Classifications

• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
  • G08G1/207—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles with respect to certain areas, e.g. forbidden or allowed areas with possible alerting when inside or outside boundaries
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
  • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
  • G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
  • G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0125—Traffic data processing
  • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
  • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
  • G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/16—Anti-collision systems
  • G08G1/164—Centralised systems, e.g. external to vehicles
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/16—Anti-collision systems
  • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
  • G01S13/88—Radar or analogous systems specially adapted for specific applications
  • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
  • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
  • G01S2013/9316—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles combined with communication equipment with other vehicles or with base stations

Definitions

• This invention generally pertains to vehicle accident surveillance and methods to deal with vehicle accidents. Embodiments of the invention are also generally related to systems and methods to diagnose vehicle issues and related to communication among components of a distributed vehicle database.
• EP 0466499 A1 is referred to in this document.
• aspects of this invention are designed to provide as close to real-time surveillance of a vehicle accident as possible to both estimate the amount and extent of damage to the vehicle or vehicles and to determine bodily harm.
• appropriate emergency response vehicles can be deployed and the repair process can be initiated including relaying, to adjusters, damage estimates and surveillance information to determine causality.
• Specific aspects of embodiments of this invention include methods and system to detect accidents before they happen or while they happen; methods and systems to anticipate an accident based on measurements acquired of vehicle movements and driving conditions that are historically indicative of an accident.
• Sensors within a vehicle deployed from a vehicle for aerial surveillance; deployed from a fixed based station for aerial surveillance; long term flight aerial surveillance; and fixed sensors that monitor a transportation network may be deployed.
• An aim of this invention is both to navigate the uncertain regulatory landscape and also take advantage of the array of sensors; sensor delivery vehicles and methods; and statistical and machine learning analysis techniques for accident prediction and accident scene surveillance.
• Embodiments of the present system alleviates potential bandwidth deficiencies and needless transfer costs for a vehicle analytics database, storing all the information in a distributed fashion, and only relaying information to a processing unit when it is needed for analysis.
• an analysis unit selectively querying across a network or networks for only the pertinent data for a relative event or task and by also identifying what type of device and/vehicle the information is desired from, then massive data transfers can be avoided.
• Typical vehicle diagnostic systems and assisted or autonomous driving systems rely on crowdsourced information that was compiled from collecting data stored in on-board vehicle systems and from external feeds such as traffic and weather. All this information is compiled and sifted through in an effort to, for example, provide a prediction of some type of hazardous conditions or need of repair. Tremendous amounts of data need to be wirelessly transmitted, typically on mobile networks, where two-way communications are established between every vehicle or external feed and the central server or servers.
• Embodiments of this invention drastically reduce the bandwidth necessary to collect and utilize information.
• a central server/s broadcasts via radio transmission (for example FM sideband) a selective query which contains specific identifiers with respect to the type of vehicle or vehicle configuration (if necessary) and/or location and time requirements and a request for information, or a notification that information is available for client systems meeting the selection criteria. If a client system receives the transmission and the client system meets the selection criteria, then and only then will a two-way communication be established with a handshake initiated by the client/s (an individual vehicle or subsystem or service).
• the qualifying clients connect to the server/s and download the information.
• bandwidth will always be saved.
• the server/s does not have to be aware of every vehicle on the road. The vehicles simply have to be aware of the server/s.
• Embodiments of this invention comprise a distributed database and method of use, where the database comprises raw sensor and environmental data related to a vehicle and the driving conditions the vehicle was subjected to. All information is both spatially and temporally referenced. In addition the information is referenced based on the type of vehicle and how the vehicle is equipped/loaded and optionally by the driver of the vehicle.
• the database is distributed among one or more central servers and clients: satellite servers, individual vehicles, and hand-held units.
• Each server and clients houses a database of information that is pertinent to one of: one or more vehicles or to an individual driver who drives the one or more vehicles.
• a vehicle will store raw sensor data from sensors embedded in the vehicle and/or that reside in-vehicle and also information acquired from external feeds - for example traffic (in the vicinity of the vehicle or along a route the vehicle will travel) and weather information.
• a satellite server will contain, for example, information for vehicles and weather and the transportation network for a given geographic area.
• Another example is a server hosted by a repair facility that has information on the type and cost of repairs for vehicles they have worked on.
• FIG. 1 depicts and embodiment using aerial surveillance from a blimp.
