment is a method, executed in part by one or more processors programmed to perform the method, for estimating vehicle repair costs.
  • the method may include receiving, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyzing the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determining one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determining a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmitting an indication of the cost estimate.
  • the system comprises a computing device including one or more processors, and one or more memory devices coupled to the one or more processors of the computing device, the one or more memory devices storing executable instructions that when executed by the one or more processors of the computing device cause the system to: receive, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyze the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determine one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determine a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmit an indication of the cost estimate.
  • a further example embodiment is a tangible, computer-readable medium storing instructions that when executed by one or more processors of a computer system cause the computer system to: receive, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyze the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determine one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determine a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmit an indication of the cost estimate.
  • FIG. 1 is a general overview of a vehicle treatment system for treating a vehicle damaged in a crash
  • FIG. 2 depicts an example vehicle treatment process capable of being implemented in the vehicle treatment system illustrated in FIG. 1 in accordance with the presently described embodiments;
  • FIG. 3 depicts an example table of vehicle treatment codes (e.g., repair) for estimating the cost of repairing vehicle damage in accordance with the presently described embodiments;
  • vehicle treatment codes e.g., repair
  • FIG. 4 depicts an example damaged vehicle including vehicle treatment codes (e.g., repair) for various vehicle parts in accordance with the presently described embodiments;
  • vehicle treatment codes e.g., repair
  • FIG. 5 depicts an example method for detecting a risk of insurance fraud based on collision data in accordance with the presently described embodiments
  • FIG. 6 depicts an example injury data table in accordance with the presently described embodiments
  • FIG. 7 is a block diagram depicting an example mobile computing device, an on-board computing device, a server device, and a communication network that may configured in the example system for treating a damaged vehicle in accordance with the described embodiments;
  • FIG. 8 is a block diagram of an example mobile computing device capable of being implemented in the example system shown in FIG. 9 ;
  • FIGS. 9-12 depict example embodiments of information displayed on the one or more user interfaces of the one or more computing devices in accordance with the presently described embodiments.
  • a vehicle treatment system utilizes crash information of a vehicle involved in a crash to approximate the extent of damage to the vehicle and determine a treatment facility for treating the damaged vehicle.
  • the estimated vehicle damage is used to generate repair codes for repairing the vehicle and estimate the total cost of repair.
  • the estimated vehicle damage is also used to detect a risk of insurance fraud by a policy holder or another person involved in the crash with the vehicle, and also to calculate a treatment complexity level for treating the vehicle. Based on a determined treatment complexity level, the system identifies a treatment facility capable of treating the damaged vehicle and sends information for transporting the damaged vehicle to the treatment facility, thereby removing the need to initially bring the damaged vehicle to an interim location for a damage assessment before transporting the damaged vehicle to a designated treatment facility for treatment.
  • the vehicle treatment system receives crash information associated with a vehicle involved in a crash.
  • the crash information may be transmitted within a data transmission, which may include information about or associated with the damaged vehicle, sensor data, damage descriptions, and/or images that may pertain to aspects of the crash, such as vehicle operating characteristics near or at the time of the crash (impact characteristics), e.g., vehicle acceleration, vehicle velocity, and/or impact direction.
  • impact characteristics vehicle operating characteristics near or at the time of the crash
  • the system may analyze one or more aspects of the crash information. For example, the system may analyze vehicle operating data received from sensors operatively coupled to the vehicle to calculate an estimate of the amount of vehicle damage base on the force characteristics of the crash. The system may also calculate an estimate of the amount of damage by analyzing a description and/or image of the damaged vehicle. Based on the extent of vehicle damage estimated by the analysis of the crash information, the treatment complexity level for treating the damaged vehicle may be determined.
  • the analysis for estimating the amount of vehicle damage may include comparing the crash information to collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle.
  • the collision data may include various levels of vehicle damage associated with specified aspects or characteristics of collision information related to other vehicles of the same or similar type as the vehicle damaged in the crash.
  • One or more categories of vehicle damage in the collision data may be equated to particular vehicle acceleration or velocity, or a range of vehicle acceleration or velocity occurring at or near the time of impact of the crash.
  • the one or more categories of vehicle damage in the collision data may also be equated to a particular description, image, illustration, etc., of a damaged vehicle. Based on the extent of vehicle damage estimated by substantially matching the crash information to comparable characteristics in the collision data, the treatment complexity level for treating the damaged vehicle may be determined.
  • the treatment complexity level is an estimate indicating the level of involvement, e.g., effort, cost; associated with treating the damaged vehicle.
  • the treatment of the vehicle may include repairing or replacing damaged vehicle parts, and in some instances where repairing the vehicle is too costly and not worth repairing (e.g., total loss), the treatment may include salvaging or scrapping the damaged vehicle. Damaged vehicles designated as a total loss, but which include some value (e.g., salvageable vehicle parts), may be sold as is, or repaired to some extent for resale. In addition, the undamaged vehicle parts of a total loss vehicle may be salvaged and stored, reused, or sold.
  • the treatment complexity level may be determined for each damaged vehicle part and/or groups of damaged vehicle parts using treatment codes and/or vehicle parts lists. For example, the hood of a damaged vehicle may require minor repairs whereas the fender may be damaged significantly and require major repairs.
  • the treatment complexity level may be determined for groups of vehicle parts using treatment codes and/or lists of damaged and/or undamaged vehicle parts. For example, one treatment code may propose repairs and/or replacement to one group of vehicle parts and be classified as a minor repair; while another treatment code may propose repairs and/or replacement to one or more critical vehicle parts and be classified as a major repair or a total loss.
  • the treatment complexity level may affect the determination of the treatment complexity level, including, and not limited to, the market value of the vehicle type (e.g., make, model, trim level, and/or year of manufacture) that includes the damaged vehicle and the corresponding vehicle parts.
  • the treatment complexity level may also be determined in part on the market value of the treatment services provided by treatment personnel involved with the prescribed treatment of the damaged vehicle.
  • the market value may be based on a set schedule with incremental adjustments over a predetermined period of time, e.g., depreciation over the life expectancy of the vehicle type.
  • the scheduled market value may become outdated and less useful. Using outdated market values for vehicle parts and/or services may result in miscalculated and inaccurate determinations of the treatment complexity level.
  • one or more market values may be monitored and used in the determination of the treatment complexity level. For example, on-demand or periodic (e.g., hourly, daily) monitoring of the market value may be implemented to adapt to a sudden and/or unforeseen change in a market value.
  • Some examples of sudden and/or unforeseen changes that may affect the market value of a vehicle, its vehicle parts, and/or associated treatment services include: discontinued production of a type of vehicle (e.g., make, model, trim level), and trends in vehicle popularity.
  • the vehicle treatment system Upon determination of the treatment complexity level, information related to treating the damaged vehicle is transmitted by the system.
  • the transmitted information may be automatically sent after the crash to one or more treatment facilities, vehicle parts suppliers, vehicle transporters, and/or persons or entities associated with the damaged vehicle, for example, the vehicle owner and/or an insurance agent.
  • the vehicle treatment system allows for the timely delivery of replacement vehicle parts to a selected vehicle treatment facility for treating the damaged vehicle, thereby avoiding the cost and time associated with known damage assessment procedures wherein the damaged vehicle is brought to the treatment facility for inspection and assessment before treatment can be scheduled. For example, an estimate of the damage to the vehicle may be made shortly after the crash to determine whether the damaged vehicle can be repaired.
  • the damaged vehicle may be brought to a vehicle treatment facility capable of salvaging and/or scrapping the damaged vehicle.
  • a repairable vehicle damaged vehicle parts that may need to be repaired and/or replaced may be identified based on the received crash information, wherein the location and availability of such replacement vehicle parts within a vehicle parts network may then be determined.
  • An aggregated order of the identified replacement vehicle parts among the one or more vehicle parts suppliers may be compiled and a transportation route may be generated based on the location and availability of the replacement vehicle parts.
  • a single delivery vehicle may be utilized to travel the transportation route and gather the aggregated order of replacement vehicle parts for delivery to the selected vehicle treatment facility.
  • the cost associated with using single delivery vehicle to timely deliver the aggregated order of replacement vehicle parts from one or more vehicle parts suppliers of the vehicle parts network is likely less than the cost associated with using several delivery vehicles and/or routes to deliver the ordered replacement vehicle parts.
  • assessing the performance and/or efficiency of the vehicle treatment process with respect to vehicle parts suppliers involved in the treatment of the damaged vehicle is more simply evaluated with a single delivery vehicle and aggregated route as compared to multiple delivery vehicles and multiple routes. For example, responsibility among the vehicle parts suppliers for a delayed delivery of the replacement vehicle parts may be more readily identifiable when one aggregated delivery route is utilized as opposed to multiple delivery routes.
  • FIG. 1 is a general overview of a system 100 capable of facilitating treatment of a vehicle damaged in a crash.
  • vehicle refers to any type of powered transportation device, which includes, and is not limited to, an automobile, truck, bus, motorcycle, and boat. While the vehicle may normally be controlled by an onboard operator, it is to be understood that the vehicle may be unmanned and remotely or autonomously operated in a conventional or nonconventional manner, such as using controls other than the steering wheel, gear shift, brake pedal, and accelerator pedal.
  • the system 100 in FIG. 1 includes a processing center 102 capable of facilitating an analysis of the damaged vehicle's crash information 104 to determine a treatment for the damaged vehicle.
  • the analysis of the crash information 104 which may include the use of collision data 106 , may be performed by system personnel and/or a computing device at the processing center 102 .
  • crash is used in reference to a particular incident in which a particular vehicle of concern was damaged and the term collision is used in reference to one or more incidents in which another vehicle or vehicles were damaged.
  • the crash information 104 provided to the processing center 102 includes specific information related to a particular vehicle and the crash that damaged the particular vehicle.
  • the crash information 104 may include information received from telematics devices, e.g., sensors, operatively coupled to the vehicle or observed by an individual, such as a vehicle operator/owner 108 , a vehicle occupant, a bystander, an insurance agent/entity 110 of the damaged vehicle, an emergency responder, an accident investigator, etc.
  • the crash information 104 may include operating characteristics of the vehicle involved in the crash such as the approximate speed of the vehicle at the time of the crash and what part(s) of the vehicle was damaged.
  • crash information provided to system personnel and/or the processing center 102 may include whether emergency response components and/or devices were deployed, e.g., airbags; or if the damaged vehicle is drivable. Images of the damaged vehicle may also be included in the crash information 104 , which may be provided for analysis and/or comparison with the collision data 106 .
  • the vehicle's operating information may be monitored by a series of measurements of conditions or characteristics pertaining to the operation of the vehicle.
  • one or more computing devices such as a mobile computing device, an on-board computing device, and/or a server device may be communicatively coupled to sensors such as an accelerometer array operatively coupled to the vehicle.
  • the accelerometer array may monitor and/or measure the acceleration/deceleration of the vehicle along several axes and/or travelling directions.
  • Other vehicle operating information such as vehicle acceleration, velocity, and direction may be measured, logged, and stored in the system 100 , for example, a data storage unit of the system or a remote storage unit communicatively coupled to the system.
  • the operating information may be logged and/or stored discretely, periodically (e.g., every second or portion or multiple thereof), or conditionally based on an occurrence or detection of an event (e.g., a crash log).
  • a crash may be detected through a near-simultaneous activation of an emergency responsive device, component, or action, such as the deployment of an air-bag, and/or an alarm or alert, e.g., automatic collision notification (ACN), etc.
  • ACN automatic collision notification
  • a crash may be detected when a computing device operatively coupled to the accelerometer detects a significant, near immediate change (increase or decrease) in the monitored acceleration in the fore-aft, lateral, and/or vertical direction of the vehicle, e.g., X, Y, and Z axes.
  • a crash may be detected through the use of a global positioning system (GPS) unit via detection of a near-immediate increase and/or decrease in vehicle velocity.
  • GPS global positioning system
  • Additional crash information 104 may include a vehicle identifier such as a vehicle data identifier (VDI) associated with the damaged vehicle involved in the crash.
  • VDI vehicle data identifier
  • the VDI may include sections or segments relating to one or more aspects or characteristics of the vehicle, such as, a vehicle manufacturer identifier, vehicle type identifier, a vehicle serial number, pointers to other vehicle information (e.g., market value), etc., and may include reference to the make, model, trim level, year, and/or type of vehicle as well the vehicle parts of the vehicle.
  • the VDI may also include the vehicle's vehicle identification number (VIN) and/or portions thereof.
  • the VIN may identify a unique vehicle and include multiple sections or segments in a standardized format that generally depends on the vehicle manufacturer and/or the country or government agency where the VIN is used, e.g., U.S.A., European Union.
  • the sections or segments of the VIN are associated with a vehicle manufacturer identifier, vehicle type identifier, a vehicle serial number, etc., and may include reference to the make, model, trim level, year, and/or type of vehicle as well the vehicle parts of the associated vehicle.
  • Collision data 106 generally includes records or compilations of information involving other vehicles damaged in other collisions.
  • the collision data 106 may include historical loss information having various collision scenarios including lists of damaged and/or undamaged vehicle parts, images, telematics data, and vehicle damage evaluations.
  • Historical loss information may include recorded amounts of vehicle damage associated with or resulting from known, observed, or measured aspects relating to a collision or impact of a particular make and/or model of vehicle, such as vehicle direction, acceleration, and/or velocity, as well as relative position of vehicle parts within the vehicle.
  • Some examples of historical loss information include vehicle collision test data, bumper test data, collision image data, traffic accident investigation data, and the like.
  • the collision data 106 may be compiled into one or more charts or tables wherein various collision aspects are associated with known, predicted, or determined vehicle damage.
  • the collision data 106 may be correlated with one or more sections or segments of the VDI and/or VIN, which may further be correlated to vehicle manufacturer information; prescribed vehicle treatments and costs; vehicle part warranties; market value estimations of various vehicle types, vehicle parts, vehicle treatment services, and/or procedures, etc.
  • the collision data 106 may also include vehicle safety information including, and not limited to, vehicle part recall information, safety notices, repair notices, etc.
  • the collision data 106 which may be stored in the system 100 and/or operatively coupled to the processing center 102 , may be periodically and/or discretely updated to include additional vehicle operating characteristics from other collisions, vehicle part damage of other damaged vehicles of similar vehicle type, and changes to the market value of vehicles, vehicle parts, and/or prescribed vehicle treatment services.
  • FIG. 2 is a flow diagram 200 depicting an example embodiment of a vehicle treatment process that may be implemented by the treatment system 100 shown in FIG. 1 .
  • the process 200 may be executed separately or cooperatively by system personnel and the processing center 102 .
  • Vehicle crash information is received or gathered for analysis (block 202 ).
  • the vehicle crash information may be provided to system personnel and/or the processing center 102 by a vehicle occupant, bystander, or emergency responder communicating characteristics of the crash.
  • the driver of the damaged vehicle may contact system personnel and/or the processing center 102 and provide operating characteristics of the vehicle near or at the time of the crash, e.g., impact characteristics such as approximate vehicle speed, description and/or image of vehicle damage, description of vehicle operation, and whether portions of the vehicle's safety system were used as a result of the crash.
  • Some crash information such as the VDI and/or VIN, may have previously been provided to the processing center 102 and/or system personnel.
  • Crash information may also be automatically provided to system personnel and/or the processing center 102 by the vehicle's engine control unit (ECU) and/or one or more telematics devices or components (sometimes referred to as an event data recorder (EDR)) that are capable of sensing, monitoring, and/or noting various vehicle operating characteristics, e.g., acceleration, velocity, position of vehicle parts relative to the vehicle, direction of the vehicle at the time of the crash, and deployment of emergency response equipment.
  • the telematics devices are operatively coupled to the vehicle and may be configured to automatically function when the vehicle is in operation. When a crash is detected, data including one or more monitored operating characteristics of the vehicle may be automatically obtained and transmitted via a communication signal to system personnel and/or the processing center 102 as crash information 104 .
  • the crash information 104 may be analyzed and/or evaluated by system personnel and/or the processing center 102 to determine an estimate of the extent of damage caused to the vehicle during the crash (block 204 ).
  • the compilation of historical collision information 106 including vehicle operating characteristics associated with known vehicle damage from similar vehicles involved in previous collisions may be used to estimate the amount of damage that occurred to the vehicle during the crash.
  • a damage evaluation tool may include a guide or template to be used in estimating the extent of vehicle damage.
  • Stored images and operating characteristics of other similar type vehicles damaged in other collisions may be used in the analysis to correlate with operating characteristics obtained in the crash information of the damaged vehicle.
  • the extent of vehicle damage resulting from the crash can be estimated by comparing crash information 104 , e.g., images and/or vehicle operating characteristics and aspects of the crash; with collision information 106 of other similar type vehicles, e.g., make, model, and or trim level.
  • crash information 104 e.g., images and/or vehicle operating characteristics and aspects of the crash
  • collision information 106 of other similar type vehicles e.g., make, model, and or trim level.
  • a treatment complexity level for treating the damaged vehicle may be determined (block 206 ) by system personnel and/or the processing center 102 .
  • the treatment complexity level may include one or more vehicle treatment components for treating the damaged vehicle, such as a pricing schema having one or more predetermined price structures associated with a vehicle, its vehicle parts, and/or services associated with treating the vehicle, e.g., treatment codes, treatment schedule, skill level and/or pay rate of treatment personnel, and/or equipment of a treatment facility used to treat the damaged vehicle.
  • the collision data 106 may include a range of treatment complexity levels corresponding to various amounts of vehicle damage, wherein various levels of vehicle damage may be equated with various levels of vehicle treatment.
  • the range of vehicle treatment complexity levels may be delineated by the amount of involvement associated with treating a damaged vehicle, for example, repairing and/or replacing vehicle parts of the damaged vehicle, or salvaging and/or scrapping a damaged vehicle determined to be a total loss.
  • the treatment complexity level represents the difficulty associated with treating individual vehicle parts within the damaged vehicle.
  • the several levels of treatment complexity may include a speed or light repair, a medium or moderate repair, a heavy or severe repair, not repairable, scrap, and salvage, for example.
  • a speed or light repair treatment designation may indicate or estimate that one or two vehicle parts need repair or replacement, or that minor refinishing may be required, but that no structural damage occurred to the vehicle.
  • a medium or moderate repair treatment designation may indicate that a few vehicle parts require repair or replacement or that light structural damage occurred to the vehicle.
  • a heavy or extensive repair treatment designation may indicate that the vehicle is not drivable, significant structural damage occurred to the vehicle, more than a predetermined amount of vehicle parts (e.g., five) need repair or replacement, or a welded-on vehicle component needs replacement.
  • a scrap designation may indicate that the vehicle is to be scrapped and not repaired. Prior to scrapping, the damaged vehicle may be dismantled to salvage any undamaged or usable vehicle parts.
  • Each treatment complexity level may include estimates or indications of the type, time, and/or cost of treatment associated with the type of vehicle (e.g., make, model, year, trim level, etc.) and amount of vehicle parts that may be damaged, e.g., body panel (front, side, rear, quarter-panel, rocker, driver-side, and passenger-side), bumper, radiator, lights, water pump, battery, struts, frame, and gas tank.
  • the estimated extent of vehicle damage determined by system personnel and/or the processing center 102 may include vehicle treatment codes and/or a list of damaged and/or undamaged vehicle parts.
  • system personnel and/or the processing center 102 may identify the requisite treatment complexity level. For example, a vehicle damage estimate requiring less than 10 hours of labor time and/or $1000 in replacement vehicle parts may be designated as a low treatment complexity level; a vehicle damage estimate requiring between 10-15 hours of labor time and/or between $1000-$2500 in replacement vehicle parts may be designated as a medium treatment complexity level; a vehicle damage estimate requiring between 15-30 hours of labor time and/or between $2500-$5000 in replacement vehicle parts may be designated as a high treatment complexity level; and a vehicle damage estimate requiring more than 30 hours of labor time, and/or having costs and labor greater than the market value of the damaged vehicle in an undamaged condition, may be designated as a total loss, scrapping, and/or salvaging treatment complexity level.
  • the total loss, scrapping, and/or salvaging designation indicates that the vehicle is not to be repaired.
  • the damaged vehicle may be dismantled to salvage any undamaged or usable vehicle parts, wherein the remaining vehicle parts may be scrapped or sold.
  • Each damaged vehicle part and/or group of vehicle parts may be assigned a vehicle treatment code from a set of vehicle treatment codes based on the extent of the damage to the vehicle and/or vehicle part(s).
  • the set of vehicle treatment codes may include a separate vehicle treatment code for each combination of crash characteristics, such as the make, model, year, and/or trim level of the vehicle being treated; the vehicle part or a list of vehicle parts being treated; the type of treatment for the vehicle part(s) including whether the vehicle part(s) needs to be repaired, replaced, salvaged, or scrapped; the extent of the damage to the vehicle part(s), etc.
  • Each vehicle treatment code may include and/or correspond to a cost estimate.
  • a specific vehicle treatment code may include repairing the hood of a first particular vehicle type (make, model, etc.) with slight damage.
  • Another specific vehicle treatment code may include replacing the bumper of a second particular vehicle type with heavy damage.
  • the associated cost estimate for the vehicle treatment code for the first vehicle type may be $100 whereas the associated cost estimate for the treatment code for the second vehicle type may be $500.
  • Each assigned vehicle treatment code may be combined to determine a total cost estimate for treating the damaged vehicle.
  • an example table 300 of vehicle treatment codes for estimating the cost of treating vehicle damage is depicted. It is to be understood that while the example table 300 includes example repair treatment codes that may be a small subset of a larger set of vehicle repair codes, other type of vehicle treatment codes may include or pertain to vehicle treatment of total loss vehicles relating to salvaging and/or scrapping values of undamaged vehicle parts. As mentioned above, the set of vehicle treatment codes may include a separate vehicle treatment code for each combination of vehicle characteristics such as make and model of the vehicle being repaired, the vehicle part being repaired, the type of repair for the vehicle part including whether the vehicle part needs to be repaired and/or replaced, the extent of the damage to the vehicle part, etc.
  • Each vehicle treatment code may correspond to a cost estimate, where the cost estimate may be determined based on collision data including historical loss information of similar type vehicles having similar type damage.
  • the associated cost estimate for a repair code corresponding to repairing the quarter panel of a particular make, model, trim level, etc. (e.g., type) of vehicle having moderate damage may be determined by analyzing repair costs from historical loss information related to repairing quarter panels of that particular type of vehicle having moderate damage from past collisions.
  • the vehicle treatment codes may be stored in the system 100 and/or operatively coupled to the processing center 102 .