• FIG. 2 Depicts an accident scene being tracked.
• FIG. 3 is a flowchart showing input into an Accident Prediction Module
• FIG. 4 is a prior art depiction of rocket propelled surveillance system.
• FIG. 5 is a prior art depiction of a small quad copter with mounted camera.
• FIG. 6 is a flowchart of events required to launch an aerial
• FIG. 7 is a depiction of an embodiment of a system that houses a distributed vehicle diagnostic database.
• FIG. 8 is a flow chart of an embodiment of a method of using a distributed vehicle diagnostic database.
• FIG. 9 is a flow chart of an embodiment of a method for follow up instructions after an event has occurred and been reported.
• FIG. 10 is a flow chart of an embodiment of how patterns and indicators are updated.
• Maintenance Report a document or report (either hardcopy or online) that results from analysis of information relating to a vehicle operation, that schedules maintenance and repairs that are required to keep a vehicle in peak operating condition.
• ln-vehicle Refers to anything that is part of the vehicle or within or attached to the vehicle.
• Sensors measurement devices which measure parameters that are directly or indirectly related to the amount and extent of maintenance and/or repair needed to keep a vehicle in peak operating condition. Sensors could be in-vehicle - either part of the vehicle or an after-market attachment to the vehicle such as a fleet management system or as part of a mobile device within the vehicle such as the sensors in a mobile phone - like accelerometers or gyroscopes. Sensors may also be outside the vehicle such as roadside traffic counters in the vicinity of the vehicle, weather stations, and satellite or airborne based sensor such as LIDAR.
• Transceiver A device capable of both receiving and sending information to another device whether it be wired or wireless. Examples are two-way radios, mobile phones, wired modems and the like.
• Transmitter A device capable of sending information over radio waves.
• Receiver A device capable of receiving information over radio waves.
• Location where an object is relative to a reference frame.
• the location of a vehicle is some embodiments is relative to the earth in terms of a coordinate system such as latitude and longitude (and perhaps elevation).
• Vehicle any object capable of moving material or people. This includes cars, trucks, boats, airplanes, construction equipment and the like.
• External Observations See the definition of sensors above for examples of observations that can come from outside the vehicle.
• Source for this information can also be from web services, for example weather data, or traffic information that is a feed coming in from a FM sideband via an FM receiver.
• Reference (for a database) an index or other attribute that can be used to select database records of interest by querying using the index or attribute.
• reference for accident information could be: location, time, time of day, time of week; make of vehicle, year of vehicle (or Vehicle Identification Number), weather conditions, location of impact (zone on the car), direction of impact, force of impact and the like.
• Normalized transforming data from a variety of sources into the same units, in the same frame of reference.
• Historical Maintenance Database a database or collection of linked databases containing information that is related to individual accident events where all information is cross referenced so that it can be used for statistical analysis of accidents and the cost of repair resulting from the accident.
• Cross-referenced With respect to a database, one entry can be queried as to its relationship to another if there is some type of relationship between the two. For example, a certain model of water pump produced by General Motors may have been used in a variety of car models over a variety of model years, so the part number for the water pump will be cross referenced to vehicle model number, year, engine type. Also note these parameters may not be sufficient information, because a part used may change mid-model year. For example, a wheel type my not be compatible halfway through a model year because the lug spacing was changed for safety reasons. In this case, the wheel would have to be referenced to the specific Vehicle Identification Number (VIN) which could be further cross referenced to a linked database containing more detailed information.
• VIN Vehicle Identification Number
• Confidence Interval One method of expressing the probability that an outcome will be observed to happen within a specific range for a given set of
• the probability that the water pump will have to be replaced for shortly after 100,000 miles of driving is 95 percent for a Ford Focus and 92 percent for a BMW 928i.
• Satellite Servers Part of the network that contains the distributed database where a portion of the database is held. Typically, the portion of the database will have information pertaining to a particular geographic area or a particular fleet of vehicles, or may contain only certain types of information, for example snow depths.
• these databases may contain accident information that identifies damage specific information, and cost of repair with is correlated with make, model, and model year of the vehicle/s involved. Once again this information is spatially and temporally indexed.
• weather related information may also be stored and indexed to location and time as well as correlated with accidents. This information can come from police reports, private insurance databases, and similar.
• Patterns Time series or frequency distribution of sequential sensor data of one or more sensors or feeds for a given time period and locale that can be used to identify Driving Events. Patterns are created by analyzing many datasets with known events happening.
• Patterns are updated by a central server in communication with a vehicle or satellite server system through the process of querying the vehicle fleet or satellite server network and where one of these remote entities has information that match the query, the remote entity will respond with relaying data for the event in question back to the main server. Definition of new patterns are further refined by soliciting data from like vehicles or circumstances, to be relayed to the central server where these data can then be used to refine the existing patterns that define an event. [0051] Patterns typically cannot be determined by human observation as they may be dependent on many variables that do not lend themselves to human observation. A human may be able to observe that the necessity of applying the brake while traveling around a curve is probably indicative of too much speed, however, combining observations of brakes, abs sensors, acceleration, weather feeds and more is beyond the ability of a human to assimilate.
• Patterns may be based on the output of 1 or more sensor and/or 1 or more observations.
• the pattern could be based on exceeding (or falling below) a threshold value, or exceeding (or falling below) an average value over time. Patterns may be analyzed in the frequency domain (after a fast Fourier transform is applied to time series data).
• Indicators Readings from one or more sensors for a given time period and locale that exceed or fall below a specified threshold value indicative or an Event, or Situation. An example of an indicator is exceeding the speed limit.
• Driving Events Something of interest that happens related to a vehicle, location, or time period which is identifiable by monitoring patterns or indicators. Events generally are categorized by something that is out of the ordinary. Examples of an event are a vehicle accident, a vehicle exceeding the speed limit, a vehicle being driven in an unsafe manner.
• An Ongoing Driving Event is a subset of an Event where the event occurs over a period of time. For example, an accident may be a momentary event, but may cause an Ongoing Event such as a slowing of traffic on the road where the accident occurs
• External Data Feeds Servers or services that available via a web interface or that are broadcast over radio frequency that provide information on conditions such as weather and traffic.
• Mutli-variate analysis A statistical technique to identify or maintain patterns. Examples are artificial neural networks and machine learning.
• Circumstances Background information related to individual events. For example, location, time, weather conditions, traffic, road condition are all
• Some objects of this invention are systems and methods to detect vehicle accidents and observe vehicle accident scenes.
• the tools used for this are sensors within a vehicle or vehicles including: video cameras; sensors that are part of the vehicle; and additional sensors that are part of a portable device within the vehicle.
• Other sensor systems include stationary sensors that are associated with the vehicle transportation network, for example, traffic counters, and speed cameras. Additional information may be provided by weather stations.
• Aerial sensors can be mounted, for example, in ROVS, autonomous drones, and manned aircraft. In addition, sensors can be outside the atmosphere mounted on satellites. Individual vehicles may be tracked by GPS or wireless transmitter signal strength triangulation to assess movements prior to an accident.
• Analysis consists of statistical analysis of sensor data from one or more system types and delivery systems where the analysis is performed by comparison of historical patterns indicative of an accident about to occur or an accident that has happened and further patterns used to assess damage and injury.
• Novel ROV / autonomous flying vehicles that are deployed from a vehicle are also part of this invention.
• Aerial surveillance which has an identified area to monitor vehicle movement and activities.
• the area could be part of a road network defined by geographic borders; it could be an intersection known to have a potential for many collisions.
• the area could change during different time periods or day of the week based on historical collision or accident rates.
• On-Vehicle Surveillance which consists of a sensor suite that is part of the vehicle and perhaps sensors that are part of a mobile device within the vehicle.
• Remote Sensing consists of numerous techniques including such things as weather satellites that can provide background information with respect to weather and road conditions.
• All of these surveillance method could be used in both a passive or active mode.
• Passive mode is where general information is recorded and stored for a fixed amount of time, then discarded unless an event such as an accident is identified. If an event such as an accident occurs, pertinent information is retrieved and analyzed and then transmitted to an analysis station or first responders or other surveillance systems.
• Active mode surveillance is defined as occurring when some sensor pattern indicative of an event of interest occurs and is used to initiate specific
• the sensor pattern may trigger additional recordation of information and/or direct sensors to monitor at a certain location and perhaps with an increased frequency of measurement than that which happens during passive surveillance.
• Aerial Surveillance can be from fixed wing aircraft or rotary aircraft or lighter than air vehicles. The surveillance can occur from manned or unmanned vehicles.
• passive aerial surveillance is used by itself or in tandem with other surveillance methods.
• FIG. 1 An example of a passive aerial surveillance is shown in FIG. 1.