  • repair code 00675 (reference 304 ) is associated with an instruction, “Refinish Hood,” and a cost estimate, $ 300 . While the instruction for repair code 00675 (reference 304 ) does not specify the extent of the damage to the hood, or the make and model of the vehicle, repair code 00675 (reference 304 ) may be used for refinishing hoods of a particular type of vehicle with light damage. In some embodiments, a separate repair code, for example, 10675 may be used for refinishing hoods for vehicles of a different particular type of vehicle with light damage. Moreover, yet another repair code, for example, 02675, may be used for refinishing hoods on vehicles with moderate damage. Further, in some embodiments, the set of repair codes may be based on additional or alternative vehicle characteristics and in other embodiments some of the above mentioned vehicle characteristics may be omitted from the set of repair codes.
  • repair code 00610 (reference 302 ) is associated with the instruction, “Repair Roof,” and a cost estimate of $700; repair code 00676 (reference 306 ) is associated with the instruction, “Refinish Fender,” and a cost estimate of $200; repair code 00678 (reference 308 ) is associated with the instruction, “Replace Grille,” and a cost estimate of $250; repair code 00679 (reference 310 ) is associated with the instruction, “Replace Door,” and a cost estimate of $500; repair code 00682 (reference 312 ) is associated with the instruction, “Replace Quarter Panel,” and a cost estimate of $400; repair code 00690 (reference 314 ) is associated with the instruction, “Repair Bumper,” and a cost estimate of $100; and repair code 00692 (reference 316 ) is associated with the instruction, “Repair Trunk Lid,” and a cost estimate of $350.
  • Each of these repair codes may be for the same particular vehicle type and may be aggregated and/or combined to estimate the total cost of repair for a damaged vehicle of that particular type. For example, by comparing crash information for a damaged vehicle of a particular type to collision data, a list of damaged vehicle parts including the extent of the damage to each vehicle part may be generated. A repair code from the set of repair codes may then be assigned to each damaged vehicle part in the list based on the vehicle characteristics for the damaged vehicle. For example, repair code 00679 (reference 310 ) may be assigned when a door in a specified type of vehicle needs to be replaced. In some embodiments, repair code 00679 may be assigned twice when two doors in the specified type of vehicle need to be replaced.
  • repair codes e.g., vehicle repair codes for a particular type of vehicle
  • each type may correspond to a separate subset of repair codes including each combination of vehicle characteristics.
  • repair codes 00600-00699 may correspond to one type of vehicle
  • repair codes 00700-00799 may correspond to another type of vehicle.
  • the vehicle type may be determined using the VDI/VIN data for the damaged vehicle as described above with reference to FIG. 1 .
  • repair codes may also be used in salvaging and/or scrapping treatments.
  • the repair code 19986 may be used for salvaging hoods of a particular type of vehicle in good condition.
  • the associated cost estimate may be a price estimate of the market value of the vehicle part assuming it is sold to a treatment facility or any other auto body shop.
  • the salvage repair codes may have an inverse relationship with the other repair codes. For example, for the salvage repair codes, vehicle parts in better condition may have higher associated price estimates, whereas for the other repair codes, the cost estimates become higher when there is more work that needs to be done to repair the vehicle part.
  • the price estimate may be based on the scarcity/demand for the vehicle part. For example, vehicle parts from an antique or classic car may be in high demand because the car is no longer manufactured.
  • the price estimates for salvage repair codes may be aggregated to determine the total price that an insurance provider can recover by salvaging vehicle parts.
  • FIG. 4 depicts an example damaged vehicle 400 including repair codes for various vehicle parts.
  • the damaged vehicle 400 may be associated with repair codes 00600-00699, which may be assigned to estimate the cost of repairing the vehicle.
  • the repair codes may be provided to a treatment facility for treating the damaged vehicle so the treatment facility knows what needs to be done to repair the vehicle without having to perform an inspection or assessment.
  • the repair codes also may be provided to ensure that the treatment facility does not miss a portion of the repair.
  • crash information for the damaged vehicle 400 may be compared to collision data including historical loss information of similar type vehicles damaged in past collisions to determine which vehicle parts are damaged, and the estimated extent of the damage to the vehicle parts including the type of repair necessary (e.g., whether the vehicle part needs to be repaired and/or replaced) as described above in FIG. 3 .
  • a repair code from the set of repair codes may then be assigned to each damaged vehicle part in the list based on the vehicle characteristics for the damaged vehicle.
  • the two doors 402 and 404 are assigned the repair code 00679 “Replace Door” with an associated cost estimate of $500 for each door.
  • the front, right fender 406 is assigned repair code 00676 “Refinish Fender” with an associated cost estimate of $200
  • the hood 408 is assigned repair code 00675 “Refinish Hood” with an associated cost estimate of $300
  • the roof 410 is assigned repair code 00610 “Replace Roof” with an associated cost estimate of $ 700 .
  • the trunk lid 412 is assigned repair code 00692 “Repair Trunk Lid” with an associated cost estimate of $350
  • the rear quarter panel 414 is assigned repair code 00682 “Replace Quarter Panel” with an associated cost estimate of $400.
  • the grille 416 is assigned repair code 00678 “Replace Grille” with an associated cost estimate of $250
  • the bumper 418 is assigned repair code 00690 “Repair Bumper” with an associated cost estimate of $100.
  • the total cost for repairing the vehicle may be estimated as $3300. This estimate may be used to pay the vehicle owner on the insurance claim, and/or to provide a treatment facility with an expectation of the cost and treatment of repair for the damaged vehicle.
  • system personnel and/or the processing center 102 may identify and select a vehicle treatment facility 112 capable of performing the recommended vehicle treatment, for example, repair, salvage, or scrap (block 208 ).
  • System personnel and/or the processing center 102 may compare the calculated treatment complexity level to prospective treatment facilities capable of providing the necessary vehicle treatment.
  • the selection of a vehicle treatment facility from among the one or more capable treatment facilities may be based on one or more dynamic criterion, such as a pricing structure, treatment facility capability, replacement vehicle part availability, treatment facility location, treatment facility quality rating and/or certification, treatment facility availability, current and/or prior business relationship with the treatment facility, etc., and combinations thereof.
  • One or more of these dynamic criteria may also be weighted and/or prioritized by system personnel and/or the processing center 102 when determining a treatment facility for treatment of the vehicle.
  • a low complexity vehicle treatment generally may not require a high or specialized skill level and the proximity and/or convenience of a vehicle treatment facility nearer the vehicle owner or the crash site may be considered to be more appropriate.
  • the location criterion of the vehicle treatment facility may be weighted and/or prioritized over some of the other criteria.
  • the skill level and/or performance record of the treatment facility may be considered and thus weighted and/or prioritized over some or all of the other criteria for determining a treatment facility.
  • the damaged vehicle may be salvaged and immediately sold or put up for auction or scrapped and shredded for its scrap metal. Scrapping the vehicle may be appropriated for low dollar, high curb-weight vehicles where the value of the damaged vehicle is perceived to be in the scrap metal.
  • the damaged vehicle may be dismantled to salvage any value associated with the damaged vehicle. For example, if the damaged vehicle includes undamaged vehicle parts, the vehicle may be dismantled and the undamaged vehicle parts may be harvested and stored in a storage facility for later use and/or sale.
  • the determination to sell or dismantle the damaged vehicle may include consideration of the treatment complexity level, the make, model, and year of the vehicle, and the market demand and/or desirability of particular harvested vehicle parts, e.g., at-risk vehicle parts for vehicles that are no longer in production. Additionally, a higher monetized recovery of the damaged vehicle may be attained if the damaged vehicle is partially repaired and/or dismantled to a varying extent, and then sold. For example, higher value and late model vehicles and/or vehicle parts may be prepared for sale. Such vehicles and vehicle parts, as well as rare or hard to find vehicles and vehicle parts may be privately or publicly sold or auctioned through a salvage treatment facility partnering with an entity using or administrating the treatment system and/or process described herein. Any unwanted vehicle parts that remain after dismantling may be shredded or scrapped.
  • system personnel and/or the processing center 102 may transmit a communication including information related to the treatment of the damaged vehicle (block 210 ).
  • the communication may be sent in the form of wired and/or wireless transmission, e.g., SMS text, e-mail, phone call, facsimile, etc. to the identified treatment facility.
  • the communication may also be transmitted to the vehicle owner and/or other one or more other entities authorized by the vehicle owner, such as a vehicle repair facility, a vehicle scrap facility, emergency personnel, an insurance agent, etc.
  • system personnel and/or the processing center 102 may contact the identified vehicle treatment facility 112 or a vehicle transporter 114 to facilitate transportation of the damaged vehicle from the crash site to the selected treatment facility, e.g., a service repair center, a scrapping or salvaging facility.
  • the damaged vehicle may be sent to an identified scrapping or salvaging facility to be dismantled where undamaged vehicle parts may be salvaged and stored at a warehouse 116 for reuse and resale before the remaining parts of the damaged vehicle are scrapped.
  • FIG. 5 depicts a flow diagram 500 of an example embodiment for detecting risks of insurance fraud based on collision data, which may be accomplished by system personnel and/or the processing center 102 .
  • the collision data may include injury data for injured drivers and/or passengers in past collisions.
  • the collision data may include information on the percentage of drivers and/or passengers who were injured driving Toyota Priuses which experienced heavy damage to the hood and front frame rails during past collisions.
  • the collision data may include information on the type of injuries suffered by those drivers and/or passengers, i.e., neck injuries, severe head trauma, etc., as well as the percentage of drivers and/or passengers who suffered each type of injury.
  • system personnel and/or the processing center 102 may utilize crash characteristics provided by an individual present at the crash site, such as the driver and/or occupant of the damaged vehicle or an emergency responder or crash characteristics automatically attained by telematics devices operatively coupled to the vehicle (block 502 ).
  • crash characteristics provided by an individual present at the crash site, such as the driver and/or occupant of the damaged vehicle or an emergency responder or crash characteristics automatically attained by telematics devices operatively coupled to the vehicle (block 502 ).
  • telematics devices operatively coupled to the vehicle (block 502 ).
  • descriptions and images of the damaged vehicle, vehicle acceleration, velocity, position of vehicle parts within the vehicle, and/or direction of the vehicle may be provided.
  • Some crash information may be attained by an accelerometer and an array of sensors including spatial sensors at the time of the crash and then transmitted via a wireless communication module to system personnel and/or the processing center 102 .
  • System personnel and/or the processing center 102 may also receive an injury claim from the policy holder for the vehicle, or another person injured in the crash (block 504 ).
  • the injury claim may be for a driver and/or passenger in the damaged vehicle at the time of the crash or a driver and/or passenger in another vehicle that is also damaged as a result of the crash.
  • the injury claim may include the type of injury, the severity of the injury, medical expenses, other complications as a result of the injury, etc.
  • System personnel and/or the processing center 102 may then analyze the crash information.
  • system personnel and/or the processing center 102 may compare various combinations of crash characteristics to collision data (block 506 ).
  • the collision data may include historical loss information of similar type vehicles damaged in past collisions.
  • the collision data may also include injury data for injured drivers and/or passengers in past collisions.
  • the injury data may be for drivers and/or passengers of the damaged vehicle as well as for drivers and/or passengers of other vehicles involved in the crash. In this manner, the system personnel and/or the processing center 102 may determine injury data for a subset of the collision data for similar type vehicles and having similar crash characteristics and/or a similar extent of damage.
  • injury data may be generated for all Ford F-150s with dented rear quarter panels requiring moderate repair from past collisions.
  • injury data may be generated for all Ford F-150s with dented rear quarter panels requiring moderate repair and having any other type(s) of damage as well.
  • injury data may be generated specifically for Ford F-150s having only dented rear quarter panels requiring moderate repair from past collisions.
  • FIG. 6 An example injury data table 470 for F-150s having the above described damage is illustrated in FIG. 6 .
  • the injury data may be stored with the collision data 106 which may be stored in the system 100 and/or operatively coupled to the processing center 102 .
  • the example injury data table 600 includes an entry for the total number of people injured, 25 (reference 602 ), in crashes involving a Ford F-150 where the damaged vehicle has a dented rear quarter panel requiring moderate repair.
  • the data table 600 also includes entries for the total number of people who were not injured, 100, and the percentage of people who were injured, 20 percent.
  • the data table 600 also includes entries for the number of people as well as the percentage of people with neck injuries 604 , back injuries 606 , and head injuries 608 as a result of the crashes. Some people injured in the crashes may have suffered multiple injuries (e.g., back and head, head and neck, etc.).
  • the injury data table 600 may also include the number of people who suffered injuries of varying severity. For example, out of the 25 people injured in the data table 600 , 10 people may have suffered severe injuries, 10 people may have suffered moderate injuries, 2 people may have suffered minor injuries, etc. Moreover, the data table 600 may also include the locations of the people who suffered injuries in the vehicle (e.g., the driver's seat, the front passenger seat, the back left seat, etc.), as well as the number of people who suffered injuries in other vehicles (e.g., 15 percent of the people were injured in Ford F-150s, while 85 percent were injured in other vehicles as a result of colliding with Ford F-150s).
  • the vehicle e.g., the driver's seat, the front passenger seat, the back left seat, etc.
  • the number of people who suffered injuries in other vehicles e.g., 15 percent of the people were injured in Ford F-150s, while 85 percent were injured in other vehicles as a result of colliding with Ford F-150s.
  • the injury data table 600 may include any other suitable injury data for past collisions involving Ford F-150s having dented rear quarter panels requiring moderate repairs. While the injury data table 600 is specific to injury data for Ford F-150s having dented rear quarter panels requiring moderate repairs, there may be several other injury data tables for Ford F-150s having one or more other damaged vehicle parts with varying extents of damage. There may also be several other injury data tables for other vehicle makes and/or models. Moreover, the injury data table 600 may be specific to those injured in Ford F-150s, and there may be a separate injury data table and/or injury data for those injured by Ford F-150s.
  • the example injury data table 600 of FIG. 6 may be compared with the claimed injury for detecting a risk of fraud.
  • the injury claim may be compared to injury data for similar type vehicles and having similar crash characteristics and/or similar extent of damage as the damaged vehicle (block 508 ). For example, if the injury claim is a claim for a severe back injury from the driver of a Ford F-150 that is determined to have a dented rear quarter panel requiring moderate repairs, the injury claim may be compared to the injury data table 600 of FIG. 6 to determine whether the injury claim matches with the injury data (block 510 ).
  • the processing center 102 may compare the percentage of people injured in the injury data to a predetermined threshold likelihood, i.e., 20 percent. If the percentage of people injured in the injury data exceeds the predetermined threshold likelihood, a suspicious loss indicator may not be generated (block 516 ). On the other hand, if the percentage of people injured in the injury data is less than the predetermined threshold likelihood, a suspicious loss indicator may be generated (block 512 ) and transmitted to an insurance agent, a claims center, etc. (block 514 ).
  • a predetermined threshold likelihood i.e. 20 percent.
  • the total percentage of people injured for similar type vehicles and having similar crash characteristics and/or similar extent of damage as the damaged vehicle may not be the only criteria for determining whether the injury claim matches with the injury data.
  • Other criteria may include the percentage of people having the same type of injury (e.g., back, neck, head, etc.), the same injury severity (e.g., minor injuries, moderate injuries, severe injuries), the same location within the vehicle (e.g., driver's seat, passenger front seat, back right seat, etc.), the same vehicle (e.g., in the Ford F-150 or collided with the Ford F-150), etc.
  • Each of these criteria may be compared to a same and/or different threshold likelihoods to determine whether the injury claim matches the injury data.
  • the injury data may be compared to one or more of the different threshold likelihoods to determine whether the injury claim matches the injury data.
  • the processing center 102 may determine for the injury claim to match the injury data, at least 20 percent of the people must have been injured, at least 10 percent must have suffered the same type of injury, at least 5 percent must have suffered the same or a worse injury severity, etc.
  • a suspicious loss indicator may be generated.
  • the suspicious loss indicator may be represented by the percentage or number of people claiming the same or similar injuries from similar past collisions.
  • the suspicious loss indicator may also be a phrase such as, “high risk,” “medium risk,” “low risk,” etc., a symbol, a color, or any other suitable indicator.
  • a risk of fraud may also be detected by comparing the cost of repair from a treatment facility to a cost estimate for the repair, for example, as determined by the repair codes. If the cost of repair from the treatment facility exceeds the cost estimate by a substantial amount, the cost of repair may be flagged as a risk of fraud and a suspicious loss indicator may be generated and transmitted to an insurance agent, a claims center, etc. That is, based on the extent of vehicle damage estimated by the comparison of the crash information to the collision data, the system may detect a risk of fraud by a policy holder or another person involved in the crash.
  • FIG. 7 illustrates a block diagram of an example treatment system 900 capable of being incorporated into the treatment system 100 shown in FIG. 1 and supporting the processes described herein for treating a vehicle damaged in a crash.
  • the high-level architecture of the vehicle treatment system 900 includes both hardware and software applications, as well as various data communications channels for communicating data between the various hardware and software components.
  • the vehicle treatment system 900 may be divided into front-end components 902 and back-end components 904 .
  • the front-end components 902 include one or more computing devices, such as a mobile computing device 910 and/or an on-board computing device 914 .
  • Either computing device 910 , 914 may be permanently or removably attached to a vehicle 908 and may interface with various sensors coupled to the vehicle 908 (e.g., a speedometer, an accelerometer, a compass, a global position unit (GPS), spatial sensor disposed throughout the vehicle, etc.) and/or may interface with various external output devices in the vehicle 908 , such as one or more tactile alert systems, one or more speakers, one or more displays devices, etc.
  • sensors coupled to the vehicle 908 e.g., a speedometer, an accelerometer, a compass, a global position unit (GPS), spatial sensor disposed throughout the vehicle, etc.
  • GPS global position unit
  • Each of the mobile computing device 910 and the on-board computing device 914 is capable of performing all of the functions of the computing device described herein or may supplement the functions performed by the other computing device.
  • the mobile computing device 910 and on-board computing device 914 may communicate with one another directly over a wired or wireless link 916 .
  • the mobile computing device 910 and the on-board computing device 914 may communicate with a network 930 over wired or wireless links 912 , 918 , respectively.
  • the network 930 may be a proprietary network, a secure public internet, a virtual private network, or some other type of network, such as dedicated access lines, plain ordinary telephone lines, satellite links, etc., and combinations thereof. Where the network 930 comprises the internet, data communications may take place over the network 930 via an internet communication protocol.
  • the treatment system 900 may also include a notification alert system 920 (e.g., automatic collision notification (ACN), advanced automatic collision or crash notification (AACN), event data recorder (EDR)), that may record and/or transmit information associated with treating the vehicle 908 after being involved in a crash.
  • ACN automatic collision notification
  • AACN advanced automatic collision or crash notification
  • EDR event data recorder
  • the front-end components 902 and the back-end components 904 communicate via the communication network 930 .
  • the back-end components 904 include a computing device such as a server 940 device or system.
  • the server device 940 may include one or more processors 962 adapted, configured, and/or operatively coupled to and/or within an analyzer to execute various software applications and/or modules of the vehicle treatment system 900 , in addition to other software routines.
  • the server device 940 may further include a database 946 adapted to store the various software applications, modules, and/or routines as well as data related to the operation of the vehicle treatment system 900 .
  • the data may include, for example, information collected by the mobile computing device 910 and/or the on-board computing device 914 pertaining to the vehicle treatment system 900 and uploaded to the server device 940 , such as sensor inputs, analyses corresponding to the methods discussed above, and images.
  • Other kinds of information that may be stored in the database may include historical vehicle collision data compiled from crash data involving vehicles categorized in the same or similar type of vehicle as the vehicle 908 and contact information relating to vehicle service repair and/or salvage treatment facilities, part suppliers, vehicle transporters, vehicle owner, insurance personnel, etc.
  • the computing devices 910 , 914 and/or server device 940 may access or store data and/or software applications in the database 946 when executing various functions and tasks associated with the operation of the vehicle treatment system 900 .
  • the vehicle treatment system 900 is shown to include one server device 940 , one mobile computing device 910 , and one on-board computing device 914 , it should be understood that additional server devices 940 , mobile computing devices 910 , and on-board computing devices 914 may be utilized.
  • the system 900 may include several server devices 940 and numerous mobile computing devices 910 , all of which may be interconnected via the network 930 .
  • the mobile computing device 910 may perform the various functions described herein in conjunction with the on-board computing device 914 or alone
  • the on-board computing device 914 may perform the various functions described herein in conjunction with the mobile computing device 910 or alone. In either instance, the mobile computing device 910 or on-board computing device may not need to be present.
  • the processing performed by the one or more server devices 940 may be distributed among a plurality of server devices 940 configured in an arrangement known as “cloud computing.”
  • This arrangement may provide several advantages, such as, for example, enabling near real-time uploads and downloads of information as well as periodic uploads and downloads of information.
  • This arrangement may provide for a thin-client embodiment of the mobile computing device 910 and/or on-board computing device 914 described herein as well as a primary backup of some or all of the data gathered by the mobile computing device 910 and/or on-board computing device 914 .
  • All of the information involved with the treatment system 100 may be displayed in a variety of formats at the server device 940 , wherein system personnel and/or the processing center 102 is provided access to such information for treating the damaged vehicle.
  • the server device 940 may have a controller 955 that is operatively connected to the database 946 via a link 956 .
  • the controller 955 may also be operatively connected to the network 930 via a communication link 935 . It should be noted that, while not shown, additional databases may be linked to the controller 955 in a known manner.
  • the controller 955 may include a program memory 960 , a processor 962 (e.g., a microprocessor or a microcontroller), a random-access memory (RAM) 964 , input/output (I/O) circuitry 966 , and a user interface module 963 all of which may be interconnected via an address/data bus 965 .
  • the user interface module 963 facilitates human-to-machine interaction and may include a display screen, keyboard, mouse device, microphone, speaker, etc.
  • the I/O circuitry 966 is shown as a single block, the I/O circuitry 966 may include a number of different types of I/O circuits.
  • the program memory 960 may be configured to store computer-readable instructions that when executed by the processor 962 cause the server device 940 to implement a server application 942 and/or a web server 943 .
  • the instructions for the server application 942 may cause the server device 940 to implement the methods described herein. While shown as a single block in FIG.
  • the server application 942 may include a number of different programs, modules, routines, sub-routines, etc., that may separately or collectively cause the server device 940 to implement the server application 942 .
  • the controller 955 may include multiple processors and/or microprocessors.
  • the memory of the controller 955 may include multiple RAMs 964 and multiple program memories 960 .
  • the RAM(s) 964 and program memories 960 may be implemented as semiconductor memories, magnetically readable memories, and/or optically readable memories, for example.
  • the instructions for the server application 942 and web server 943 are shown being stored in the program memory 960 , the instructions may additionally or alternatively be stored in the database 946 and/or RAM 964 .
  • the vehicle treatment system 900 may include only the front-end components 902 .