• An aerial vehicle 101 continually scans an area filled with roads and vehicles 102. Vehicles coming in and out of the area 102 are identified. An account of individual vehicles entering and leaving the survey area can be maintained over time.
• An aerial surveillance module (either that is part of the aerial surveillance vehicle or that is in remote communication with the aerial vehicle) is used to observe ground vehicle movement.
• the aerial surveillance module in addition to vehicle recognition software, also has a digital map of the survey area. By tracking the movement of individual vehicles through the survey area, the aerial surveillance module can detect:
• the aerial surveillance module can transmit instructions to other surveillance systems (either aerial, fixed or vehicle based) via wireless communications to alert these other systems that active monitoring of a situation may be necessary.
• FIG. 2 depicts result that could be obtained from aerial surveillance.
• vehicle 201 and a second vehicle 203 are observed at a first location and are continued to be tracked until a second time where it is observed that Vehicle 203 collides with vehicle 201 at location 205.
• information may be transmitted to vehicles 201 and 203 or to emergency authorities or others.
• the information may contain the travel history of the two vehicles including their locations and speeds and driving behavior.
• communications may be initiated with other surveillance systems when a vehicle moves out of the surveillance area and if there was a reason to continue monitoring it in other quadrants or surveillance areas.
• a scenario for aerial surveillance is:
• a. Notify local surveillance assets to start actively monitoring vehicles with risky behavior by transmitting location and trajectory information b. Notify individual vehicle monitoring systems in the vicinity of vehicles that are driving in a risky manner, of the risk, and make sure that monitoring systems are activated c. When vehicles are near the boundary of the aerial surveillance area, notify the adjacent aerial surveillance areas to actively monitor the incoming vehicle.
• Aerial surveillance at lower altitudes may comprise passive monitoring, for example, at a busy intersection where many accidents are known to happen simply scan the intersection recording a time series of information (for example video) and simultaneously be performing pattern recognition analysis on the information for patterns that would indicate an accident or impending accident. Once an accident is detected or is imminent, the time series data that is pertinent to the accident, is transferred to an analysis station or the authorities or to vehicles involved in the accident.
• passive monitoring for example, at a busy intersection where many accidents are known to happen simply scan the intersection recording a time series of information (for example video) and simultaneously be performing pattern recognition analysis on the information for patterns that would indicate an accident or impending accident.
• Surveillance system at an interchange may not be on an air vehicle, but could be attached to a pole or other structure where sensors are high above the interchange, so effectively there is an aerial view of the interchange.
• Active surveillance may be initiated when any passive surveillance system detects a pattern of concern. Active surveillance would occur when a passive surveillance system deviated from it standard sweep path to monitor a specific vehicle or vehicles or a specific location.
• Vehicles equipped with sensors that measure vehicle motion, and vehicle behavior and/or motion and behavior of adjacent vehicles fall into this category and are part of embodiments of this invention.
• On-vehicle sensors are monitored for patterns indicative of an accident occurrence or an impending accident. These patterns, for example, could be rapid changes in acceleration, proximity alerts either from video analysis or other
• electromagnetic monitoring such as sonar, or infrared.
• Ground based surveillance can be one of:
• Remote sensing such as analysis of imagery from satellites can provide general information about driving conditions, for example, weather. Resolution of imagery would typically be on the other of 1 square meter or more, so in most cases, you could not discern an individual vehicle.
• a variety of flying vehicles can be used for aerial surveillance.
• aerial vehicles are better suited for different applications.
• Basic types of aerial vehicles include fixed-wing, traditional helicopters, multi-prop copters such as a hexi-copter, blimps or dirigibles; and variations or combinations of the above.
• a fixed location implies that the aerial vehicle is normally housed on the ground when not in use, in a single location that is more or less central to area under surveillance. Size of the vehicle will depend on the application.
• Air vehicle can be designed with electric motors powered by batteries which are in turn charged with solar panels.
• very light weight slow moving fixed wing or blimp type vehicles can be up in the air for extended periods of time with minimal fuel.
• a flight vehicle When wishing to capture information about an accident while it happens or shortly thereafter, in an embodiment, a flight vehicle is in communication with sensors within the vehicle such as accelerometers. When either an impending accident or an accident in progress is detected via analysis of patterns, the flight vehicle is launched very rapidly in an attempt to have a vertical launch should the vehicle begin to roll over.