  • a mobile computing device 910 and/or on-board computing device 914 may perform any and/or all of the processing associated with compiling or gathering crash information, determining a treatment complexity level based on the crash information, determining a treatment for the vehicle based on the a treatment complexity level; and transmitting information associated with the treatment of the vehicle.
  • the mobile computing device 910 may include a user interface module 1002 , a positioning module 1006 such as a global positioning system (GPS) module, a communication module 1020 which may include one or more wireless radios, a forward image capture module 1018 , a rearward image capture module 1022 , an accelerometer array 1024 , and a controller 1004 .
  • the on-board computing device 914 may include a user interface module 1002 , a GPS module 1006 , a communication module 1020 which may include one or more wireless radios, a forward image capture module 1018 , a rearward image capture module 1022 , an accelerometer array 1024 , and a controller 1004 .
  • the mobile computing device 910 and on-board computing device 914 may be integrated into a single device that can perform the functions of both devices. It will be appreciated that functions performed by either the mobile computing device 910 or the on-board computing device 914 may also be performed by the on-board computing device 914 in cooperation with the mobile computing device 910 .
  • the mobile computing device 910 may be a general-use mobile personal computer, cellular phone, smartphone, tablet computer, wearable computer (e.g., a watch, glasses, etc.), or a device dedicated to facilitating treatment of a damaged vehicle.
  • the on-board computing device 914 may be a general-use on-board computer capable of performing the functions relating to vehicle operation or dedicated to facilitate treatment of a damaged vehicle.
  • the on-board computing device 914 may be installed by the manufacturer of the vehicle 908 or as an aftermarket modification to the vehicle. Further, the mobile computing device 910 and/or on-board computing device 914 may be a thin-client device that outsources some or most processing to the server device 940 .
  • the controller 1004 includes a program memory 1008 , a microprocessor (MP) 1010 , a random-access memory (RAM) 1012 , and input/output (I/O) circuitry 1016 , all of which are interconnected via an address/data bus 1014 .
  • the I/O circuitry 1016 is depicted in FIG. 10 as a single block, the I/O circuitry 1016 may include a number of different types of I/O circuits.
  • the program memory 1008 includes an operating system 1026 , a data storage device 1028 , a plurality of software applications 1030 , and a plurality of software routines 1034 .
  • the operating system 1026 may include one of a plurality of mobile platforms such as the iOS®, AndroidTM, Palm® webOS, Windows® Mobile/Phone, BlackBerry® OS, or Symbian® OS mobile technology platforms, developed by Apple Inc., Google Inc., Palm Inc. (now Hewlett-Packard Company), Microsoft Corporation, Research in Motion (RIM), and Nokia, respectively.
  • the data storage 1028 may include application data for the plurality of applications 1030 , routine data for the plurality of routines 1034 , and other data necessary to interact with the server 940 through the network 930 .
  • the data storage device 1028 may include vehicle collision data associated with a vehicle type that includes the vehicle 908 .
  • the vehicle type may include the make, model, and year of the vehicle.
  • the vehicle collision data may include one or more compilations of recorded measurements of damaged vehicle parts and components and the corresponding acceleration and derived vectors, e.g., velocity and direction, of such characteristics attributed for the damage.
  • the controller 1004 may also include, or otherwise be operatively coupled for communication with other data storage mechanisms (e.g., one or more hard disk drives, optical storage drives, solid state storage devices, etc.) that may reside within the mobile computing device 910 and/or on-board computer 914 or operatively coupled to the network 930 and/or server device 940 .
  • the GPS module 1006 may use “Assisted GPS” (A-GPS), satellite GPS, or any other suitable global positioning protocol or system that locates vehicle 908 via the position of the mobile computing device 910 and/or on-board computing device 914 .
  • A-GPS utilizes terrestrial cell phone towers or Wi-Fi hotspots (e.g., wireless router points) to more accurately and more quickly determine the location of the vehicle 908 via the mobile computing device 910 and/or on-board computing device 914 while satellite GPS is generally more useful in more remote regions that lack cell towers or Wi-Fi hotspots.
  • the GPS module 1006 may also facilitate the determination of the velocity and direction of the vehicle 908 , via the coupling of the mobile computing device 910 and/or on-board computing device 914 to the vehicle.
  • the accelerometer array 1024 is one example of a telematics device or module that may incorporate one or more accelerometers positioned to determine the acceleration and direction of movements of the mobile computing device 910 and/or on-board computing device 914 , which effectively correlate to the acceleration and direction of movements of the vehicle 908 .
  • the accelerometer array 1024 may include an X-axis accelerometer 1024 x, a Y-axis accelerometer 1024 y, and a Z-axis accelerometer 1024 z to measure the acceleration and direction of movement in each respective dimension.
  • a three dimensional vector describing a movement of the vehicle 908 via the mobile computing device 910 and/or on-board computing device 914 through three dimensional space can be established by combining the outputs of the X-axis, Y-axis, and Z-axis accelerometers 1024 x, y, z using known methods.
  • Single- and multi-axis models of the accelerometer 1024 are capable of detecting magnitude and direction of acceleration as a vector quantity, and may be used to sense orientation and/or coordinate acceleration of the vehicle 908 .
  • the forward and rearward image capture module 1018 , 1022 may be built-in cameras within the mobile computing device 910 and/or on-board computing device 914 and/or may be peripheral cameras, such as webcams, cameras installed inside the vehicle 908 , cameras installed outside the vehicle 908 , etc., that are communicatively coupled with the mobile computing device 910 and/or on-board computing device 914 .
  • the image capture module 1018 , 1022 may be oriented toward the front and rear of the vehicle 908 .
  • the forward image capture module 1018 may be oriented toward the front of the vehicle 908 to observe the forward area of the vehicle 908 while the rearward image capture module 1022 may be oriented toward the rear of the vehicle 908 to observe the rearward area of the vehicle 908 , or vice-versa.
  • Some embodiments of the treatment system 900 may have both a forward image capture module 1018 and a rearward image capture module 1022 , but other embodiments may have only one or no image capture module.
  • either or both of the forward image capture module 1018 and the rearward image capture module 1022 may include an infrared illuminator 1018 i, 1022 i , respectively, to facilitate low light and/or night image capturing. Such an infrared illuminator 1018 i, 1022 i may be automatically activated when light is insufficient for image capturing.
  • the GPS module 1006 , the image capture modules 1018 , 1022 , and the accelerometer array 1024 may be referred to collectively as the “sensors” of the mobile computing device 910 and/or on-board computing device 914 .
  • additional GPS modules 1006 , image capture modules 1018 , 1022 , and/or the accelerometer arrays 1024 may be operatively coupled to the mobile computing device 910 and/or on-board computing device 914 .
  • the mobile computing device 910 and/or on-board computing device 914 may also include or be coupled to other sensors such as a thermometer, microphone, thermal image capture device, biomedical sensor, etc.
  • the microphone may be incorporated with the user interface module 1002 and used to receive voice inputs from the vehicle operator while the thermometer and/or thermal image capture device may be used to determine fire or heat damage to the vehicle 908 , and the biomedical sensor may capture biological characteristics of the vehicle operator.
  • the communication module 1020 may communicate with the server device 940 via any suitable wired or wireless communication protocol network, such as a wireless telephony network (e.g., GSM, CDMA, LTE, etc.), a Wi-Fi network (802.11 standards), a WiMAX network, a Bluetooth network, etc.
  • the communication unit 1020 may also be capable of communicating using a near field communication standard (e.g., ISO/IEC 18092, standards provided by the NFC Forum, etc.).
  • the mobile computing device 910 and/or on-board computing device 914 may include the user-input interface 1002 , which may include a “soft” keyboard that is presented on a display screen of the mobile computing device 910 and/or on-board computing device 914 , an external hardware keyboard communicating via a wired or a wireless connection (e.g., a Bluetooth keyboard), and an external mouse, or any other suitable user-input device or component (see examples in FIGS. 9-12 ).
  • the user-input module 1002 may also include a microphone (not shown) capable of receiving voice input from a vehicle operator as well as a display screen.
  • FIG. 8 depicts only one microprocessor 1010
  • the controller 1004 may include multiple microprocessors 1010 .
  • the memory of the controller 1004 may also include multiple RAMs 1012 and multiple program memories 1008 .
  • the controller 1004 may implement the RAM 1012 and the program memories 1008 as semiconductor memories, magnetically readable memories, and/or optically readable memories, for example.
  • the one or more processors 1010 may be adapted, configured, and/or operatively coupled to and/or within an analyzer to execute any of the plurality of software applications 1030 and/or any of the plurality of software routines 1034 residing in the program memory 1008 , in addition to other software applications.
  • One of the plurality of applications 1030 may be a client application 1032 that may be implemented as a series of machine-readable instructions for performing the various functions associated with implementing the vehicle treatment system 900 as well as receiving information at, displaying information on, and transmitting information from the mobile device 910 and/or the on-board computing device 914 .
  • a client application 1032 may function to implement a system wherein the front-end components 902 communicate and cooperate with back-end components 904 as described above.
  • the client application 1032 may include machine-readable instructions for implementing the user interface 1002 to allow a user to input commands to, and receive information from, the vehicle treatment system 900 .
  • One of the plurality of applications 1030 may be a native web browser 1036 , such as Apple's Safari®, Google AndroidTM mobile web browser, Microsoft Internet Explorer® for Mobile, Opera MobileTM, that may be implemented as a series of machine-readable instructions for receiving, interpreting, and displaying web page information from the server device 940 or other back-end components 904 while also receiving inputs from the vehicle operator.
  • Another application of the plurality of applications may include an embedded web browser 1042 that may be implemented as a series of machine-readable instructions for receiving, interpreting, and displaying web page information from the server device 940 or other back-end components 904 within the client application 1032 .
  • Another of the plurality of client applications 1030 or routines 1034 may include an accelerometer routine 1038 that determines the acceleration and direction of movements of the mobile computing device 910 and/or on-board computing device 914 , which correlate to the acceleration and direction of the vehicle 908 .
  • the accelerometer routine may process data from the accelerometer array 1024 to determine one or more vectors describing the motion of the vehicle 908 for use with the client application 1032 .
  • the accelerometer routine 1038 may combine the data from each accelerometer 1024 x,y,z to establish the vectors describing the motion of the vehicle 908 as it moves through three dimensional space.
  • the accelerometer routine 1038 may use data pertaining to less than three axes.
  • Another routine in the plurality of applications 1030 or routines 1034 may include a vehicle velocity routine 1040 that coordinates with the GPS module 1006 to retrieve vehicle velocity and direction information for use with one or more of the plurality of applications, such as the client application 1032 , or for use with other routines.
  • a vehicle velocity routine 1040 that coordinates with the GPS module 1006 to retrieve vehicle velocity and direction information for use with one or more of the plurality of applications, such as the client application 1032 , or for use with other routines.
  • routines 1034 may include an image capture routine that coordinates with the image capture modules 1018 , 1022 to retrieve image data for use with one or more of the plurality of applications, such as the client application 1032 , or for use with other routines.
  • Another routine in the plurality of application 1030 or routines 1034 may include a position determination routine that coordinates with the spatial sensors disposed throughout the vehicle to determine the positions of vehicle parts relative to the vehicle for use with one or more of the plurality of applications, such as the client application 1032 , or for use with other routines.
  • the user or vehicle operator may also launch or instantiate any other suitable user interface application (e.g., the native web browser 1036 , or any other one of the plurality of software applications 1030 ) to access the server device 940 to implement the vehicle treatment system 900 . Additionally, the user or vehicle operator may launch the client application 1032 from the mobile computing device 910 and/or on-board computing device 914 , to access the server device 940 to implement the vehicle treatment system 900 .
  • any other suitable user interface application e.g., the native web browser 1036 , or any other one of the plurality of software applications 1030
  • the user or vehicle operator may launch the client application 1032 from the mobile computing device 910 and/or on-board computing device 914 , to access the server device 940 to implement the vehicle treatment system 900 .
  • a treatment for the vehicle 908 can be determined.
  • the mobile computing device 910 and/or on-board computing device 914 may determine that the damaged vehicle can be repaired or scrapped, and where the damaged vehicle may be taken for such treatment.
  • the mobile computing device 910 and/or on-board computing device 914 may also transmit information associated with the treatment of the damaged vehicle.
  • the transmitted information may be sent to a treatment facility capable of performing the treatment and/or the information may be sent to a transportation facility and include a request to transport the damaged vehicle to the treatment facility.
  • the mobile computing device 910 and/or on-board computing device 914 may display on the user interface 1002 an initial loss report screen including, for example, a cost estimate for treating the vehicle, for example, based on one or more treatment codes.
  • the initial loss report screen may also include other treatment information such as the crash information, the vehicle type including make and model, the treatment complexity level, an estimated duration for repairing the vehicle, a list of treatment facilities capable of treating the vehicle and their respective availabilities, etc.
  • the display may also include options allowing the user to select a treatment facility from the list of treatment facilities, transfer funds into the user's personal account, schedule a rental car, etc.
  • the server device 940 may perform many of the processing functions remotely that may otherwise be performed by system personnel and/or the mobile computing device 910 and/or on-board computing device 914 .
  • the server device 940 may include a number of software applications capable of receiving vehicle operating information gathered by the sensors and/or acquiring collision data to be used in determining the extent of damage to the vehicle 908 involved in the crash.
  • the mobile computing device 910 and/or on-board computing device 914 may gather information from its sensors as described herein, but instead of using the information locally, the mobile computing device 910 and/or on-board computing device 914 may send the information to the server device 940 for remote processing.
  • the server device 940 may perform the analysis of the gathered crash information to determine the amount of damage to the vehicle 908 as described herein.
  • the server device 940 may then determine whether the damaged vehicle can be repaired or scrapped, and where the damaged vehicle may be taken for such treatment.
  • the server device 940 may also transmit information associated with the treatment of the damaged vehicle.
  • the information transmitted by the server device 940 may be sent to a treatment facility and/or a transport facility and include a request to transport the damaged vehicle to the treatment facility, or the server device 940 may transmit the information to the mobile computing device 910 and/or on-board computing device 914 .
  • FIGS. 9-12 depict application pages that may be presented on the user interface 1002 of the mobile computing device 910 as part of the user interface used to implement the vehicle treatment system 900 . While FIGS. 9-12 depict pages or screens of information capable of being presented on the display 1002 of the mobile computing device 910 , it is to be understood that the application pages or screens of information could be displayed on the display 1002 of the on-board computing device 914 in addition to being displayed on the mobile device 910 or as an alternative. In addition, the application pages may also be displayed on the user interface 963 of the server device 940 . The applications or pages may be generated by the mobile computing device 910 / 914 or sent to the mobile computing device 910 / 914 by the server 940 (e.g., as with a thin client).
  • the user may launch the application from the mobile computing device 910 / 914 via any suitable manner, such as touch-selecting a start application icon 1104 on the display 1002 of the mobile computing device 910 / 914 or speaking a voice command into the microphone (not shown) of the mobile computing device 910 / 914 .
  • the application 1032 may begin to run on the mobile computing device 910 / 914 as described above in connection to block 202 , FIG. 2 ; or the mobile computing device 910 may communicate with the on-board computing device 914 and the client application 1032 may begin to run on the on-board computing device 914 .
  • a monitor screen 1100 of the client application and/or routine may be displayed on the screen of the mobile computing device 910 / 914 .
  • the monitor screen 1100 may include a ‘Calibrate” tab 1102 , a “Start” tab 1104 , a “Settings” tab 1106 , and a ‘Report’ tab 1108 .
  • the client application may execute a calibration routine.
  • a calibration screen (not shown) may be displayed on the screen of the mobile computing device 910 / 914 during execution of the calibration routine, wherein the progress of the calibration routine may be indicated by an illustration showing the approximate status of the calibration routine.
  • a user may cancel the calibration and/or set the calibration routine to run in the “background,” so as not to appear on the screen 1100 of the mobile computing device 910 / 914 .
  • the client application may begin to monitor and collect data about vehicle operation.
  • the collected data may be stored as described above and/or additional data may be mathematically determined from the collected data about vehicle operation and also stored.
  • a vehicle monitor screen 1200 shown in FIG. 10 may be displayed on the screen of the mobile computing device 910 / 914 .
  • the vehicle monitor screen 1200 may include a “Stop” tab 1202 . If the “Stop” tab 1202 is selected by the user, the vehicle treatment system 900 will terminate vehicle operation monitoring.
  • the vehicle treatment system 900 may also be stopped by a voice command of the user.
  • the vehicle treatment system 900 e.g., gathering and analyzing of the vehicle operation and/or collision data, may be ceased by the mobile computing device 910 / 914 detecting that the engine of the vehicle 908 has stopped.
  • a settings screen 1300 may be displayed on the screen of the mobile computing device 910 / 914 .
  • the settings screen 1300 may include a variety of information that the user or vehicle operator may enter into the vehicle treatment system 900 via a “soft” keyboard 1306 of the user interface of the mobile computing device 910 / 914 .
  • Such information may include the vehicle owner's name and/or contact information 1302 .
  • Additional information may include the make, model, and year of the vehicle type 1304 of the vehicle 908 that will be utilized with the treatment system 900 .
  • the settings screen 1300 may also include a variety of parameters that may be entered and adjusted by the user, such as the mode for turning on the treatment system 900 , i.e., manual or automatic, etc.
  • the parameters may be modified and saved by the user or vehicle operator via selection of a “Save” tab 1308 of the user interface on the mobile computing device 910 / 914 .
  • a report screen 1400 may be displayed on the screen of the mobile device 910 / 914 .
  • the report screen 1400 may include a list of contacts 1402 to be notified in the event of a crash.
  • the contact list 1402 may include the vehicle owner, insurance agent, etc., and may be entered and/or modified by the user via a “soft” keyboard 1406 of a user interface of the mobile computing device 910 .
  • the list of contacts 1402 may be saved by the user or vehicle operator via selection of the “Save” tab 1408 of the user interface of the mobile computing device 910 .
  • routines, subroutines, applications, or instructions may constitute either software (e.g., code embodied on a machine-readable medium) or hardware.
  • routines, etc. are tangible units capable of performing certain operations and may be configured or arranged in a certain manner.
  • one or more computer systems e.g., a standalone, client or server computer system
  • one or more hardware modules of a computer system e.g., a processor or a group of processors
  • software e.g., an application or application portion
  • a hardware module may be implemented mechanically or electronically.
  • a hardware module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC) to perform certain operations.
  • a hardware module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.
  • the term “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein.
  • hardware modules are temporarily configured (e.g., programmed)
  • each of the hardware modules need not be configured or instantiated at any one instance in time.
  • the hardware modules comprise a general-purpose processor configured using software
  • the general-purpose processor may be configured as respective different hardware modules at different times.
  • Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.
  • Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple of such hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).
  • a resource e.g., a collection of information
  • processors may be temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions.
  • the modules referred to herein may, in some example embodiments, comprise processor-implemented modules.
  • the methods or routines described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented hardware modules. The performance of certain operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.
  • the performance of certain operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines.
  • the one or more processors or processor-implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the one or more processors or processor-implemented modules may be distributed across a number of geographic locations.
  • any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment.
  • the appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
  • Coupled and “connected” along with their derivatives.
  • some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact.
  • the term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still cooperate or interact with each other.
  • the embodiments are not limited in this context.
  • the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion.
  • a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
  • “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).

Abstract

An example method for estimating vehicle repair costs includes receiving, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyzing the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determining one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determining a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmitting an indication of the cost estimate.

Description

    CROSS REFERENCE TO RELATED APPLICATIONS
  • This application is a continuation of U.S. patent application Ser. No. 15/720,790 entitled “SYSTEM, METHOD, AND COMPUTER-READABLE MEDIUM FOR COMPARING AUTOMATICALLY DETERMINED CRASH INFORMATION TO HISTORICAL COLLISION DATA TO DETECT FRAUD,” filed on Sep. 29, 2017, which is a continuation of U.S. patent application Ser. No. 14/732,331 entitled “SYSTEM, METHOD, AND COMPUTER-READABLE MEDIUM FOR FACILITATING DELIVERY OF REPLACEMENT PARTS FOR A DAMAGED VEHICLE,” filed on Jun. 5, 2015, which claims the benefit of U.S. Provisional Patent Application No. 62/023,711 entitled “SYSTEM AND METHOD FOR AUTOMATED VEHICLE REPAIR TRIAGE,” filed on Jul. 11, 2014, the entire contents of which are hereby expressly incorporated by reference.
  • TECHNICAL FIELD
  • The present disclosure generally relates to a system and a method for treating a vehicle damaged in a crash, and more particularly, to determining a repair cost estimate based on historical collision data.
  • BACKGROUND
  • Every year, vehicles are involved in collisions that result in varying amounts of damage to the vehicle. If the damaged vehicle is insured, an insurance claim is usually filed shortly after the collision. The damaged vehicle is typically brought to a location where an appraisal or assessment of the damage is made. Depending on the extent of the damage and the treatment facility where the damaged vehicle was brought, the damaged vehicle may then need to be further transported to a different treatment facility that is capable of performing the necessary repairs, or in the case where the damage is too costly to repair, to a salvage or a scrap facility. Additional costs are incurred when the damaged vehicle is brought to a first location for the initial appraisal and then to a subsequent location for the repair or salvage. By determining the extent of damage to the vehicle and the corresponding treatment shortly after a collision, the time and costs involved to currently process an insurance claim may be reduced.
  • SUMMARY
  • A first example embodiment is a method, executed in part by one or more processors programmed to perform the method, for estimating vehicle repair costs. The method may include receiving, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyzing the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determining one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determining a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmitting an indication of the cost estimate.
  • Another example embodiment is a system for estimating vehicle repair costs. The system comprises a computing device including one or more processors, and one or more memory devices coupled to the one or more processors of the computing device, the one or more memory devices storing executable instructions that when executed by the one or more processors of the computing device cause the system to: receive, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyze the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determine one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determine a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmit an indication of the cost estimate.
  • A further example embodiment is a tangible, computer-readable medium storing instructions that when executed by one or more processors of a computer system cause the computer system to: receive, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyze the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determine one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determine a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmit an indication of the cost estimate.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The figures described below depict various aspects of the systems and methods disclosed herein. It should be understood that each figure depicts an embodiment of a particular aspect of the disclosed system and methods, and that each of the figures is intended to accord with a possible embodiment thereof. Further, wherever possible, the following description refers to the reference numerals included in the following figures, in which features depicted in multiple figures are designated with consistent reference numerals.
  • FIG. 1 is a general overview of a vehicle treatment system for treating a vehicle damaged in a crash;
  • FIG. 2 depicts an example vehicle treatment process capable of being implemented in the vehicle treatment system illustrated in FIG. 1 in accordance with the presently described embodiments;
  • FIG. 3 depicts an example table of vehicle treatment codes (e.g., repair) for estimating the cost of repairing vehicle damage in accordance with the presently described embodiments;
  • FIG. 4 depicts an example damaged vehicle including vehicle treatment codes (e.g., repair) for various vehicle parts in accordance with the presently described embodiments;
  • FIG. 5 depicts an example method for detecting a risk of insurance fraud based on collision data in accordance with the presently described embodiments;
  • FIG. 6 depicts an example injury data table in accordance with the presently described embodiments;
  • FIG. 7 is a block diagram depicting an example mobile computing device, an on-board computing device, a server device, and a communication network that may configured in the example system for treating a damaged vehicle in accordance with the described embodiments;
  • FIG. 8 is a block diagram of an example mobile computing device capable of being implemented in the example system shown in FIG. 9; and
  • FIGS. 9-12 depict example embodiments of information displayed on the one or more user interfaces of the one or more computing devices in accordance with the presently described embodiments.
  • DETAILED DESCRIPTION
  • A vehicle treatment system utilizes crash information of a vehicle involved in a crash to approximate the extent of damage to the vehicle and determine a treatment facility for treating the damaged vehicle. The estimated vehicle damage is used to generate repair codes for repairing the vehicle and estimate the total cost of repair. Moreover, the estimated vehicle damage is also used to detect a risk of insurance fraud by a policy holder or another person involved in the crash with the vehicle, and also to calculate a treatment complexity level for treating the vehicle. Based on a determined treatment complexity level, the system identifies a treatment facility capable of treating the damaged vehicle and sends information for transporting the damaged vehicle to the treatment facility, thereby removing the need to initially bring the damaged vehicle to an interim location for a damage assessment before transporting the damaged vehicle to a designated treatment facility for treatment.
  • More specifically, the vehicle treatment system receives crash information associated with a vehicle involved in a crash. The crash information may be transmitted within a data transmission, which may include information about or associated with the damaged vehicle, sensor data, damage descriptions, and/or images that may pertain to aspects of the crash, such as vehicle operating characteristics near or at the time of the crash (impact characteristics), e.g., vehicle acceleration, vehicle velocity, and/or impact direction. To estimate the extent of vehicle damage caused in the crash, the system may analyze one or more aspects of the crash information. For example, the system may analyze vehicle operating data received from sensors operatively coupled to the vehicle to calculate an estimate of the amount of vehicle damage base on the force characteristics of the crash. The system may also calculate an estimate of the amount of damage by analyzing a description and/or image of the damaged vehicle. Based on the extent of vehicle damage estimated by the analysis of the crash information, the treatment complexity level for treating the damaged vehicle may be determined.
  • The analysis for estimating the amount of vehicle damage may include comparing the crash information to collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle. The collision data may include various levels of vehicle damage associated with specified aspects or characteristics of collision information related to other vehicles of the same or similar type as the vehicle damaged in the crash. One or more categories of vehicle damage in the collision data may be equated to particular vehicle acceleration or velocity, or a range of vehicle acceleration or velocity occurring at or near the time of impact of the crash. The one or more categories of vehicle damage in the collision data may also be equated to a particular description, image, illustration, etc., of a damaged vehicle. Based on the extent of vehicle damage estimated by substantially matching the crash information to comparable characteristics in the collision data, the treatment complexity level for treating the damaged vehicle may be determined.
  • The treatment complexity level is an estimate indicating the level of involvement, e.g., effort, cost; associated with treating the damaged vehicle. The treatment of the vehicle may include repairing or replacing damaged vehicle parts, and in some instances where repairing the vehicle is too costly and not worth repairing (e.g., total loss), the treatment may include salvaging or scrapping the damaged vehicle. Damaged vehicles designated as a total loss, but which include some value (e.g., salvageable vehicle parts), may be sold as is, or repaired to some extent for resale. In addition, the undamaged vehicle parts of a total loss vehicle may be salvaged and stored, reused, or sold.
  • In some embodiments, the treatment complexity level may be determined for each damaged vehicle part and/or groups of damaged vehicle parts using treatment codes and/or vehicle parts lists. For example, the hood of a damaged vehicle may require minor repairs whereas the fender may be damaged significantly and require major repairs. Alternatively, the treatment complexity level may be determined for groups of vehicle parts using treatment codes and/or lists of damaged and/or undamaged vehicle parts. For example, one treatment code may propose repairs and/or replacement to one group of vehicle parts and be classified as a minor repair; while another treatment code may propose repairs and/or replacement to one or more critical vehicle parts and be classified as a major repair or a total loss.
  • Several factors may affect the determination of the treatment complexity level, including, and not limited to, the market value of the vehicle type (e.g., make, model, trim level, and/or year of manufacture) that includes the damaged vehicle and the corresponding vehicle parts. The treatment complexity level may also be determined in part on the market value of the treatment services provided by treatment personnel involved with the prescribed treatment of the damaged vehicle. Generally, the market value may be based on a set schedule with incremental adjustments over a predetermined period of time, e.g., depreciation over the life expectancy of the vehicle type. However, if the market value should suddenly change due to an unforeseen circumstance, the scheduled market value may become outdated and less useful. Using outdated market values for vehicle parts and/or services may result in miscalculated and inaccurate determinations of the treatment complexity level.
  • To accommodate for sudden and/or unforeseen changes in the market value of a vehicle, its vehicle parts, and/or potential vehicle treatment services associated with the vehicle, one or more market values may be monitored and used in the determination of the treatment complexity level. For example, on-demand or periodic (e.g., hourly, daily) monitoring of the market value may be implemented to adapt to a sudden and/or unforeseen change in a market value. Some examples of sudden and/or unforeseen changes that may affect the market value of a vehicle, its vehicle parts, and/or associated treatment services include: discontinued production of a type of vehicle (e.g., make, model, trim level), and trends in vehicle popularity. By adapting to sudden and/or unforeseen changes in market value, a calculated and more accurate treatment complexity level may be used in comparison to a fixed-rate and likely defunct market value.
  • Upon determination of the treatment complexity level, information related to treating the damaged vehicle is transmitted by the system. The transmitted information may be automatically sent after the crash to one or more treatment facilities, vehicle parts suppliers, vehicle transporters, and/or persons or entities associated with the damaged vehicle, for example, the vehicle owner and/or an insurance agent. In one example embodiment, the vehicle treatment system allows for the timely delivery of replacement vehicle parts to a selected vehicle treatment facility for treating the damaged vehicle, thereby avoiding the cost and time associated with known damage assessment procedures wherein the damaged vehicle is brought to the treatment facility for inspection and assessment before treatment can be scheduled. For example, an estimate of the damage to the vehicle may be made shortly after the crash to determine whether the damaged vehicle can be repaired. If it is not feasible to repair the damaged vehicle (e.g., total loss), the damaged vehicle may be brought to a vehicle treatment facility capable of salvaging and/or scrapping the damaged vehicle. For a repairable vehicle, damaged vehicle parts that may need to be repaired and/or replaced may be identified based on the received crash information, wherein the location and availability of such replacement vehicle parts within a vehicle parts network may then be determined. An aggregated order of the identified replacement vehicle parts among the one or more vehicle parts suppliers may be compiled and a transportation route may be generated based on the location and availability of the replacement vehicle parts. A single delivery vehicle may be utilized to travel the transportation route and gather the aggregated order of replacement vehicle parts for delivery to the selected vehicle treatment facility. The cost associated with using single delivery vehicle to timely deliver the aggregated order of replacement vehicle parts from one or more vehicle parts suppliers of the vehicle parts network is likely less than the cost associated with using several delivery vehicles and/or routes to deliver the ordered replacement vehicle parts. In addition, assessing the performance and/or efficiency of the vehicle treatment process with respect to vehicle parts suppliers involved in the treatment of the damaged vehicle is more simply evaluated with a single delivery vehicle and aggregated route as compared to multiple delivery vehicles and multiple routes. For example, responsibility among the vehicle parts suppliers for a delayed delivery of the replacement vehicle parts may be more readily identifiable when one aggregated delivery route is utilized as opposed to multiple delivery routes.
  • FIG. 1 is a general overview of a system 100 capable of facilitating treatment of a vehicle damaged in a crash. As used herein, the term “vehicle” refers to any type of powered transportation device, which includes, and is not limited to, an automobile, truck, bus, motorcycle, and boat. While the vehicle may normally be controlled by an onboard operator, it is to be understood that the vehicle may be unmanned and remotely or autonomously operated in a conventional or nonconventional manner, such as using controls other than the steering wheel, gear shift, brake pedal, and accelerator pedal.
  • The system 100 in FIG. 1 includes a processing center 102 capable of facilitating an analysis of the damaged vehicle's crash information 104 to determine a treatment for the damaged vehicle. The analysis of the crash information 104, which may include the use of collision data 106, may be performed by system personnel and/or a computing device at the processing center 102. Throughout this description, the term crash is used in reference to a particular incident in which a particular vehicle of concern was damaged and the term collision is used in reference to one or more incidents in which another vehicle or vehicles were damaged.
  • The crash information 104 provided to the processing center 102 includes specific information related to a particular vehicle and the crash that damaged the particular vehicle. The crash information 104 may include information received from telematics devices, e.g., sensors, operatively coupled to the vehicle or observed by an individual, such as a vehicle operator/owner 108, a vehicle occupant, a bystander, an insurance agent/entity 110 of the damaged vehicle, an emergency responder, an accident investigator, etc. The crash information 104 may include operating characteristics of the vehicle involved in the crash such as the approximate speed of the vehicle at the time of the crash and what part(s) of the vehicle was damaged. Other observed or obtained crash information provided to system personnel and/or the processing center 102 may include whether emergency response components and/or devices were deployed, e.g., airbags; or if the damaged vehicle is drivable. Images of the damaged vehicle may also be included in the crash information 104, which may be provided for analysis and/or comparison with the collision data 106.
  • In some embodiments, the vehicle's operating information may be monitored by a series of measurements of conditions or characteristics pertaining to the operation of the vehicle. In particular, one or more computing devices such as a mobile computing device, an on-board computing device, and/or a server device may be communicatively coupled to sensors such as an accelerometer array operatively coupled to the vehicle. The accelerometer array may monitor and/or measure the acceleration/deceleration of the vehicle along several axes and/or travelling directions. Other vehicle operating information such as vehicle acceleration, velocity, and direction may be measured, logged, and stored in the system 100, for example, a data storage unit of the system or a remote storage unit communicatively coupled to the system. The operating information may be logged and/or stored discretely, periodically (e.g., every second or portion or multiple thereof), or conditionally based on an occurrence or detection of an event (e.g., a crash log).
  • The detection of a crash involving the vehicle may be facilitated in one or more novel or known ways. A crash may be detected through a near-simultaneous activation of an emergency responsive device, component, or action, such as the deployment of an air-bag, and/or an alarm or alert, e.g., automatic collision notification (ACN), etc. In another embodiment incorporating an accelerometer, a crash may be detected when a computing device operatively coupled to the accelerometer detects a significant, near immediate change (increase or decrease) in the monitored acceleration in the fore-aft, lateral, and/or vertical direction of the vehicle, e.g., X, Y, and Z axes. In a further embodiment, a crash may be detected through the use of a global positioning system (GPS) unit via detection of a near-immediate increase and/or decrease in vehicle velocity.
  • Additional crash information 104 may include a vehicle identifier such as a vehicle data identifier (VDI) associated with the damaged vehicle involved in the crash. The VDI may include sections or segments relating to one or more aspects or characteristics of the vehicle, such as, a vehicle manufacturer identifier, vehicle type identifier, a vehicle serial number, pointers to other vehicle information (e.g., market value), etc., and may include reference to the make, model, trim level, year, and/or type of vehicle as well the vehicle parts of the vehicle. The VDI may also include the vehicle's vehicle identification number (VIN) and/or portions thereof. The VIN may identify a unique vehicle and include multiple sections or segments in a standardized format that generally depends on the vehicle manufacturer and/or the country or government agency where the VIN is used, e.g., U.S.A., European Union. The sections or segments of the VIN are associated with a vehicle manufacturer identifier, vehicle type identifier, a vehicle serial number, etc., and may include reference to the make, model, trim level, year, and/or type of vehicle as well the vehicle parts of the associated vehicle.
  • Collision data 106 generally includes records or compilations of information involving other vehicles damaged in other collisions. The collision data 106 may include historical loss information having various collision scenarios including lists of damaged and/or undamaged vehicle parts, images, telematics data, and vehicle damage evaluations. Historical loss information may include recorded amounts of vehicle damage associated with or resulting from known, observed, or measured aspects relating to a collision or impact of a particular make and/or model of vehicle, such as vehicle direction, acceleration, and/or velocity, as well as relative position of vehicle parts within the vehicle. Some examples of historical loss information include vehicle collision test data, bumper test data, collision image data, traffic accident investigation data, and the like.
  • The collision data 106 may be compiled into one or more charts or tables wherein various collision aspects are associated with known, predicted, or determined vehicle damage. For example, the collision data 106 may be correlated with one or more sections or segments of the VDI and/or VIN, which may further be correlated to vehicle manufacturer information; prescribed vehicle treatments and costs; vehicle part warranties; market value estimations of various vehicle types, vehicle parts, vehicle treatment services, and/or procedures, etc. The collision data 106 may also include vehicle safety information including, and not limited to, vehicle part recall information, safety notices, repair notices, etc. The collision data 106, which may be stored in the system 100 and/or operatively coupled to the processing center 102, may be periodically and/or discretely updated to include additional vehicle operating characteristics from other collisions, vehicle part damage of other damaged vehicles of similar vehicle type, and changes to the market value of vehicles, vehicle parts, and/or prescribed vehicle treatment services.
  • FIG. 2 is a flow diagram 200 depicting an example embodiment of a vehicle treatment process that may be implemented by the treatment system 100 shown in FIG. 1. The process 200 may be executed separately or cooperatively by system personnel and the processing center 102. Vehicle crash information is received or gathered for analysis (block 202). The vehicle crash information may be provided to system personnel and/or the processing center 102 by a vehicle occupant, bystander, or emergency responder communicating characteristics of the crash. For example, the driver of the damaged vehicle may contact system personnel and/or the processing center 102 and provide operating characteristics of the vehicle near or at the time of the crash, e.g., impact characteristics such as approximate vehicle speed, description and/or image of vehicle damage, description of vehicle operation, and whether portions of the vehicle's safety system were used as a result of the crash. Some crash information, such as the VDI and/or VIN, may have previously been provided to the processing center 102 and/or system personnel.
  • Crash information may also be automatically provided to system personnel and/or the processing center 102 by the vehicle's engine control unit (ECU) and/or one or more telematics devices or components (sometimes referred to as an event data recorder (EDR)) that are capable of sensing, monitoring, and/or noting various vehicle operating characteristics, e.g., acceleration, velocity, position of vehicle parts relative to the vehicle, direction of the vehicle at the time of the crash, and deployment of emergency response equipment. The telematics devices are operatively coupled to the vehicle and may be configured to automatically function when the vehicle is in operation. When a crash is detected, data including one or more monitored operating characteristics of the vehicle may be automatically obtained and transmitted via a communication signal to system personnel and/or the processing center 102 as crash information 104.
  • The crash information 104 may be analyzed and/or evaluated by system personnel and/or the processing center 102 to determine an estimate of the extent of damage caused to the vehicle during the crash (block 204). The compilation of historical collision information 106 including vehicle operating characteristics associated with known vehicle damage from similar vehicles involved in previous collisions may be used to estimate the amount of damage that occurred to the vehicle during the crash. For example, a damage evaluation tool may include a guide or template to be used in estimating the extent of vehicle damage. Stored images and operating characteristics of other similar type vehicles damaged in other collisions may be used in the analysis to correlate with operating characteristics obtained in the crash information of the damaged vehicle. In one embodiment, the extent of vehicle damage resulting from the crash can be estimated by comparing crash information 104, e.g., images and/or vehicle operating characteristics and aspects of the crash; with collision information 106 of other similar type vehicles, e.g., make, model, and or trim level.
  • Once the extent of vehicle damage caused by the crash has been estimated, a treatment complexity level for treating the damaged vehicle may be determined (block 206) by system personnel and/or the processing center 102. The treatment complexity level may include one or more vehicle treatment components for treating the damaged vehicle, such as a pricing schema having one or more predetermined price structures associated with a vehicle, its vehicle parts, and/or services associated with treating the vehicle, e.g., treatment codes, treatment schedule, skill level and/or pay rate of treatment personnel, and/or equipment of a treatment facility used to treat the damaged vehicle.
  • The collision data 106 may include a range of treatment complexity levels corresponding to various amounts of vehicle damage, wherein various levels of vehicle damage may be equated with various levels of vehicle treatment. In particular, the range of vehicle treatment complexity levels may be delineated by the amount of involvement associated with treating a damaged vehicle, for example, repairing and/or replacing vehicle parts of the damaged vehicle, or salvaging and/or scrapping a damaged vehicle determined to be a total loss. In some embodiments, the treatment complexity level represents the difficulty associated with treating individual vehicle parts within the damaged vehicle.
  • The several levels of treatment complexity may include a speed or light repair, a medium or moderate repair, a heavy or severe repair, not repairable, scrap, and salvage, for example. A speed or light repair treatment designation may indicate or estimate that one or two vehicle parts need repair or replacement, or that minor refinishing may be required, but that no structural damage occurred to the vehicle. A medium or moderate repair treatment designation may indicate that a few vehicle parts require repair or replacement or that light structural damage occurred to the vehicle. A heavy or extensive repair treatment designation may indicate that the vehicle is not drivable, significant structural damage occurred to the vehicle, more than a predetermined amount of vehicle parts (e.g., five) need repair or replacement, or a welded-on vehicle component needs replacement. A scrap designation may indicate that the vehicle is to be scrapped and not repaired. Prior to scrapping, the damaged vehicle may be dismantled to salvage any undamaged or usable vehicle parts.
  • Each treatment complexity level may include estimates or indications of the type, time, and/or cost of treatment associated with the type of vehicle (e.g., make, model, year, trim level, etc.) and amount of vehicle parts that may be damaged, e.g., body panel (front, side, rear, quarter-panel, rocker, driver-side, and passenger-side), bumper, radiator, lights, water pump, battery, struts, frame, and gas tank. The estimated extent of vehicle damage determined by system personnel and/or the processing center 102 may include vehicle treatment codes and/or a list of damaged and/or undamaged vehicle parts. By comparing and/or matching the vehicle treatment codes and/or lists of damaged and undamaged vehicle parts of the vehicle damaged in the crash to the vehicle collision data 106, system personnel and/or the processing center 102 may identify the requisite treatment complexity level. For example, a vehicle damage estimate requiring less than 10 hours of labor time and/or $1000 in replacement vehicle parts may be designated as a low treatment complexity level; a vehicle damage estimate requiring between 10-15 hours of labor time and/or between $1000-$2500 in replacement vehicle parts may be designated as a medium treatment complexity level; a vehicle damage estimate requiring between 15-30 hours of labor time and/or between $2500-$5000 in replacement vehicle parts may be designated as a high treatment complexity level; and a vehicle damage estimate requiring more than 30 hours of labor time, and/or having costs and labor greater than the market value of the damaged vehicle in an undamaged condition, may be designated as a total loss, scrapping, and/or salvaging treatment complexity level. The total loss, scrapping, and/or salvaging designation indicates that the vehicle is not to be repaired. For such non-repairable designations, the damaged vehicle may be dismantled to salvage any undamaged or usable vehicle parts, wherein the remaining vehicle parts may be scrapped or sold.
  • Each damaged vehicle part and/or group of vehicle parts may be assigned a vehicle treatment code from a set of vehicle treatment codes based on the extent of the damage to the vehicle and/or vehicle part(s). The set of vehicle treatment codes may include a separate vehicle treatment code for each combination of crash characteristics, such as the make, model, year, and/or trim level of the vehicle being treated; the vehicle part or a list of vehicle parts being treated; the type of treatment for the vehicle part(s) including whether the vehicle part(s) needs to be repaired, replaced, salvaged, or scrapped; the extent of the damage to the vehicle part(s), etc. Each vehicle treatment code may include and/or correspond to a cost estimate. For example, a specific vehicle treatment code may include repairing the hood of a first particular vehicle type (make, model, etc.) with slight damage. Another specific vehicle treatment code may include replacing the bumper of a second particular vehicle type with heavy damage. The associated cost estimate for the vehicle treatment code for the first vehicle type may be $100 whereas the associated cost estimate for the treatment code for the second vehicle type may be $500. Each assigned vehicle treatment code may be combined to determine a total cost estimate for treating the damaged vehicle.
  • Referring now to FIG. 3, an example table 300 of vehicle treatment codes for estimating the cost of treating vehicle damage is depicted. It is to be understood that while the example table 300 includes example repair treatment codes that may be a small subset of a larger set of vehicle repair codes, other type of vehicle treatment codes may include or pertain to vehicle treatment of total loss vehicles relating to salvaging and/or scrapping values of undamaged vehicle parts. As mentioned above, the set of vehicle treatment codes may include a separate vehicle treatment code for each combination of vehicle characteristics such as make and model of the vehicle being repaired, the vehicle part being repaired, the type of repair for the vehicle part including whether the vehicle part needs to be repaired and/or replaced, the extent of the damage to the vehicle part, etc. Each vehicle treatment code may correspond to a cost estimate, where the cost estimate may be determined based on collision data including historical loss information of similar type vehicles having similar type damage. For example, the associated cost estimate for a repair code corresponding to repairing the quarter panel of a particular make, model, trim level, etc. (e.g., type) of vehicle having moderate damage may be determined by analyzing repair costs from historical loss information related to repairing quarter panels of that particular type of vehicle having moderate damage from past collisions. In some embodiments, the vehicle treatment codes may be stored in the system 100 and/or operatively coupled to the processing center 102.
  • As shown in FIG. 3, repair code 00675 (reference 304) is associated with an instruction, “Refinish Hood,” and a cost estimate, $300. While the instruction for repair code 00675 (reference 304) does not specify the extent of the damage to the hood, or the make and model of the vehicle, repair code 00675 (reference 304) may be used for refinishing hoods of a particular type of vehicle with light damage. In some embodiments, a separate repair code, for example, 10675 may be used for refinishing hoods for vehicles of a different particular type of vehicle with light damage. Moreover, yet another repair code, for example, 02675, may be used for refinishing hoods on vehicles with moderate damage. Further, in some embodiments, the set of repair codes may be based on additional or alternative vehicle characteristics and in other embodiments some of the above mentioned vehicle characteristics may be omitted from the set of repair codes.
  • As further shown in FIG. 3, repair code 00610 (reference 302) is associated with the instruction, “Repair Roof,” and a cost estimate of $700; repair code 00676 (reference 306) is associated with the instruction, “Refinish Fender,” and a cost estimate of $200; repair code 00678 (reference 308) is associated with the instruction, “Replace Grille,” and a cost estimate of $250; repair code 00679 (reference 310) is associated with the instruction, “Replace Door,” and a cost estimate of $500; repair code 00682 (reference 312) is associated with the instruction, “Replace Quarter Panel,” and a cost estimate of $400; repair code 00690 (reference 314) is associated with the instruction, “Repair Bumper,” and a cost estimate of $100; and repair code 00692 (reference 316) is associated with the instruction, “Repair Trunk Lid,” and a cost estimate of $350. Each of these repair codes may be for the same particular vehicle type and may be aggregated and/or combined to estimate the total cost of repair for a damaged vehicle of that particular type. For example, by comparing crash information for a damaged vehicle of a particular type to collision data, a list of damaged vehicle parts including the extent of the damage to each vehicle part may be generated. A repair code from the set of repair codes may then be assigned to each damaged vehicle part in the list based on the vehicle characteristics for the damaged vehicle. For example, repair code 00679 (reference 310) may be assigned when a door in a specified type of vehicle needs to be replaced. In some embodiments, repair code 00679 may be assigned twice when two doors in the specified type of vehicle need to be replaced.
  • While the example table 300 depicts eight vehicle treatment codes (e.g., vehicle repair codes for a particular type of vehicle), this is merely for ease of illustration only. There may be hundreds or thousands of repair codes, each corresponding to a different combination of vehicle characteristics. More specifically, each type may correspond to a separate subset of repair codes including each combination of vehicle characteristics. For example, repair codes 00600-00699 may correspond to one type of vehicle, while repair codes 00700-00799 may correspond to another type of vehicle. The vehicle type may be determined using the VDI/VIN data for the damaged vehicle as described above with reference to FIG. 1. Furthermore, in some embodiments, repair codes may also be used in salvaging and/or scrapping treatments. For example, the repair code 19986 may be used for salvaging hoods of a particular type of vehicle in good condition. The associated cost estimate may be a price estimate of the market value of the vehicle part assuming it is sold to a treatment facility or any other auto body shop. The salvage repair codes may have an inverse relationship with the other repair codes. For example, for the salvage repair codes, vehicle parts in better condition may have higher associated price estimates, whereas for the other repair codes, the cost estimates become higher when there is more work that needs to be done to repair the vehicle part. Further, the price estimate may be based on the scarcity/demand for the vehicle part. For example, vehicle parts from an antique or classic car may be in high demand because the car is no longer manufactured. The price estimates for salvage repair codes may be aggregated to determine the total price that an insurance provider can recover by salvaging vehicle parts.
  • FIG. 4 depicts an example damaged vehicle 400 including repair codes for various vehicle parts. Continuing with the vehicle treatment example from FIG. 3, the damaged vehicle 400 may be associated with repair codes 00600-00699, which may be assigned to estimate the cost of repairing the vehicle. Moreover, in some embodiments, the repair codes may be provided to a treatment facility for treating the damaged vehicle so the treatment facility knows what needs to be done to repair the vehicle without having to perform an inspection or assessment. The repair codes also may be provided to ensure that the treatment facility does not miss a portion of the repair.
  • In any event, crash information for the damaged vehicle 400 may be compared to collision data including historical loss information of similar type vehicles damaged in past collisions to determine which vehicle parts are damaged, and the estimated extent of the damage to the vehicle parts including the type of repair necessary (e.g., whether the vehicle part needs to be repaired and/or replaced) as described above in FIG. 3. A repair code from the set of repair codes may then be assigned to each damaged vehicle part in the list based on the vehicle characteristics for the damaged vehicle.
  • In the example damaged vehicle 400, the two doors 402 and 404 are assigned the repair code 00679 “Replace Door” with an associated cost estimate of $500 for each door. The front, right fender 406 is assigned repair code 00676 “Refinish Fender” with an associated cost estimate of $200, the hood 408 is assigned repair code 00675 “Refinish Hood” with an associated cost estimate of $300, and the roof 410 is assigned repair code 00610 “Replace Roof” with an associated cost estimate of $700. Further, the trunk lid 412 is assigned repair code 00692 “Repair Trunk Lid” with an associated cost estimate of $350, and the rear quarter panel 414 is assigned repair code 00682 “Replace Quarter Panel” with an associated cost estimate of $400. Additionally, the grille 416 is assigned repair code 00678 “Replace Grille” with an associated cost estimate of $250, and the bumper 418 is assigned repair code 00690 “Repair Bumper” with an associated cost estimate of $100. Combining the cost estimates for each of the repair codes corresponding to the damaged vehicle parts, the total cost for repairing the vehicle may be estimated as $3300. This estimate may be used to pay the vehicle owner on the insurance claim, and/or to provide a treatment facility with an expectation of the cost and treatment of repair for the damaged vehicle.
  • Referring again to FIG. 2, upon determination of the estimated treatment complexity level, system personnel and/or the processing center 102 may identify and select a vehicle treatment facility 112 capable of performing the recommended vehicle treatment, for example, repair, salvage, or scrap (block 208). System personnel and/or the processing center 102 may compare the calculated treatment complexity level to prospective treatment facilities capable of providing the necessary vehicle treatment. The selection of a vehicle treatment facility from among the one or more capable treatment facilities may be based on one or more dynamic criterion, such as a pricing structure, treatment facility capability, replacement vehicle part availability, treatment facility location, treatment facility quality rating and/or certification, treatment facility availability, current and/or prior business relationship with the treatment facility, etc., and combinations thereof. One or more of these dynamic criteria may also be weighted and/or prioritized by system personnel and/or the processing center 102 when determining a treatment facility for treatment of the vehicle. For example, a low complexity vehicle treatment generally may not require a high or specialized skill level and the proximity and/or convenience of a vehicle treatment facility nearer the vehicle owner or the crash site may be considered to be more appropriate. Thus, for a low complexity treatment, the location criterion of the vehicle treatment facility may be weighted and/or prioritized over some of the other criteria. For medium or high complexity vehicle treatments, the skill level and/or performance record of the treatment facility may be considered and thus weighted and/or prioritized over some or all of the other criteria for determining a treatment facility.
  • In some instances where the damage to the vehicle is too extensive or costly to be repaired and is determined to be a total loss, the damaged vehicle may be salvaged and immediately sold or put up for auction or scrapped and shredded for its scrap metal. Scrapping the vehicle may be appropriated for low dollar, high curb-weight vehicles where the value of the damaged vehicle is perceived to be in the scrap metal. In other instances, the damaged vehicle may be dismantled to salvage any value associated with the damaged vehicle. For example, if the damaged vehicle includes undamaged vehicle parts, the vehicle may be dismantled and the undamaged vehicle parts may be harvested and stored in a storage facility for later use and/or sale. The determination to sell or dismantle the damaged vehicle may include consideration of the treatment complexity level, the make, model, and year of the vehicle, and the market demand and/or desirability of particular harvested vehicle parts, e.g., at-risk vehicle parts for vehicles that are no longer in production. Additionally, a higher monetized recovery of the damaged vehicle may be attained if the damaged vehicle is partially repaired and/or dismantled to a varying extent, and then sold. For example, higher value and late model vehicles and/or vehicle parts may be prepared for sale. Such vehicles and vehicle parts, as well as rare or hard to find vehicles and vehicle parts may be privately or publicly sold or auctioned through a salvage treatment facility partnering with an entity using or administrating the treatment system and/or process described herein. Any unwanted vehicle parts that remain after dismantling may be shredded or scrapped.
  • Upon selection of an appropriate vehicle treatment facility, system personnel and/or the processing center 102 may transmit a communication including information related to the treatment of the damaged vehicle (block 210). The communication may be sent in the form of wired and/or wireless transmission, e.g., SMS text, e-mail, phone call, facsimile, etc. to the identified treatment facility. The communication may also be transmitted to the vehicle owner and/or other one or more other entities authorized by the vehicle owner, such as a vehicle repair facility, a vehicle scrap facility, emergency personnel, an insurance agent, etc. In one example embodiment, system personnel and/or the processing center 102 may contact the identified vehicle treatment facility 112 or a vehicle transporter 114 to facilitate transportation of the damaged vehicle from the crash site to the selected treatment facility, e.g., a service repair center, a scrapping or salvaging facility. For irreparably damaged vehicles (e.g., total loss), the damaged vehicle may be sent to an identified scrapping or salvaging facility to be dismantled where undamaged vehicle parts may be salvaged and stored at a warehouse 116 for reuse and resale before the remaining parts of the damaged vehicle are scrapped.
  • In addition to estimating the extent of vehicle damage, collision data may be used to detect risks of insurance fraud. FIG. 5 depicts a flow diagram 500 of an example embodiment for detecting risks of insurance fraud based on collision data, which may be accomplished by system personnel and/or the processing center 102. The collision data may include injury data for injured drivers and/or passengers in past collisions. For example, the collision data may include information on the percentage of drivers and/or passengers who were injured driving Toyota Priuses which experienced heavy damage to the hood and front frame rails during past collisions. More specifically, the collision data may include information on the type of injuries suffered by those drivers and/or passengers, i.e., neck injuries, severe head trauma, etc., as well as the percentage of drivers and/or passengers who suffered each type of injury.
  • In particular, system personnel and/or the processing center 102 may utilize crash characteristics provided by an individual present at the crash site, such as the driver and/or occupant of the damaged vehicle or an emergency responder or crash characteristics automatically attained by telematics devices operatively coupled to the vehicle (block 502). For example, descriptions and images of the damaged vehicle, vehicle acceleration, velocity, position of vehicle parts within the vehicle, and/or direction of the vehicle may be provided. Some crash information may be attained by an accelerometer and an array of sensors including spatial sensors at the time of the crash and then transmitted via a wireless communication module to system personnel and/or the processing center 102.
  • System personnel and/or the processing center 102 may also receive an injury claim from the policy holder for the vehicle, or another person injured in the crash (block 504). For example, the injury claim may be for a driver and/or passenger in the damaged vehicle at the time of the crash or a driver and/or passenger in another vehicle that is also damaged as a result of the crash. The injury claim may include the type of injury, the severity of the injury, medical expenses, other complications as a result of the injury, etc.
  • System personnel and/or the processing center 102 may then analyze the crash information. In one example embodiment, system personnel and/or the processing center 102 may compare various combinations of crash characteristics to collision data (block 506). The collision data may include historical loss information of similar type vehicles damaged in past collisions. The collision data may also include injury data for injured drivers and/or passengers in past collisions. The injury data may be for drivers and/or passengers of the damaged vehicle as well as for drivers and/or passengers of other vehicles involved in the crash. In this manner, the system personnel and/or the processing center 102 may determine injury data for a subset of the collision data for similar type vehicles and having similar crash characteristics and/or a similar extent of damage. For example, if the damaged vehicle is a Ford F-150 with a dented rear quarter panel requiring moderate repairs, injury data may be generated for all Ford F-150s with dented rear quarter panels requiring moderate repair from past collisions. In some embodiments, injury data may be generated for all Ford F-150s with dented rear quarter panels requiring moderate repair and having any other type(s) of damage as well. However, in other embodiments, injury data may be generated specifically for Ford F-150s having only dented rear quarter panels requiring moderate repair from past collisions.
  • An example injury data table 470 for F-150s having the above described damage is illustrated in FIG. 6. As mentioned above, the injury data may be stored with the collision data 106 which may be stored in the system 100 and/or operatively coupled to the processing center 102. The example injury data table 600 includes an entry for the total number of people injured, 25 (reference 602), in crashes involving a Ford F-150 where the damaged vehicle has a dented rear quarter panel requiring moderate repair. The data table 600 also includes entries for the total number of people who were not injured, 100, and the percentage of people who were injured, 20 percent. Moreover, the data table 600 also includes entries for the number of people as well as the percentage of people with neck injuries 604, back injuries 606, and head injuries 608 as a result of the crashes. Some people injured in the crashes may have suffered multiple injuries (e.g., back and head, head and neck, etc.).
  • In some embodiments, the injury data table 600 may also include the number of people who suffered injuries of varying severity. For example, out of the 25 people injured in the data table 600, 10 people may have suffered severe injuries, 10 people may have suffered moderate injuries, 2 people may have suffered minor injuries, etc. Moreover, the data table 600 may also include the locations of the people who suffered injuries in the vehicle (e.g., the driver's seat, the front passenger seat, the back left seat, etc.), as well as the number of people who suffered injuries in other vehicles (e.g., 15 percent of the people were injured in Ford F-150s, while 85 percent were injured in other vehicles as a result of colliding with Ford F-150s). Additionally, the injury data table 600 may include any other suitable injury data for past collisions involving Ford F-150s having dented rear quarter panels requiring moderate repairs. While the injury data table 600 is specific to injury data for Ford F-150s having dented rear quarter panels requiring moderate repairs, there may be several other injury data tables for Ford F-150s having one or more other damaged vehicle parts with varying extents of damage. There may also be several other injury data tables for other vehicle makes and/or models. Moreover, the injury data table 600 may be specific to those injured in Ford F-150s, and there may be a separate injury data table and/or injury data for those injured by Ford F-150s.
  • The example injury data table 600 of FIG. 6, or any other suitable injury data, may be compared with the claimed injury for detecting a risk of fraud. Turning back to FIG. 5, the injury claim may be compared to injury data for similar type vehicles and having similar crash characteristics and/or similar extent of damage as the damaged vehicle (block 508). For example, if the injury claim is a claim for a severe back injury from the driver of a Ford F-150 that is determined to have a dented rear quarter panel requiring moderate repairs, the injury claim may be compared to the injury data table 600 of FIG. 6 to determine whether the injury claim matches with the injury data (block 510).
  • To determine whether the injury claim matches the injury data, the processing center 102 may compare the percentage of people injured in the injury data to a predetermined threshold likelihood, i.e., 20 percent. If the percentage of people injured in the injury data exceeds the predetermined threshold likelihood, a suspicious loss indicator may not be generated (block 516). On the other hand, if the percentage of people injured in the injury data is less than the predetermined threshold likelihood, a suspicious loss indicator may be generated (block 512) and transmitted to an insurance agent, a claims center, etc. (block 514).
  • In some embodiments, the total percentage of people injured for similar type vehicles and having similar crash characteristics and/or similar extent of damage as the damaged vehicle, may not be the only criteria for determining whether the injury claim matches with the injury data. Other criteria may include the percentage of people having the same type of injury (e.g., back, neck, head, etc.), the same injury severity (e.g., minor injuries, moderate injuries, severe injuries), the same location within the vehicle (e.g., driver's seat, passenger front seat, back right seat, etc.), the same vehicle (e.g., in the Ford F-150 or collided with the Ford F-150), etc. Each of these criteria may be compared to a same and/or different threshold likelihoods to determine whether the injury claim matches the injury data. The injury data may be compared to one or more of the different threshold likelihoods to determine whether the injury claim matches the injury data. For example, the processing center 102 may determine for the injury claim to match the injury data, at least 20 percent of the people must have been injured, at least 10 percent must have suffered the same type of injury, at least 5 percent must have suffered the same or a worse injury severity, etc.
  • As mentioned above, if the injury claim does not match the injury data, a suspicious loss indicator may be generated. The suspicious loss indicator may be represented by the percentage or number of people claiming the same or similar injuries from similar past collisions. The suspicious loss indicator may also be a phrase such as, “high risk,” “medium risk,” “low risk,” etc., a symbol, a color, or any other suitable indicator.
  • In some embodiments, a risk of fraud may also be detected by comparing the cost of repair from a treatment facility to a cost estimate for the repair, for example, as determined by the repair codes. If the cost of repair from the treatment facility exceeds the cost estimate by a substantial amount, the cost of repair may be flagged as a risk of fraud and a suspicious loss indicator may be generated and transmitted to an insurance agent, a claims center, etc. That is, based on the extent of vehicle damage estimated by the comparison of the crash information to the collision data, the system may detect a risk of fraud by a policy holder or another person involved in the crash.
  • FIG. 7 illustrates a block diagram of an example treatment system 900 capable of being incorporated into the treatment system 100 shown in FIG. 1 and supporting the processes described herein for treating a vehicle damaged in a crash. The high-level architecture of the vehicle treatment system 900 includes both hardware and software applications, as well as various data communications channels for communicating data between the various hardware and software components. The vehicle treatment system 900 may be divided into front-end components 902 and back-end components 904. The front-end components 902 include one or more computing devices, such as a mobile computing device 910 and/or an on-board computing device 914. Either computing device 910, 914 may be permanently or removably attached to a vehicle 908 and may interface with various sensors coupled to the vehicle 908 (e.g., a speedometer, an accelerometer, a compass, a global position unit (GPS), spatial sensor disposed throughout the vehicle, etc.) and/or may interface with various external output devices in the vehicle 908, such as one or more tactile alert systems, one or more speakers, one or more displays devices, etc.
  • Each of the mobile computing device 910 and the on-board computing device 914 is capable of performing all of the functions of the computing device described herein or may supplement the functions performed by the other computing device. The mobile computing device 910 and on-board computing device 914 may communicate with one another directly over a wired or wireless link 916. In addition, the mobile computing device 910 and the on-board computing device 914 may communicate with a network 930 over wired or wireless links 912, 918, respectively. The network 930 may be a proprietary network, a secure public internet, a virtual private network, or some other type of network, such as dedicated access lines, plain ordinary telephone lines, satellite links, etc., and combinations thereof. Where the network 930 comprises the internet, data communications may take place over the network 930 via an internet communication protocol.
  • The treatment system 900 may also include a notification alert system 920 (e.g., automatic collision notification (ACN), advanced automatic collision or crash notification (AACN), event data recorder (EDR)), that may record and/or transmit information associated with treating the vehicle 908 after being involved in a crash. The front-end components 902 and the back-end components 904 communicate via the communication network 930. The back-end components 904 include a computing device such as a server 940 device or system. The server device 940 may include one or more processors 962 adapted, configured, and/or operatively coupled to and/or within an analyzer to execute various software applications and/or modules of the vehicle treatment system 900, in addition to other software routines. The server device 940 may further include a database 946 adapted to store the various software applications, modules, and/or routines as well as data related to the operation of the vehicle treatment system 900. The data may include, for example, information collected by the mobile computing device 910 and/or the on-board computing device 914 pertaining to the vehicle treatment system 900 and uploaded to the server device 940, such as sensor inputs, analyses corresponding to the methods discussed above, and images. Other kinds of information that may be stored in the database may include historical vehicle collision data compiled from crash data involving vehicles categorized in the same or similar type of vehicle as the vehicle 908 and contact information relating to vehicle service repair and/or salvage treatment facilities, part suppliers, vehicle transporters, vehicle owner, insurance personnel, etc. The computing devices 910, 914 and/or server device 940 may access or store data and/or software applications in the database 946 when executing various functions and tasks associated with the operation of the vehicle treatment system 900.
  • Although the vehicle treatment system 900 is shown to include one server device 940, one mobile computing device 910, and one on-board computing device 914, it should be understood that additional server devices 940, mobile computing devices 910, and on-board computing devices 914 may be utilized. For example, the system 900 may include several server devices 940 and numerous mobile computing devices 910, all of which may be interconnected via the network 930. As discussed above, the mobile computing device 910 may perform the various functions described herein in conjunction with the on-board computing device 914 or alone Likewise, the on-board computing device 914 may perform the various functions described herein in conjunction with the mobile computing device 910 or alone. In either instance, the mobile computing device 910 or on-board computing device may not need to be present. Furthermore, the processing performed by the one or more server devices 940 may be distributed among a plurality of server devices 940 configured in an arrangement known as “cloud computing.” This arrangement may provide several advantages, such as, for example, enabling near real-time uploads and downloads of information as well as periodic uploads and downloads of information. This arrangement may provide for a thin-client embodiment of the mobile computing device 910 and/or on-board computing device 914 described herein as well as a primary backup of some or all of the data gathered by the mobile computing device 910 and/or on-board computing device 914. All of the information involved with the treatment system 100, for example, crash information, collision data, VDI/VIN data, images, historical loss information, damage evaluation tools, damaged vehicle parts list, inventory of vehicle parts stored at the storage facility, vehicle transporters, treatment centers, customer contact information, insurance agent/entity contact information, etc. may be displayed in a variety of formats at the server device 940, wherein system personnel and/or the processing center 102 is provided access to such information for treating the damaged vehicle.
  • The server device 940 may have a controller 955 that is operatively connected to the database 946 via a link 956. The controller 955 may also be operatively connected to the network 930 via a communication link 935. It should be noted that, while not shown, additional databases may be linked to the controller 955 in a known manner. The controller 955 may include a program memory 960, a processor 962 (e.g., a microprocessor or a microcontroller), a random-access memory (RAM) 964, input/output (I/O) circuitry 966, and a user interface module 963 all of which may be interconnected via an address/data bus 965. The user interface module 963 facilitates human-to-machine interaction and may include a display screen, keyboard, mouse device, microphone, speaker, etc. Although the I/O circuitry 966 is shown as a single block, the I/O circuitry 966 may include a number of different types of I/O circuits. The program memory 960 may be configured to store computer-readable instructions that when executed by the processor 962 cause the server device 940 to implement a server application 942 and/or a web server 943. The instructions for the server application 942 may cause the server device 940 to implement the methods described herein. While shown as a single block in FIG. 7, it will be appreciated that the server application 942 may include a number of different programs, modules, routines, sub-routines, etc., that may separately or collectively cause the server device 940 to implement the server application 942. It should also be appreciated that although only one processor 962 is shown, the controller 955 may include multiple processors and/or microprocessors. Similarly, the memory of the controller 955 may include multiple RAMs 964 and multiple program memories 960. The RAM(s) 964 and program memories 960 may be implemented as semiconductor memories, magnetically readable memories, and/or optically readable memories, for example. Further, while the instructions for the server application 942 and web server 943 are shown being stored in the program memory 960, the instructions may additionally or alternatively be stored in the database 946 and/or RAM 964.
  • Alternatively, the vehicle treatment system 900 may include only the front-end components 902. For example, a mobile computing device 910 and/or on-board computing device 914 may perform any and/or all of the processing associated with compiling or gathering crash information, determining a treatment complexity level based on the crash information, determining a treatment for the vehicle based on the a treatment complexity level; and transmitting information associated with the treatment of the vehicle.
  • Referring now to FIG. 8, the mobile computing device 910 may include a user interface module 1002, a positioning module 1006 such as a global positioning system (GPS) module, a communication module 1020 which may include one or more wireless radios, a forward image capture module 1018, a rearward image capture module 1022, an accelerometer array 1024, and a controller 1004. Similarly, the on-board computing device 914 may include a user interface module 1002, a GPS module 1006, a communication module 1020 which may include one or more wireless radios, a forward image capture module 1018, a rearward image capture module 1022, an accelerometer array 1024, and a controller 1004.
  • The mobile computing device 910 and on-board computing device 914 may be integrated into a single device that can perform the functions of both devices. It will be appreciated that functions performed by either the mobile computing device 910 or the on-board computing device 914 may also be performed by the on-board computing device 914 in cooperation with the mobile computing device 910. The mobile computing device 910 may be a general-use mobile personal computer, cellular phone, smartphone, tablet computer, wearable computer (e.g., a watch, glasses, etc.), or a device dedicated to facilitating treatment of a damaged vehicle. The on-board computing device 914 may be a general-use on-board computer capable of performing the functions relating to vehicle operation or dedicated to facilitate treatment of a damaged vehicle. The on-board computing device 914 may be installed by the manufacturer of the vehicle 908 or as an aftermarket modification to the vehicle. Further, the mobile computing device 910 and/or on-board computing device 914 may be a thin-client device that outsources some or most processing to the server device 940.
  • Similar to the controller 955, the controller 1004 includes a program memory 1008, a microprocessor (MP) 1010, a random-access memory (RAM) 1012, and input/output (I/O) circuitry 1016, all of which are interconnected via an address/data bus 1014. Although the I/O circuitry 1016 is depicted in FIG. 10 as a single block, the I/O circuitry 1016 may include a number of different types of I/O circuits. The program memory 1008 includes an operating system 1026, a data storage device 1028, a plurality of software applications 1030, and a plurality of software routines 1034. The operating system 1026 may include one of a plurality of mobile platforms such as the iOS®, Android™, Palm® webOS, Windows® Mobile/Phone, BlackBerry® OS, or Symbian® OS mobile technology platforms, developed by Apple Inc., Google Inc., Palm Inc. (now Hewlett-Packard Company), Microsoft Corporation, Research in Motion (RIM), and Nokia, respectively. The data storage 1028 may include application data for the plurality of applications 1030, routine data for the plurality of routines 1034, and other data necessary to interact with the server 940 through the network 930. In particular, the data storage device 1028 may include vehicle collision data associated with a vehicle type that includes the vehicle 908. The vehicle type may include the make, model, and year of the vehicle. The vehicle collision data may include one or more compilations of recorded measurements of damaged vehicle parts and components and the corresponding acceleration and derived vectors, e.g., velocity and direction, of such characteristics attributed for the damage. In some embodiments, the controller 1004 may also include, or otherwise be operatively coupled for communication with other data storage mechanisms (e.g., one or more hard disk drives, optical storage drives, solid state storage devices, etc.) that may reside within the mobile computing device 910 and/or on-board computer 914 or operatively coupled to the network 930 and/or server device 940.
  • The GPS module 1006 may use “Assisted GPS” (A-GPS), satellite GPS, or any other suitable global positioning protocol or system that locates vehicle 908 via the position of the mobile computing device 910 and/or on-board computing device 914. For example, A-GPS utilizes terrestrial cell phone towers or Wi-Fi hotspots (e.g., wireless router points) to more accurately and more quickly determine the location of the vehicle 908 via the mobile computing device 910 and/or on-board computing device 914 while satellite GPS is generally more useful in more remote regions that lack cell towers or Wi-Fi hotspots. The GPS module 1006 may also facilitate the determination of the velocity and direction of the vehicle 908, via the coupling of the mobile computing device 910 and/or on-board computing device 914 to the vehicle.
  • The accelerometer array 1024 is one example of a telematics device or module that may incorporate one or more accelerometers positioned to determine the acceleration and direction of movements of the mobile computing device 910 and/or on-board computing device 914, which effectively correlate to the acceleration and direction of movements of the vehicle 908. In some embodiments, the accelerometer array 1024 may include an X-axis accelerometer 1024 x, a Y-axis accelerometer 1024 y, and a Z-axis accelerometer 1024 z to measure the acceleration and direction of movement in each respective dimension. It will be appreciated by those of ordinary skill in the art that a three dimensional vector describing a movement of the vehicle 908 via the mobile computing device 910 and/or on-board computing device 914 through three dimensional space can be established by combining the outputs of the X-axis, Y-axis, and Z-axis accelerometers 1024 x, y, z using known methods. Single- and multi-axis models of the accelerometer 1024 are capable of detecting magnitude and direction of acceleration as a vector quantity, and may be used to sense orientation and/or coordinate acceleration of the vehicle 908.
  • The forward and rearward image capture module 1018, 1022 may be built-in cameras within the mobile computing device 910 and/or on-board computing device 914 and/or may be peripheral cameras, such as webcams, cameras installed inside the vehicle 908, cameras installed outside the vehicle 908, etc., that are communicatively coupled with the mobile computing device 910 and/or on-board computing device 914. The image capture module 1018, 1022 may be oriented toward the front and rear of the vehicle 908. For example, the forward image capture module 1018 may be oriented toward the front of the vehicle 908 to observe the forward area of the vehicle 908 while the rearward image capture module 1022 may be oriented toward the rear of the vehicle 908 to observe the rearward area of the vehicle 908, or vice-versa. Some embodiments of the treatment system 900 may have both a forward image capture module 1018 and a rearward image capture module 1022, but other embodiments may have only one or no image capture module. Further, either or both of the forward image capture module 1018 and the rearward image capture module 1022 may include an infrared illuminator 1018 i, 1022 i, respectively, to facilitate low light and/or night image capturing. Such an infrared illuminator 1018 i, 1022 i may be automatically activated when light is insufficient for image capturing.
  • The GPS module 1006, the image capture modules 1018, 1022, and the accelerometer array 1024 may be referred to collectively as the “sensors” of the mobile computing device 910 and/or on-board computing device 914. Of course, it will be appreciated that additional GPS modules 1006, image capture modules 1018, 1022, and/or the accelerometer arrays 1024 may be operatively coupled to the mobile computing device 910 and/or on-board computing device 914. Further, the mobile computing device 910 and/or on-board computing device 914 may also include or be coupled to other sensors such as a thermometer, microphone, thermal image capture device, biomedical sensor, etc. The microphone may be incorporated with the user interface module 1002 and used to receive voice inputs from the vehicle operator while the thermometer and/or thermal image capture device may be used to determine fire or heat damage to the vehicle 908, and the biomedical sensor may capture biological characteristics of the vehicle operator.
  • The communication module 1020 may communicate with the server device 940 via any suitable wired or wireless communication protocol network, such as a wireless telephony network (e.g., GSM, CDMA, LTE, etc.), a Wi-Fi network (802.11 standards), a WiMAX network, a Bluetooth network, etc. The communication unit 1020 may also be capable of communicating using a near field communication standard (e.g., ISO/IEC 18092, standards provided by the NFC Forum, etc.).
  • The mobile computing device 910 and/or on-board computing device 914 may include the user-input interface 1002, which may include a “soft” keyboard that is presented on a display screen of the mobile computing device 910 and/or on-board computing device 914, an external hardware keyboard communicating via a wired or a wireless connection (e.g., a Bluetooth keyboard), and an external mouse, or any other suitable user-input device or component (see examples in FIGS. 9-12). As described earlier, the user-input module 1002 may also include a microphone (not shown) capable of receiving voice input from a vehicle operator as well as a display screen.
  • With reference to the controllers 955, 1004, it should be appreciated that although FIG. 8 depicts only one microprocessor 1010, the controller 1004 may include multiple microprocessors 1010. The memory of the controller 1004 may also include multiple RAMs 1012 and multiple program memories 1008. The controller 1004 may implement the RAM 1012 and the program memories 1008 as semiconductor memories, magnetically readable memories, and/or optically readable memories, for example. The one or more processors 1010 may be adapted, configured, and/or operatively coupled to and/or within an analyzer to execute any of the plurality of software applications 1030 and/or any of the plurality of software routines 1034 residing in the program memory 1008, in addition to other software applications. One of the plurality of applications 1030 may be a client application 1032 that may be implemented as a series of machine-readable instructions for performing the various functions associated with implementing the vehicle treatment system 900 as well as receiving information at, displaying information on, and transmitting information from the mobile device 910 and/or the on-board computing device 914. A client application 1032 may function to implement a system wherein the front-end components 902 communicate and cooperate with back-end components 904 as described above. The client application 1032 may include machine-readable instructions for implementing the user interface 1002 to allow a user to input commands to, and receive information from, the vehicle treatment system 900. One of the plurality of applications 1030 may be a native web browser 1036, such as Apple's Safari®, Google Android™ mobile web browser, Microsoft Internet Explorer® for Mobile, Opera Mobile™, that may be implemented as a series of machine-readable instructions for receiving, interpreting, and displaying web page information from the server device 940 or other back-end components 904 while also receiving inputs from the vehicle operator. Another application of the plurality of applications may include an embedded web browser 1042 that may be implemented as a series of machine-readable instructions for receiving, interpreting, and displaying web page information from the server device 940 or other back-end components 904 within the client application 1032.
  • Another of the plurality of client applications 1030 or routines 1034 may include an accelerometer routine 1038 that determines the acceleration and direction of movements of the mobile computing device 910 and/or on-board computing device 914, which correlate to the acceleration and direction of the vehicle 908. The accelerometer routine may process data from the accelerometer array 1024 to determine one or more vectors describing the motion of the vehicle 908 for use with the client application 1032. In some embodiments where the accelerometer array 1024 has X-axis, Y-axis, and Z-axis accelerometers 1024 x,y,z, the accelerometer routine 1038 may combine the data from each accelerometer 1024 x,y,z to establish the vectors describing the motion of the vehicle 908 as it moves through three dimensional space. In some embodiments, the accelerometer routine 1038 may use data pertaining to less than three axes.
  • Another routine in the plurality of applications 1030 or routines 1034 may include a vehicle velocity routine 1040 that coordinates with the GPS module 1006 to retrieve vehicle velocity and direction information for use with one or more of the plurality of applications, such as the client application 1032, or for use with other routines.
  • Yet another routine in the plurality of applications 1030 or routines 1034 may include an image capture routine that coordinates with the image capture modules 1018, 1022 to retrieve image data for use with one or more of the plurality of applications, such as the client application 1032, or for use with other routines.
  • Another routine in the plurality of application 1030 or routines 1034 may include a position determination routine that coordinates with the spatial sensors disposed throughout the vehicle to determine the positions of vehicle parts relative to the vehicle for use with one or more of the plurality of applications, such as the client application 1032, or for use with other routines.
  • The user or vehicle operator may also launch or instantiate any other suitable user interface application (e.g., the native web browser 1036, or any other one of the plurality of software applications 1030) to access the server device 940 to implement the vehicle treatment system 900. Additionally, the user or vehicle operator may launch the client application 1032 from the mobile computing device 910 and/or on-board computing device 914, to access the server device 940 to implement the vehicle treatment system 900.
  • After the vehicle operating information (e.g., acceleration, velocity, and direction) has been gathered or determined by the sensors or the mobile computing device 910 and/or on-board computing device 914, previously recorded collision data may be utilized to determine the extent of damage to the vehicle 908 involved in a crash. Once the extent of the damage has been assessed, a treatment for the vehicle 908 can be determined. For example, the mobile computing device 910 and/or on-board computing device 914 may determine that the damaged vehicle can be repaired or scrapped, and where the damaged vehicle may be taken for such treatment. The mobile computing device 910 and/or on-board computing device 914 may also transmit information associated with the treatment of the damaged vehicle. For example, the transmitted information may be sent to a treatment facility capable of performing the treatment and/or the information may be sent to a transportation facility and include a request to transport the damaged vehicle to the treatment facility. In some embodiments, the mobile computing device 910 and/or on-board computing device 914 may display on the user interface 1002 an initial loss report screen including, for example, a cost estimate for treating the vehicle, for example, based on one or more treatment codes. The initial loss report screen may also include other treatment information such as the crash information, the vehicle type including make and model, the treatment complexity level, an estimated duration for repairing the vehicle, a list of treatment facilities capable of treating the vehicle and their respective availabilities, etc. The display may also include options allowing the user to select a treatment facility from the list of treatment facilities, transfer funds into the user's personal account, schedule a rental car, etc.
  • In embodiments where the mobile computing device 910 and/or on-board computing device 914 is a thin-client device, the server device 940 may perform many of the processing functions remotely that may otherwise be performed by system personnel and/or the mobile computing device 910 and/or on-board computing device 914. In such embodiments, the server device 940 may include a number of software applications capable of receiving vehicle operating information gathered by the sensors and/or acquiring collision data to be used in determining the extent of damage to the vehicle 908 involved in the crash. For example, the mobile computing device 910 and/or on-board computing device 914 may gather information from its sensors as described herein, but instead of using the information locally, the mobile computing device 910 and/or on-board computing device 914 may send the information to the server device 940 for remote processing. The server device 940 may perform the analysis of the gathered crash information to determine the amount of damage to the vehicle 908 as described herein. The server device 940 may then determine whether the damaged vehicle can be repaired or scrapped, and where the damaged vehicle may be taken for such treatment. The server device 940 may also transmit information associated with the treatment of the damaged vehicle. For example, the information transmitted by the server device 940 may be sent to a treatment facility and/or a transport facility and include a request to transport the damaged vehicle to the treatment facility, or the server device 940 may transmit the information to the mobile computing device 910 and/or on-board computing device 914.
  • FIGS. 9-12 depict application pages that may be presented on the user interface 1002 of the mobile computing device 910 as part of the user interface used to implement the vehicle treatment system 900. While FIGS. 9-12 depict pages or screens of information capable of being presented on the display 1002 of the mobile computing device 910, it is to be understood that the application pages or screens of information could be displayed on the display 1002 of the on-board computing device 914 in addition to being displayed on the mobile device 910 or as an alternative. In addition, the application pages may also be displayed on the user interface 963 of the server device 940. The applications or pages may be generated by the mobile computing device 910/914 or sent to the mobile computing device 910/914 by the server 940 (e.g., as with a thin client). The user may launch the application from the mobile computing device 910/914 via any suitable manner, such as touch-selecting a start application icon 1104 on the display 1002 of the mobile computing device 910/914 or speaking a voice command into the microphone (not shown) of the mobile computing device 910/914. After the user launches the application 1032, the application 1032 may begin to run on the mobile computing device 910/914 as described above in connection to block 202, FIG. 2; or the mobile computing device 910 may communicate with the on-board computing device 914 and the client application 1032 may begin to run on the on-board computing device 914.
  • With reference now to FIG. 9, a monitor screen 1100 of the client application and/or routine may be displayed on the screen of the mobile computing device 910/914. The monitor screen 1100 may include a ‘Calibrate” tab 1102, a “Start” tab 1104, a “Settings” tab 1106, and a ‘Report’ tab 1108. When the user selects the “Calibrate” tab 1102, the client application may execute a calibration routine. A calibration screen (not shown) may be displayed on the screen of the mobile computing device 910/914 during execution of the calibration routine, wherein the progress of the calibration routine may be indicated by an illustration showing the approximate status of the calibration routine. If desired, a user may cancel the calibration and/or set the calibration routine to run in the “background,” so as not to appear on the screen 1100 of the mobile computing device 910/914.
  • When the user selects the “Start” tab 1104, the client application may begin to monitor and collect data about vehicle operation. The collected data may be stored as described above and/or additional data may be mathematically determined from the collected data about vehicle operation and also stored. Once started, a vehicle monitor screen 1200 shown in FIG. 10 may be displayed on the screen of the mobile computing device 910/914. The vehicle monitor screen 1200 may include a “Stop” tab 1202. If the “Stop” tab 1202 is selected by the user, the vehicle treatment system 900 will terminate vehicle operation monitoring. The vehicle treatment system 900 may also be stopped by a voice command of the user. Alternatively, the vehicle treatment system 900, e.g., gathering and analyzing of the vehicle operation and/or collision data, may be ceased by the mobile computing device 910/914 detecting that the engine of the vehicle 908 has stopped.
  • Referring now to FIG. 11, when the user selects the “Settings” tab 1106 shown in FIG. 11, a settings screen 1300 may be displayed on the screen of the mobile computing device 910/914. The settings screen 1300 may include a variety of information that the user or vehicle operator may enter into the vehicle treatment system 900 via a “soft” keyboard 1306 of the user interface of the mobile computing device 910/914. Such information may include the vehicle owner's name and/or contact information 1302. Additional information may include the make, model, and year of the vehicle type 1304 of the vehicle 908 that will be utilized with the treatment system 900. The settings screen 1300 may also include a variety of parameters that may be entered and adjusted by the user, such as the mode for turning on the treatment system 900, i.e., manual or automatic, etc. The parameters may be modified and saved by the user or vehicle operator via selection of a “Save” tab 1308 of the user interface on the mobile computing device 910/914.
  • Referring now to FIG. 12, when the user selects the “Report” tab 1108 shown in FIG. 12, a report screen 1400 may be displayed on the screen of the mobile device 910/914. The report screen 1400 may include a list of contacts 1402 to be notified in the event of a crash. The contact list 1402 may include the vehicle owner, insurance agent, etc., and may be entered and/or modified by the user via a “soft” keyboard 1406 of a user interface of the mobile computing device 910. The list of contacts 1402 may be saved by the user or vehicle operator via selection of the “Save” tab 1408 of the user interface of the mobile computing device 910.
  • Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.
  • Additionally, certain embodiments are described herein as including logic or a number of routines, subroutines, applications, or instructions. These may constitute either software (e.g., code embodied on a machine-readable medium) or hardware. In hardware, the routines, etc., are tangible units capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.
  • In various embodiments, a hardware module may be implemented mechanically or electronically. For example, a hardware module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC) to perform certain operations. A hardware module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.
  • Accordingly, the term “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where the hardware modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.
  • Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple of such hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).
  • The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.
  • Similarly, the methods or routines described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented hardware modules. The performance of certain operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.
  • The performance of certain operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the one or more processors or processor-implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the one or more processors or processor-implemented modules may be distributed across a number of geographic locations.
  • Unless specifically stated otherwise, discussions herein using words such as “processing,” “computing, ” “calculating, ” “determining, ” “presenting, ” “displaying,” or the like may refer to actions or processes of a machine (e.g., a computer) that manipulates or transforms data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, non-volatile memory, or a combination thereof), registers, or other machine components that receive, store, transmit, or display information.
  • As used herein any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
  • Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. For example, some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still cooperate or interact with each other. The embodiments are not limited in this context.
  • As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).
  • In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense of the description. This description, and the claims that follow, should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise.
  • Still further, for the purposes of illustration only, the figures depict preferred embodiments of a communication system and method for a mobile platform. One skilled in the art will readily recognize from the discussion above that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles described herein.
  • Of course, the applications and benefits of the systems, methods, and techniques described herein are not limited to only the above examples. Many other applications and benefits are possible by using the systems, methods, and techniques described herein.
  • It should also be understood that, unless a term is expressly defined in this patent using the sentence “As used herein, the term ‘_ _ _’ is hereby defined to mean . . . ” or a similar sentence, there is no intent to limit the meaning of that term, either expressly or by implication, beyond its plain or ordinary meaning, and such term should not be interpreted to be limited in scope based on any statement made in any section of this patent (other than the language of the claims). To the extent that any term recited in the claims at the end of this patent is referred to in this patent in a manner consistent with a single meaning, that is done for sake of clarity only so as to not confuse the reader, and it is not intended that such claim term be limited, by implication or otherwise, to that single meaning. Finally, unless a claim element is defined by reciting the word “means” and a function without the recital of any structure, it is not intended that the scope of any claim element be interpreted based on the application of 35 U.S.C. § 112, sixth paragraph.

Claims (20)

What is claimed:
1. A method for estimating vehicle repair costs, the method executed in part by one or more processors programmed to perform the method, the method comprising:
receiving, by the one or more processors via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle, the crash information collected by the one or more sensors, including an accelerometer;
analyzing, by the one or more processors, the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type;
determining, by the one or more processors, one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information;
determining, by the one or more processors, a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and
transmitting, by the one or more processors, an indication of the cost estimate.
2. The method of claim 1, wherein determining the cost estimate includes:
compiling a list of replacement vehicle parts based on the determined one or more damaged vehicle parts of the damaged vehicle; and
determining the cost estimate based on the list of replacement parts.
3. The method of claim 1, wherein determining the cost estimate includes:
determining a type of treatment for each damaged vehicle part of the determined one or more damaged vehicle parts.
4. The method of claim 1, wherein determining the cost estimate includes:
determining a treatment complexity level associated with treating the damaged vehicle based on the received crash information and the determined one or more damaged vehicle parts.
5. The method of claim 4, wherein the treatment complexity level includes a time duration for completing treatment of the damaged vehicle.
6. The method of claim 4, wherein the treatment complexity level indicates whether the damaged vehicle is a total loss.
7. The method of claim 4, further comprising:
determining, by the one or more processors, based on the treatment complexity level, a vehicle treatment facility capable of treating the damaged vehicle; and
transmitting, by the one or more processors, an indication of the vehicle treatment facility.
8. The method of claim 1, wherein receiving the crash information includes:
receiving, from a computing device coupled to the one or more sensors, the crash information, the computing device configured to transmit the crash information to the one or more processors automatically in response to the crash.
9. The method of claim 1, wherein:
receiving the crash information further includes receiving one or more images of the damaged vehicle; and
analyzing the crash information further includes comparing the one or more images included in the crash information to stored images included in the respective collision data of the vehicle type.
10. The method of claim 1, wherein receiving the crash information includes:
receiving an indication of whether emergency response equipment of the damaged vehicle was deployed due to the crash.
11. A system for estimating vehicle repair costs, the system comprising:
a computing device including one or more processors; and
one or more memory devices coupled to the one or more processors of the computing device, the one or more memory devices storing executable instructions that when executed by the one or more processors of the computing device cause the system to:
receive, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle, the crash information collected by the one or more sensors, including an accelerometer;
analyze the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type;
determine one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information;
determine a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and
transmit an indication of the cost estimate.
12. The system of claim 11, wherein, to determine the cost estimate, the executable instructions cause the system to:
compile a list of replacement vehicle parts based on the determined one or more damaged vehicle parts of the damaged vehicle; and
determine the cost estimate based on the list of replacement parts.
13. The system of claim 11, wherein, to determine the cost estimate, the executable instructions cause the system to:
determine a type of treatment for each damaged vehicle part of the determined one or more damaged vehicle parts.
14. The system of claim 11, wherein, to determine the cost estimate, the executable instructions cause the system to:
determine a treatment complexity level associated with treating the damaged vehicle based on the received crash information and the determined one or more damaged vehicle parts.
15. The system of claim 14, wherein the treatment complexity level includes a time duration for completing treatment of the damaged vehicle.
16. The system of claim 14, wherein the treatment complexity level indicates whether the damaged vehicle is a total loss.
17. The system of claim 14, wherein the executable instructions further cause the system to:
determine, based on the treatment complexity level, a vehicle treatment facility capable of treating the damaged vehicle; and
transmit an indication of the vehicle treatment facility.
18. The system of claim 11, wherein the computing device is a first computing device, and wherein, to receive the crash information, the executable instructions cause the system to:
receive, from a second computing device coupled to the one or more sensors, the crash information, the second computing device configured to transmit the crash information to the one or more processors automatically in response to the crash.
19. The system of claim 11, wherein the crash information includes one or more images of the damaged vehicle, and wherein, to analyze the crash information, the executable instructions further cause the system to:
analyze the crash information by comparing the one or more images included in the crash information to stored images included in the respective collision data of the vehicle type.
20. A tangible, computer-readable medium storing instructions that when executed by one or more processors of a computer system cause the computer system to:
receive, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle, the crash information collected by the one or more sensors, including an accelerometer;
analyze the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type;
determine one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information;
determine a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and
transmit an indication of the cost estimate.
US17/465,088 2014-07-11 2021-09-02 System, Method, and Computer-Readable Medium for Comparing Automatically Determined Crash Information to Historical Collision Data to Estimate Repair Costs Pending US20210398088A1 (en)

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US201462023711P 2014-07-11 2014-07-11
US14/732,331 US9799010B1 (en) 2014-07-11 2015-06-05 System, method, and computer-readable medium for facilitating delivery of replacement parts for a damaged vehicle
US15/720,790 US11138570B1 (en) 2014-07-11 2017-09-29 System, method, and computer-readable medium for comparing automatically determined crash information to historical collision data to detect fraud
US17/465,088 US20210398088A1 (en) 2014-07-11 2021-09-02 System, Method, and Computer-Readable Medium for Comparing Automatically Determined Crash Information to Historical Collision Data to Estimate Repair Costs

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US14/627,104 Active 2036-03-21 US9904928B1 (en) 2014-07-11 2015-02-20 Method and system for comparing automatically determined crash information to historical collision data to detect fraud
US14/627,170 Active 2035-08-07 US10013718B1 (en) 2014-07-11 2015-02-20 Method and system for automatically streamlining the vehicle claims process
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US15/138,387 Active 2036-01-04 US10332318B1 (en) 2014-07-11 2016-04-26 Method and system of using spatial sensors on vehicle frame to determine crash information
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US15/907,628 Active 2036-03-19 US11798320B2 (en) 2014-07-11 2018-02-28 System, method, and computer-readable medium for facilitating treatment of a vehicle damaged in a crash
US16/692,421 Active US11756126B1 (en) 2014-07-11 2019-11-22 Method and system for automatically streamlining the vehicle claims process
US17/465,088 Pending US20210398088A1 (en) 2014-07-11 2021-09-02 System, Method, and Computer-Readable Medium for Comparing Automatically Determined Crash Information to Historical Collision Data to Estimate Repair Costs
US18/331,360 Pending US20230316417A1 (en) 2014-07-11 2023-06-08 Method and System for Automatically Streamlining the Vehicle Claims Process
US18/370,700 Pending US20240013588A1 (en) 2014-07-11 2023-09-20 System, method, and computer-readable medium for facilitating treatment of a vehicle damaged in a crash

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US14/627,104 Active 2036-03-21 US9904928B1 (en) 2014-07-11 2015-02-20 Method and system for comparing automatically determined crash information to historical collision data to detect fraud
US14/627,170 Active 2035-08-07 US10013718B1 (en) 2014-07-11 2015-02-20 Method and system for automatically streamlining the vehicle claims process
US14/627,139 Active US9208526B1 (en) 2014-07-11 2015-02-20 Method and system for categorizing vehicle treatment facilities into treatment complexity levels
US14/627,145 Active 2035-05-26 US9646345B1 (en) 2014-07-11 2015-02-20 Method and system for displaying an initial loss report including repair information
US14/627,092 Active US9361735B1 (en) 2014-07-11 2015-02-20 Method and system of using spatial sensors on vehicle frame to determine crash information
US14/732,326 Active 2035-11-11 US9990677B1 (en) 2014-07-11 2015-06-05 System, method, and computer-readable medium for facilitating treatment of a vehicle damaged in a crash
US14/732,331 Expired - Fee Related US9799010B1 (en) 2014-07-11 2015-06-05 System, method, and computer-readable medium for facilitating delivery of replacement parts for a damaged vehicle
US14/946,111 Active US9495667B1 (en) 2014-07-11 2015-11-19 Method and system for categorizing vehicle treatment facilities into treatment complexity levels
US15/138,387 Active 2036-01-04 US10332318B1 (en) 2014-07-11 2016-04-26 Method and system of using spatial sensors on vehicle frame to determine crash information
US15/287,178 Active US9898784B1 (en) 2014-07-11 2016-10-06 Method and system for categorizing vehicle treatment facilities into treatment complexity levels
US15/477,201 Active 2036-01-06 US10460535B1 (en) 2014-07-11 2017-04-03 Method and system for displaying an initial loss report including repair information
US15/720,790 Active 2036-04-22 US11138570B1 (en) 2014-07-11 2017-09-29 System, method, and computer-readable medium for comparing automatically determined crash information to historical collision data to detect fraud
US15/865,485 Active US10074140B1 (en) 2014-07-11 2018-01-09 Method and system for categorizing vehicle treatment facilities into treatment complexity levels
US15/865,478 Active 2036-04-18 US10997607B1 (en) 2014-07-11 2018-01-09 Method and system for comparing automatically determined crash information to historical collision data to detect fraud
US15/907,628 Active 2036-03-19 US11798320B2 (en) 2014-07-11 2018-02-28 System, method, and computer-readable medium for facilitating treatment of a vehicle damaged in a crash
US16/692,421 Active US11756126B1 (en) 2014-07-11 2019-11-22 Method and system for automatically streamlining the vehicle claims process

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Families Citing this family (72)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10963966B1 (en) * 2013-09-27 2021-03-30 Allstate Insurance Company Electronic exchange of insurance information
US11669090B2 (en) 2014-05-20 2023-06-06 State Farm Mutual Automobile Insurance Company Autonomous vehicle operation feature monitoring and evaluation of effectiveness
US10089693B1 (en) 2014-05-20 2018-10-02 State Farm Mutual Automobile Insurance Company Fully autonomous vehicle insurance pricing
US9972054B1 (en) 2014-05-20 2018-05-15 State Farm Mutual Automobile Insurance Company Accident fault determination for autonomous vehicles
US10373259B1 (en) 2014-05-20 2019-08-06 State Farm Mutual Automobile Insurance Company Fully autonomous vehicle insurance pricing
US10599155B1 (en) 2014-05-20 2020-03-24 State Farm Mutual Automobile Insurance Company Autonomous vehicle operation feature monitoring and evaluation of effectiveness
US9904928B1 (en) 2014-07-11 2018-02-27 State Farm Mutual Automobile Insurance Company Method and system for comparing automatically determined crash information to historical collision data to detect fraud
US10540723B1 (en) 2014-07-21 2020-01-21 State Farm Mutual Automobile Insurance Company Methods of providing insurance savings based upon telematics and usage-based insurance
US10336321B1 (en) 2014-11-13 2019-07-02 State Farm Mutual Automobile Insurance Company Autonomous vehicle control assessment and selection
US20160239921A1 (en) * 2015-02-16 2016-08-18 Autoclaims Direct Inc. Apparatus and methods for estimating an extent of property damage
USD775142S1 (en) * 2015-02-20 2016-12-27 State Farm Mutual Automobile Insurance Company Display screen with a graphical user interface for automobile repair estimation and recommendation
US10083551B1 (en) 2015-04-13 2018-09-25 Allstate Insurance Company Automatic crash detection
US9767625B1 (en) 2015-04-13 2017-09-19 Allstate Insurance Company Automatic crash detection
US9870649B1 (en) 2015-08-28 2018-01-16 State Farm Mutual Automobile Insurance Company Shared vehicle usage, monitoring and feedback
US10460534B1 (en) * 2015-10-26 2019-10-29 Allstate Insurance Company Vehicle-to-vehicle accident detection
US11242051B1 (en) 2016-01-22 2022-02-08 State Farm Mutual Automobile Insurance Company Autonomous vehicle action communications
US10134278B1 (en) 2016-01-22 2018-11-20 State Farm Mutual Automobile Insurance Company Autonomous vehicle application
US10493936B1 (en) 2016-01-22 2019-12-03 State Farm Mutual Automobile Insurance Company Detecting and responding to autonomous vehicle collisions
US11719545B2 (en) 2016-01-22 2023-08-08 Hyundai Motor Company Autonomous vehicle component damage and salvage assessment
US10324463B1 (en) 2016-01-22 2019-06-18 State Farm Mutual Automobile Insurance Company Autonomous vehicle operation adjustment based upon route
US11441916B1 (en) 2016-01-22 2022-09-13 State Farm Mutual Automobile Insurance Company Autonomous vehicle trip routing
US10395332B1 (en) 2016-01-22 2019-08-27 State Farm Mutual Automobile Insurance Company Coordinated autonomous vehicle automatic area scanning
US10354230B1 (en) * 2016-01-28 2019-07-16 Allstate Insurance Company Automatic determination of rental car term associated with a vehicle collision repair incident
US11093906B2 (en) 2016-03-09 2021-08-17 Autozone Parts, Inc. Systems and apparatuses facilitating a do-it-yourself experience-based repair solution
US10937104B1 (en) * 2016-05-11 2021-03-02 United Services Automobile Association (Usaa) Vehicle damage estimation
US20170337593A1 (en) * 2016-05-19 2017-11-23 Vincent S. Tong Method to recommend an auto shop to an automobile user
US11734653B2 (en) * 2016-07-12 2023-08-22 My Car Fix, LLC Systems and methods for automobile maintenance scheduling
US20180040039A1 (en) * 2016-08-08 2018-02-08 Audatex North America, Inc. Vehicle Component Partitioner
CA2976770A1 (en) * 2016-08-18 2018-02-18 Mitchell International, Inc. Methods for vehicle valuation utilizing automated integration of build sheet data and devices thereof
US10902525B2 (en) 2016-09-21 2021-01-26 Allstate Insurance Company Enhanced image capture and analysis of damaged tangible objects
WO2018057497A1 (en) * 2016-09-21 2018-03-29 Allstate Insurance Company Enhanced image capture and analysis of damaged tangible objects
US11361380B2 (en) 2016-09-21 2022-06-14 Allstate Insurance Company Enhanced image capture and analysis of damaged tangible objects
US10339647B2 (en) * 2016-10-06 2019-07-02 Toyota Motor Engineering & Manufacturing North America, Inc. Methods, systems, and media for qualitative and/or quantitative indentation detection
US10657707B1 (en) * 2017-01-09 2020-05-19 State Farm Mutual Automobile Insurance Company Photo deformation techniques for vehicle repair analysis
US10719501B1 (en) 2017-03-03 2020-07-21 State Farm Mutual Automobile Insurance Company Systems and methods for analyzing vehicle sensor data via a blockchain
US20210312405A1 (en) 2017-04-05 2021-10-07 State Farm Mutual Automobile Insurance Company Systems and methods for recall compliance via blockchain
CN107292395A (en) * 2017-06-26 2017-10-24 深圳市中车数联科技有限公司 Method for building up, device and the computer-readable storage medium of automotive electronics health account
US11087292B2 (en) * 2017-09-01 2021-08-10 Allstate Insurance Company Analyzing images and videos of damaged vehicles to determine damaged vehicle parts and vehicle asymmetries
US11416942B1 (en) 2017-09-06 2022-08-16 State Farm Mutual Automobile Insurance Company Using a distributed ledger to determine fault in subrogation
US10872381B1 (en) * 2017-09-06 2020-12-22 State Farm Mutual Automobile Insurance Company Evidence oracles
US11386498B1 (en) 2017-09-06 2022-07-12 State Farm Mutual Automobile Insurance Company Using historical data for subrogation on a distributed ledger
CN109583982A (en) * 2017-09-29 2019-04-05 车伯乐(北京)信息科技有限公司 A kind of processing method apparatus and system of information of vehicles
US10926727B2 (en) * 2017-10-18 2021-02-23 Qirfiraz Siddiqui Smart surface for detecting collision forces
CN108564681B (en) * 2018-04-17 2021-12-31 百度在线网络技术(北京)有限公司 Data processing method, data processing apparatus, computing device, program product, and storage medium
US10609541B1 (en) 2018-04-27 2020-03-31 Mbit Wireless, Inc. Method and apparatus for emergency alert in client devices
US10783589B2 (en) * 2018-11-03 2020-09-22 International Business Machines Corporation Armonk Detection of abnormal estimates
US20200184591A1 (en) * 2018-12-10 2020-06-11 Allstate Insurance Company System and Methods for Analyzing Roadside Assistance Service of Vehicles in Real Time
CN109697429A (en) * 2018-12-27 2019-04-30 睿驰达新能源汽车科技(北京)有限公司 A kind of method and device of determining vehicle damage
CN109816121A (en) * 2019-01-21 2019-05-28 北汽福田汽车股份有限公司 The monitoring system and method for vehicle maintenance service
US11710097B2 (en) 2019-03-22 2023-07-25 BlueOwl, LLC Systems and methods for obtaining incident information to reduce fraud
FR3097565B1 (en) * 2019-06-19 2022-08-12 Staubli Sa Ets Textile machine, weaving loom comprising such a textile machine and associated methods
WO2020263482A1 (en) * 2019-06-24 2020-12-30 Carbon, Inc. Preemptive apparatus failure detection in additive manufacturing
KR102391007B1 (en) 2019-07-15 2022-04-27 현대자동차주식회사 System and method for providing service of chancing vehicle parts
US11514482B2 (en) 2019-09-06 2022-11-29 Honda Motor Co., Ltd. Systems and methods for estimating a remaining value
US11188853B2 (en) * 2019-09-30 2021-11-30 The Travelers Indemnity Company Systems and methods for artificial intelligence (AI) damage triage and dynamic resource allocation, routing, and scheduling
US20210125211A1 (en) * 2019-10-23 2021-04-29 Carma Automotive Inc. Parameter-based reconditioning index for estimation of vehicle reconditioning cost
US11388351B1 (en) 2019-10-29 2022-07-12 BlueOwl, LLC Systems and methods for gate-based vehicle image capture
US11417208B1 (en) 2019-10-29 2022-08-16 BlueOwl, LLC Systems and methods for fraud prevention based on video analytics
DE102019220070A1 (en) * 2019-12-18 2021-06-24 Robert Bosch Gmbh Method for user interaction of an electrical device and / or an electrical device accessory and system for carrying out the method
CN115668250A (en) 2020-01-03 2023-01-31 易识有限公司 Method for determining a painting request for a damaged vehicle
CN111538872B (en) * 2020-07-09 2020-11-03 太平金融科技服务(上海)有限公司 Visualization method and device of service node information, computer equipment and medium
US11488117B2 (en) * 2020-08-27 2022-11-01 Mitchell International, Inc. Systems and methods for managing associations between damaged parts and non-reusable parts in a collision repair estimate
US11556903B2 (en) * 2020-08-30 2023-01-17 VB Solutions, LLC Method and application for automating automobile service provider tracking and communications
US20230237584A1 (en) * 2020-10-29 2023-07-27 BlueOwl, LLC Systems and methods for evaluating vehicle insurance claims
CN112435044A (en) * 2020-12-03 2021-03-02 广州极飞科技有限公司 After-sale document processing method and device, electronic equipment, system and storage medium
US20220198842A1 (en) * 2020-12-18 2022-06-23 Motional Ad Llc Predictive analytics for vehicle health
JP7110463B1 (en) * 2021-09-22 2022-08-01 株式会社タウ Information processing device, information processing method, and program
WO2023086589A1 (en) * 2021-11-11 2023-05-19 ServiceTitan, Inc. Systems and methods for dynamic pricing
WO2023187851A1 (en) * 2022-03-28 2023-10-05 日産自動車株式会社 Vehicle data analysis method and device
CN115208927B (en) * 2022-08-24 2022-12-06 成都秦川物联网科技股份有限公司 Industrial Internet of things for correcting, regulating and controlling defective products and control method thereof
DE102022125059A1 (en) * 2022-09-28 2024-03-28 Frank Hoffmann Procedure for processing and monitoring motor vehicle damage cases
CN115808911B (en) * 2023-02-02 2023-04-28 成都秦川物联网科技股份有限公司 Industrial Internet of things regulation and control method and system for defective products generated in production line

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7359821B1 (en) * 2002-06-11 2008-04-15 Injury Sciences Llc Methods and apparatus for using black box data to analyze vehicular accidents
US20080306996A1 (en) * 2007-06-05 2008-12-11 Mcclellan Scott System and Method for the Collection, Correlation and Use of Vehicle Collision Data
US20100138242A1 (en) * 2008-07-14 2010-06-03 Cross Country Automotive Services Electronic Vehicle Repair Management (eVRM)
US20120076437A1 (en) * 2001-11-08 2012-03-29 Digiclaim, Inc. System and method for automated claims processing
US8799034B1 (en) * 2013-03-08 2014-08-05 Allstate University Company Automated accident detection, fault attribution, and claims processing
US20140278572A1 (en) * 2013-03-15 2014-09-18 State Farm Mutual Automobile Insurance Company System and method for routing a vehicle damaged in a crash
US20150317739A1 (en) * 2014-04-30 2015-11-05 Hartford Fire Insurance Company System and method for vehicle repair cost estimate verification

Family Cites Families (200)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7415126B2 (en) 1992-05-05 2008-08-19 Automotive Technologies International Inc. Occupant sensing system
US4853850A (en) * 1985-09-10 1989-08-01 Krass Jr James E Vehicle computer diagnostic interface apparatus
JPH01220075A (en) 1988-02-29 1989-09-01 Nippon Taisanbin Kogyo Kk Displaying part reading method
US5504674A (en) * 1991-02-19 1996-04-02 Ccc Information Services, Inc. Insurance claims estimate, text, and graphics network and method
US6557889B2 (en) 1991-07-09 2003-05-06 Automotive Technologies International Inc. Crush velocity sensing vehicle crash sensor
US7284769B2 (en) * 1995-06-07 2007-10-23 Automotive Technologies International, Inc. Method and apparatus for sensing a vehicle crash
US6823244B2 (en) 1995-06-07 2004-11-23 Automotive Technologies International, Inc. Vehicle part control system including electronic sensors
US7481453B2 (en) 1991-07-09 2009-01-27 Automotive Technologies International, Inc. Inflator system
US5317503A (en) 1992-03-27 1994-05-31 Isao Inoue Apparatus for calculating a repair cost of a damaged car
US5943295A (en) 1997-02-06 1999-08-24 Automotive Technologies International Inc. Method for identifying the presence and orientation of an object in a vehicle
US7477758B2 (en) * 1992-05-05 2009-01-13 Automotive Technologies International, Inc. System and method for detecting objects in vehicular compartments
US6746078B2 (en) 1997-12-17 2004-06-08 Automotive Technologies International, Inc. System and method for moving a headrest based on anticipatory sensing
US9102220B2 (en) 1992-05-05 2015-08-11 American Vehicular Sciences Llc Vehicular crash notification system
US7983817B2 (en) 1995-06-07 2011-07-19 Automotive Technologies Internatinoal, Inc. Method and arrangement for obtaining information about vehicle occupants
WO1994022693A1 (en) * 1993-03-31 1994-10-13 Automotive Technologies International, Inc. Vehicle occupant position and velocity sensor
US5950169A (en) 1993-05-19 1999-09-07 Ccc Information Services, Inc. System and method for managing insurance claim processing
US5742666A (en) 1994-10-05 1998-04-21 Tele Digital Development, Inc. Emergency mobile telephone
US8799461B2 (en) * 1994-11-29 2014-08-05 Apple Inc. System for collecting, analyzing, and transmitting information relevant to transportation networks
US7832762B2 (en) 1995-06-07 2010-11-16 Automotive Technologies International, Inc. Vehicular bus including crash sensor or occupant protection system control module
US7786864B1 (en) 2000-09-08 2010-08-31 Automotive Technologies International, Inc. Vehicular RFID and sensor assemblies
US7527288B2 (en) 1995-06-07 2009-05-05 Automotive Technologies International, Inc. Vehicle with crash sensor coupled to data bus
EP0847003A3 (en) 1996-12-03 2004-01-02 Texas Instruments Inc. An audio memo system and method of operation thereof
DE69828808D1 (en) 1997-10-23 2005-03-03 Key Safety Systems Inc IMPACT SENSOR SYSTEM
WO1999040529A1 (en) * 1998-02-04 1999-08-12 Biodynamic Research Corp. System and method for acquiring and quantifying vehicular damage information
US6470303B2 (en) * 1998-02-04 2002-10-22 Injury Sciences Llc System and method for acquiring and quantifying vehicular damage information
JP2000067247A (en) 1998-06-08 2000-03-03 Toshiba Corp Image recognizing device
EP0982673A3 (en) * 1998-08-21 2002-10-02 Tsubasa System Co. Ltd. Vehicle repair cost estimating system
US6076028A (en) 1998-09-29 2000-06-13 Veridian Engineering, Inc. Method and apparatus for automatic vehicle event detection, characterization and reporting
US6851504B2 (en) 1998-12-14 2005-02-08 Trw Vehicle Safety Systems Inc. Method and apparatus for anticipating a vehicle crash event
US6859009B2 (en) 1999-07-02 2005-02-22 Richard Jablin Urban transportation system
US7514917B2 (en) 2003-09-19 2009-04-07 Automotive Systems Laboratory, Inc. Magnetic crash sensor
US8180585B2 (en) * 1999-08-26 2012-05-15 Tk Holdings, Inc. Magnetic crash sensor
US7161350B2 (en) 1999-09-07 2007-01-09 Jentek Sensors, Inc. Method for material property monitoring with perforated, surface mounted sensors
US6644688B1 (en) 1999-11-04 2003-11-11 Automotive Systems Labortory, Inc. Crash sensing system
EP1252480A1 (en) 1999-11-12 2002-10-30 Go Sensors, L.L.C. Image metrology methods and apparatus
US6225891B1 (en) * 2000-01-07 2001-05-01 Hittite Microwave Corp. Wide-angle, static and positional anticipatory object detection system
US6609050B2 (en) 2000-01-20 2003-08-19 Daimlerchrysler Corporation Vehicle warranty and repair computer-networked system
US6810383B1 (en) 2000-01-21 2004-10-26 Xactware, Inc. Automated task management and evaluation
US6375377B1 (en) 2000-03-22 2002-04-23 Robert Lowery Automotive paint restoration tool and method
CA2378342A1 (en) 2000-04-20 2001-11-01 General Electric Company Method and system for graphically identifying replacement parts for generally complex equipment
US20020007289A1 (en) 2000-07-11 2002-01-17 Malin Mark Elliott Method and apparatus for processing automobile repair data and statistics
US20020103622A1 (en) 2000-07-17 2002-08-01 Burge John R. Decision-aid system based on wirelessly-transmitted vehicle crash sensor information
US6882986B1 (en) 2000-08-07 2005-04-19 Tymetrix Method for automatic processing of invoices
US6694234B2 (en) 2000-10-06 2004-02-17 Gmac Insurance Company Customer service automation systems and methods
US6431593B1 (en) 2000-10-13 2002-08-13 Trw Inc. Vehicle crash determination arrangement and method, utilizing center of gravity, for an occupant protection system
US7860764B1 (en) 2000-10-19 2010-12-28 Blaise Alexander Method and system for leasing motor vehicles to credit challenged consumers
US20020087488A1 (en) 2000-11-07 2002-07-04 Ron Fordahl System and method of tracking vehicle information and bill consolidation
US20020077867A1 (en) * 2000-12-14 2002-06-20 Gittins Richard Simon Automated claims fulfillment system
US6754564B2 (en) * 2001-01-30 2004-06-22 Archie L. Newport Integrated vehicle information system
US7635676B2 (en) 2001-02-21 2009-12-22 Alavita Pharmaccuticals, Inc. Modified annexin proteins and methods for their use in organ transplantation
US7080080B1 (en) 2001-04-05 2006-07-18 Miller Claims Consulting, Inc. Web-based siding material matching system
US6737584B2 (en) 2001-05-01 2004-05-18 Bridgeport Fittings, Inc. Electrical cable connector
JP2002326569A (en) * 2001-05-02 2002-11-12 Eac:Kk Damaged part recognition system and recognition method for damaged vehicle
US7324951B2 (en) 2001-06-05 2008-01-29 Renwick Glenn M Method of processing vehicle damage claims
US20030078798A1 (en) 2001-07-05 2003-04-24 Milwaukee Public Schools Computerized maintenance management system
US8204766B2 (en) 2001-08-15 2012-06-19 Meridian Enterprises Corporation Insurance claim payment card system
WO2003023557A2 (en) 2001-09-06 2003-03-20 Wtd Technologies, Inc. Accident evidence recording method
US7436937B2 (en) * 2001-09-26 2008-10-14 Clawson Jeffrey J Method and system for the police response dispatch protocol of an emergency dispatch system
US6918458B2 (en) 2001-10-12 2005-07-19 Autoliv Asp, Inc. Load management system and method for motor vehicle restraints
US20030200123A1 (en) * 2001-10-18 2003-10-23 Burge John R. Injury analysis system and method for insurance claims
US20030111525A1 (en) 2001-12-18 2003-06-19 Georgina Sweeney Method and system of determining status of automobile undergoing repair
US20030171959A1 (en) * 2002-02-06 2003-09-11 David Galloway Method and apparatus for generating an automobile insurance endorsement
US20030200151A1 (en) 2002-04-22 2003-10-23 John Ellenson System and method for facilitating the real-time pricing, sale and appraisal of used vehicles
US20040044549A1 (en) 2002-08-30 2004-03-04 Loop Kevin S. Method of determining potential for repair services in a geographic area
CA2490385C (en) 2002-10-28 2014-05-06 Marquage Antivol Sherlock, Inc. Method of preventing theft of vehicles using intensive marking
JP2004177191A (en) * 2002-11-26 2004-06-24 Fujitsu Ltd Method and device for judging damaged part
US9818136B1 (en) 2003-02-05 2017-11-14 Steven M. Hoffberg System and method for determining contingent relevance
DE10305861A1 (en) * 2003-02-13 2004-08-26 Adam Opel Ag Motor vehicle device for spatial measurement of a scene inside or outside the vehicle, combines a LIDAR system with an image sensor system to obtain optimum 3D spatial image data
AU2004225177A1 (en) 2003-04-02 2004-10-14 F-Technologies Ltd. Methods and systems for the management of insurance claims and property
CA2424708A1 (en) 2003-04-08 2004-10-08 Lee A. Danisch A method and apparatus for sensing impact between a vehicle and an object
US20050072234A1 (en) 2003-05-20 2005-04-07 Weidong Zhu System and method for detecting structural damage
US7496228B2 (en) 2003-06-13 2009-02-24 Landwehr Val R Method and system for detecting and classifying objects in images, such as insects and other arthropods
US8744961B2 (en) 2003-07-25 2014-06-03 Stoneeagle Services, Inc. Method of providing secure payment and transaction reconciliation
US8121887B2 (en) 2003-08-29 2012-02-21 Ppg Industries Ohio, Inc. Method and system for reporting on the quality of a repair process
US7664612B2 (en) 2003-09-19 2010-02-16 T K Holdings, Inc. Signal processing system and method
WO2005038604A2 (en) 2003-10-15 2005-04-28 Engelman Paul R Wireless automobile valuation information service
US20050108063A1 (en) * 2003-11-05 2005-05-19 Madill Robert P.Jr. Systems and methods for assessing the potential for fraud in business transactions
US7596512B1 (en) 2003-11-26 2009-09-29 Carfax, Inc. System and method for determining vehicle price adjustment values
US8595079B1 (en) 2003-11-26 2013-11-26 Carfax, Inc. System and method for determining vehicle price values
ES2666890T3 (en) 2004-03-03 2018-05-08 Metis Design Corporation Damage detection device
US20050267774A1 (en) 2004-06-01 2005-12-01 David Merritt Method and apparatus for obtaining and using vehicle sales price data in performing vehicle valuations
US7636676B1 (en) * 2004-08-05 2009-12-22 Wolery Alan K System and method for allowing a vehicle owner to obtain a vehicle repair estimate
US7181968B2 (en) * 2004-08-25 2007-02-27 Autoliv Asp, Inc. Configurable accelerometer assembly
US20060064367A1 (en) 2004-09-23 2006-03-23 Block Robert J Systems and methods for insuring intellectual property holding companies
US20060074790A1 (en) 2004-10-06 2006-04-06 Jeremy Anspach Method for marketing leased assets
US20060155614A1 (en) 2004-10-07 2006-07-13 Vpro Inc. Method and Apparatus for Selling Consumer Products Using High Resolution Images
US7912740B2 (en) 2004-11-01 2011-03-22 Claims Services Group, Inc. System and method for processing work products for vehicles via the world wide web
US7359781B2 (en) * 2004-12-14 2008-04-15 Trw Automotive U.S. Llc Method and apparatus for determining symmetric and asymmetric crash events with improved misuse margins
US7716076B1 (en) 2004-12-27 2010-05-11 Ocean Tomo, Llc System and method for financing an insurance transaction
US20060210192A1 (en) 2005-03-17 2006-09-21 Symagery Microsystems Inc. Automatic perspective distortion detection and correction for document imaging
EP1696381A1 (en) 2005-02-25 2006-08-30 Copart, Inc. Systems and Methods for Determining Vehicle Salvage Value
US20090326989A1 (en) 2005-03-23 2009-12-31 Schmitt Brett A Interactive information management system and method
US20060265235A1 (en) 2005-05-12 2006-11-23 The Crawford Group, Inc. Method and system for managing vehicle leases
US20060287895A1 (en) 2005-06-21 2006-12-21 National Autos Llc Dba Autoland Of Wilmington Negative equity insurance
US8655776B2 (en) 2005-07-19 2014-02-18 The Prudential Insurance Company Of America Benefits contract providing a bundle of benefits
US20070067075A1 (en) 2005-09-16 2007-03-22 Mcmillan Michael W Quick automotive cosmetic repair
US8874477B2 (en) 2005-10-04 2014-10-28 Steven Mark Hoffberg Multifactorial optimization system and method
US20070156552A1 (en) 2005-10-11 2007-07-05 Manganiello Anthony M Method and system for debt management
WO2007109541A2 (en) 2006-03-16 2007-09-27 Brubaker Curtis M System and method for obtaining revenue through the display of hyper-relevant advertising on moving objects
US20070136106A1 (en) * 2005-12-09 2007-06-14 Gary Hart Method and system of managing and administering automotive glass repairs and replacements
US20070136163A1 (en) 2005-12-14 2007-06-14 Capital One Financial Corporation Systems and methods for providing financing information based on a vehicle identification number
CA2575171A1 (en) 2006-01-20 2007-07-20 Ppg Industries Ohio, Inc. Method of improving throughput performance of an automotive repair shop
US8117090B2 (en) 2006-01-30 2012-02-14 Craig Duncan Romero Motor vehicle remarketing service
US20070179860A1 (en) 2006-01-30 2007-08-02 Romero Craig D Motor vehicle remarketing service
US20090216565A1 (en) 2006-02-27 2009-08-27 Opyd Iii Leon P Method for protecting equity in purchased goods
GB0605188D0 (en) 2006-03-16 2006-04-26 Pte Ltd Lifetime damage monitor
US8762234B2 (en) 2006-03-22 2014-06-24 Mark Haydne David Jenkins Duty and tax avoidance device and system
US20080235116A1 (en) 2007-03-22 2008-09-25 Jensen John B Process and method for systematically exchanging product between manufacturer of product or representative of product and purchaser for an established term
DE102006018723A1 (en) 2006-04-20 2007-10-25 Hans Edmund Hochrein Vehicle impact warning
US8230362B2 (en) 2006-05-31 2012-07-24 Manheim Investments, Inc. Computer-assisted and/or enabled systems, methods, techniques, services and user interfaces for conducting motor vehicle and other inspections
US9189960B2 (en) 2006-05-31 2015-11-17 Manheim Investments, Inc. Computer-based technology for aiding the repair of motor vehicles
US20070294052A1 (en) 2006-06-16 2007-12-20 Sikorsky Aircraft Corporation Supplier teardown & analysis reporting system
US20080046261A1 (en) 2006-08-17 2008-02-21 Scene Genesis, Inc. Direct repair program management systems and methods thereof
US20080052216A1 (en) 2006-08-22 2008-02-28 Johnson Arthur W System and method for determining used vehicle market values for use in hedging risks associated with used vehicle futures contracts
US10366352B2 (en) * 2006-10-06 2019-07-30 The Crawford Group, Inc. Method and system for communicating vehicle repair information to a business-to-business rental vehicle reservation management computer system
DE102006048725A1 (en) 2006-10-16 2008-04-17 Robert Bosch Gmbh Method for determining the axis of rotation of a vehicle wheel
US20080243556A1 (en) 2006-10-31 2008-10-02 Dennis Hogan Historical insurance transaction system and method
US20080133425A1 (en) 2006-12-05 2008-06-05 Bernard Grush Method for road use credit tracking and exchange
US8160906B2 (en) 2006-12-12 2012-04-17 The Crawford Group, Inc. System and method for improved rental vehicle reservation management
US8694328B1 (en) 2006-12-14 2014-04-08 Joseph Gormley Vehicle customization and personalization activities
US20080243530A1 (en) 2007-03-27 2008-10-02 James Stubler Method for auditing product damage claims utilizing shock sensor technology
US20080255887A1 (en) * 2007-04-10 2008-10-16 Autoonline Gmbh Informationssysteme Method and system for processing an insurance claim for a damaged vehicle
US8346578B1 (en) 2007-06-13 2013-01-01 United Services Automobile Association Systems and methods for using unmanned aerial vehicles
US8131417B2 (en) 2007-08-29 2012-03-06 Driverside, Inc Automotive diagnostic and estimate system and method
US20130297353A1 (en) 2008-01-18 2013-11-07 Mitek Systems Systems and methods for filing insurance claims using mobile imaging
US20090300065A1 (en) 2008-05-30 2009-12-03 Birchall James T Computer system and methods for improving identification of subrogation opportunities
WO2009152380A1 (en) * 2008-06-11 2009-12-17 Repairpal, Inc. Method and system for determining services pricing
US20100023352A1 (en) 2008-07-23 2010-01-28 The Crawford Group, Inc. System and Method for Improved Information Sharing by Repair Facilities for Managing Rental Vehicle Reservations
US8311856B1 (en) * 2008-10-13 2012-11-13 Allstate Insurance Company Communication of insurance claim data
US7931037B1 (en) 2009-02-25 2011-04-26 Ryan Jason S Covering system
US20100274631A1 (en) 2009-04-24 2010-10-28 Veretech Holdings, Inc. System and Method For Generating Vehicle Sales Leads
US20100274571A1 (en) 2009-04-24 2010-10-28 Veretech Holdings Inc. System and method for generating vehicle service leads and vehicle sales leads
US20100293181A1 (en) 2009-05-18 2010-11-18 Autoonline Gmbh Informationssysteme VALUEpilot - METHOD AND APPARATUS FOR ESTIMATING A VALUE OF A VEHICLE
US20100299190A1 (en) 2009-05-20 2010-11-25 Tim Pratt Automotive market place system
US8346577B2 (en) 2009-05-29 2013-01-01 Hyperquest, Inc. Automation of auditing claims
CA2763369A1 (en) 2009-06-01 2010-12-09 Bio-Rad Laboratories, Inc. Calibration of imaging device for biological/chemical samples
US20120188105A1 (en) 2009-09-30 2012-07-26 Rakan Khaled Y. ALKHALAF System for monitoring the position of vehicle components
WO2011047125A1 (en) 2009-10-14 2011-04-21 Summit Mobile Solutions, Inc. Method and system for damage reporting and repair
US20110173086A1 (en) 2009-12-14 2011-07-14 Berkowitz Ed Systems and Methods for Dynamic Pricing and Auction Adjudication During Online Auctions
US20110313936A1 (en) 2010-06-18 2011-12-22 Joseph Michael Sieger Method and apparatus for estimating value of a damaged vehicle
US20120005070A1 (en) 2010-07-01 2012-01-05 Veretech Holdings, Inc. Sales lead generation system using a credit score survey
US20120005108A1 (en) 2010-07-02 2012-01-05 Buybook Technology, Inc. Method and system for providing a guaranteed offer price for a vehicle
EP2405236B1 (en) 2010-07-07 2012-10-31 Leica Geosystems AG Geodesic measuring device with automatic extremely precise targeting functionality
US20120136743A1 (en) 2010-11-30 2012-05-31 Zonar Systems, Inc. System and method for obtaining competitive pricing for vehicle services
US20120136802A1 (en) 2010-11-30 2012-05-31 Zonar Systems, Inc. System and method for vehicle maintenance including remote diagnosis and reverse auction for identified repairs
US20120265563A1 (en) 2010-10-09 2012-10-18 Kwasny David J System and method for automobile collision repair
US20120113141A1 (en) 2010-11-09 2012-05-10 Cbs Interactive Inc. Techniques to visualize products using augmented reality
EP3255613B1 (en) 2010-12-15 2022-09-21 Auto Telematics Ltd Method and system for logging vehicle behaviour
US9158869B2 (en) 2011-01-11 2015-10-13 Accurence, Inc. Method and system for property damage analysis
US8928495B2 (en) 2011-01-24 2015-01-06 Lexisnexis Risk Solutions Inc. Systems and methods for telematics monitoring and communications
US8781912B2 (en) 2011-03-15 2014-07-15 Opera Solutions, Llc Computer-based method and computer program product for setting floor prices for items sold at auction
WO2012126004A2 (en) 2011-03-17 2012-09-20 Winning Bid, Inc. Systems, devices and methods facilitating structured settlement transactions
US20150324924A1 (en) 2011-04-28 2015-11-12 Allstate Insurance Company Streamlined Claims Processing
US20130124366A1 (en) 2011-05-09 2013-05-16 Paul Breed Apparatus and methods for efficient generation and delivery of item information
US20130006809A1 (en) 2011-07-01 2013-01-03 Buybook Technologies, Inc. Method and system for providing a certified swap price for a vehicle
JP6031736B2 (en) 2011-07-21 2016-11-24 富士ゼロックス株式会社 Object identification system and program
US10453013B1 (en) 2011-08-31 2019-10-22 Inherent Leverage, Inc. Method for processing vehicle repair
US20130262255A1 (en) 2011-09-27 2013-10-03 Strategyn Equity Partners, Inc. Facilitating transactions with granular job outcomes
US20130218761A1 (en) 2011-10-10 2013-08-22 David J. Kwasny System, method,computer product and website for automobile collision repair
US8719134B1 (en) 2012-02-01 2014-05-06 Allstate Insurance Company Insurance rating plan
US9349234B2 (en) 2012-03-14 2016-05-24 Autoconnect Holdings Llc Vehicle to vehicle social and business communications
US20130325541A1 (en) 2012-05-08 2013-12-05 John A. Capriotti System and method for managing and providing vehicle maintenance
US20140012748A1 (en) 2012-07-05 2014-01-09 General Electric Company Repair system and method
US8718385B2 (en) 2012-07-23 2014-05-06 State Farm Mutual Automobile Insurance Company Siding identification systems and methods
WO2015002630A2 (en) * 2012-07-24 2015-01-08 Deloitte Development Llc Fraud detection methods and systems
US8712893B1 (en) * 2012-08-16 2014-04-29 Allstate Insurance Company Enhanced claims damage estimation using aggregate display
US8510196B1 (en) * 2012-08-16 2013-08-13 Allstate Insurance Company Feedback loop in mobile damage assessment and claims processing
US20140081675A1 (en) 2012-09-19 2014-03-20 The Travelers Indemnity Company Systems, methods, and apparatus for optimizing claim appraisals
US9665912B1 (en) 2012-09-20 2017-05-30 Allstate Insurance Company Insurance claim capitation and predictive payment modeling
US9002719B2 (en) * 2012-10-08 2015-04-07 State Farm Mutual Automobile Insurance Company Device and method for building claim assessment
US20140114691A1 (en) 2012-10-23 2014-04-24 InnovaPad, LP Methods and Systems for the Integrated Collection of Data for Use in Incident Reports and Insurance Claims and to Related Methods of Performing Emergency Responder Cost Recovery
US9661304B2 (en) 2012-10-31 2017-05-23 Ricoh Company, Ltd. Pre-calculation of sine waves for pixel values
US20150006023A1 (en) * 2012-11-16 2015-01-01 Scope Technologies Holdings Ltd System and method for determination of vheicle accident information
US9076034B2 (en) 2012-12-07 2015-07-07 Analog Devices, Inc. Object localization using vertical symmetry
US10304137B1 (en) 2012-12-27 2019-05-28 Allstate Insurance Company Automated damage assessment and claims processing
US8923650B2 (en) 2013-01-07 2014-12-30 Wexenergy Innovations Llc System and method of measuring distances related to an object
US20140222820A1 (en) 2013-02-05 2014-08-07 Gary Alan Mott Apparatus, system, and method for vehicular characteristic monitoring and cataloging
US9132911B2 (en) 2013-02-28 2015-09-15 Sikorsky Aircraft Corporation Damage adaptive control
US9019092B1 (en) 2013-03-08 2015-04-28 Allstate Insurance Company Determining whether a vehicle is parked for automated accident detection, fault attribution, and claims processing
US20140278576A1 (en) 2013-03-14 2014-09-18 Invenger Technologies Inc. Method, apparatus, and computer program product for obtaining coverage request authorizations
US9508200B1 (en) 2013-03-15 2016-11-29 State Farm Mutual Automobile Insurance Company System and method for using a specialty vehicle data identifier to facilitate treatment of a vehicle damaged in a crash
US8731977B1 (en) 2013-03-15 2014-05-20 Red Mountain Technologies, LLC System and method for analyzing and using vehicle historical data
US9858622B1 (en) 2013-03-15 2018-01-02 State Farm Mutual Automobile Insurance Company System and method for facilitating vehicle insurance services
US20140316825A1 (en) 2013-04-18 2014-10-23 Audatex North America, Inc. Image based damage recognition and repair cost estimation
US20140358641A1 (en) 2013-06-03 2014-12-04 Robert Friedman Method and system for vehicle leases permitting multiple vehicle exchanges
JP5786901B2 (en) 2013-06-20 2015-09-30 株式会社デンソー Accident reporting system
US20150025917A1 (en) 2013-07-15 2015-01-22 Advanced Insurance Products & Services, Inc. System and method for determining an underwriting risk, risk score, or price of insurance using cognitive information
US20150039522A1 (en) 2013-07-31 2015-02-05 State Farm Mutual Automobile Insurance Company System and method of providing a vehicle repair status
US9940675B2 (en) 2013-10-11 2018-04-10 Hartford Fire Insurance Company System and method for rules driven insurance claim processing
US20150120484A1 (en) 2013-10-25 2015-04-30 Alteso Llc System and method for marketing and selling auction items
US20150149218A1 (en) 2013-11-22 2015-05-28 Gulfstream Telematics LLC Detection System for Analyzing Crash Events and Methods of the Same
US9877176B2 (en) 2013-12-18 2018-01-23 Medlegal Network, Inc. Methods and systems of managing accident communications over a network
US20150178849A1 (en) 2013-12-19 2015-06-25 The Travelers Indemnity Company Systems and methods for consultative insurance quotations
US9113288B2 (en) * 2014-01-16 2015-08-18 General Motors Llc Controlling a short-range wireless connection between a vehicle telematics unit and an in-vehicle audio system
US9561432B2 (en) 2014-03-12 2017-02-07 Wargaming.Net Limited Touch control with dynamic zones
US8885916B1 (en) 2014-03-28 2014-11-11 State Farm Mutual Automobile Insurance Company System and method for automatically measuring the dimensions of and identifying the type of exterior siding
US10860955B2 (en) 2014-04-04 2020-12-08 Tower Rock Technologies, Llc Job loader
US9727921B2 (en) * 2014-06-09 2017-08-08 State Farm Mutual Automobile Insurance Company Systems and methods for processing damage to insured properties or structures
US9904928B1 (en) 2014-07-11 2018-02-27 State Farm Mutual Automobile Insurance Company Method and system for comparing automatically determined crash information to historical collision data to detect fraud
US9505365B1 (en) 2015-05-15 2016-11-29 Ford Global Technologies, Llc Wearable data management during an incident

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120076437A1 (en) * 2001-11-08 2012-03-29 Digiclaim, Inc. System and method for automated claims processing
US7359821B1 (en) * 2002-06-11 2008-04-15 Injury Sciences Llc Methods and apparatus for using black box data to analyze vehicular accidents
US20080306996A1 (en) * 2007-06-05 2008-12-11 Mcclellan Scott System and Method for the Collection, Correlation and Use of Vehicle Collision Data
US20100138242A1 (en) * 2008-07-14 2010-06-03 Cross Country Automotive Services Electronic Vehicle Repair Management (eVRM)
US8799034B1 (en) * 2013-03-08 2014-08-05 Allstate University Company Automated accident detection, fault attribution, and claims processing
US20140278572A1 (en) * 2013-03-15 2014-09-18 State Farm Mutual Automobile Insurance Company System and method for routing a vehicle damaged in a crash
US20150317739A1 (en) * 2014-04-30 2015-11-05 Hartford Fire Insurance Company System and method for vehicle repair cost estimate verification

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