• the air vehicle could be a rotary type or a type of rocket with a deployable parachute.
• a rocket or similar device could be deployed much like a torpedo, from a tube, but vertically oriented.
• Virtually any type of airframe can be made to take off or, land and fly autonomously. This would require location and altitude sensors as well as some frame of reference, for example a digital map or a location beacon either at a fixed location or on a vehicle of interest.
• the flying vehicle can be piloted remotely 6.2.5.3 Combination
• a combination of remote piloting and autonomous flight can be used.
• take-off and landing can be remotely piloted, while in surveillance mode, the flight could be autonomous.
• an aerial vehicle will contain a human pilot.
• 6.2.6.1 Quad or other copter There is a variety of remotely operated or semi-autonomous vehicle which achieve lift using one or more propellers. Configuration with 4 or 6 blades usually mounted in the same plain and all oriented with the direction of thrust perpendicular to the mounting plane. These copter or drones as they are often called come in a variety of sizes from less than a kilogram in weight up to 20 kilograms or more
• Blimps have the advantage that they can stay in flight for extended periods as most of the energy is directed to moving the vehicle rather than keeping it aloft and the helium provides most of the lift.
• a parachute mounted sensor suite which comprises a camera and perhaps other sensing devices is contained in a cylindrical or other aerodynamic container which in turn is attached to a chemical propellant or compressed gas engine or a kinetic energy device (for example a spring) capable of propelling the sensor suite and parachute at rapid speed above the vehicle.
• the motor or other propulsion device is actuated by a signal from the vehicle monitoring system (or potentially a remote systems) when it detects an accident about to happen or that is in progress.
• the vehicle monitoring system is equipped with a sensor or sensors (such as a gyroscope) that can be used to determine if the vehicle is oriented with the top of the car being up (within a threshold angle). If the top of the vehicle is not up and within the threshold angle of being perpendicular to the vertical direction, the apparatus is not launched - to prohibit injury or damage to objects or people on the ground.
• a sensor or sensors such as a gyroscope
• FIG 6 depicts a launch scenario in an embodiment of this invention that utilizes a projectile with a parachute.
• the apparatus is housed in a weatherproof container with either a retractable hatch or cover that is penetrable by the apparatus.
• the sensor suite is in standby mode 602 and in communication with a pattern detection module in the vehicle. If an accident pattern is identified 604, the launch mechanism is checked to be in a vertical position 606 and if so, the apparatus is launched 608, the hatch is either opened (prior to engine ignition) or penetrated when the apparatus lifts off.
• An example of a mechanism for launch would be much like a jack-in-the-box where a cover and latch hold into place the projectile which is mounted on a spring. Once the latch is opened, the projectile is free to exit and the spring force is released propelling the projectile into the air.
• a mechanism for launch would be much like a jack-in-the-box where a cover and latch hold into place the projectile which is mounted on a spring. Once
• the parachute is deployed by various means known in the art.
• the vehicle is located and tracked.
• the camera is mounted on a gimbal and servo motors keep the lens oriented towards the car. There may optionally be a servo to stabilize the compass direction of the view of the camera, as the parachute and apparatus may be rotating.
• the apparatus is equipped with a propeller or propellant to provide a horizontal and/or vertical forces to either prolong the length of time the apparatus can stay airborne or to be able to circle the vehicle for measurements at various altitudes above the vehicle or angles around the vehicle.
• the camera may be equipped with a zoom lens to capture more or less detail of the accident scene.
• Potential triggers (patterns) that would initiate a launch are the same as described in the section on indications of an accident occurring or about to happen.
• FIG. 4 depicts a similar solution in the art (from European Patent
• EP 0466499 A1 is a battlefield aerial surveillance device where a rocket is launched from a ground vehicle 49 at time (A). At time (B) near the apex of the flight the aerodynamic casing of the rocket is separated exposing the surveillance apparatus 9 with a parachute 15 comprising a camera with a field of view 7 and configured with a device to prohibit rotation 29. The video is transmitted to a ground vehicle at time (E).
• the present invention differs from EP0466499 in that the rocket deployment is from the vehicle being surveyed and the deployment is initiated based on sensor output and pattern recognition.
• the camera may be able to be directed and the parachute may be steerable.
• image software may be able to detect the vehicle of interest and zoom in on it.
• an autonomous air vehicle deployed from a ground vehicle.
• the air vehicle comprises a communication module that is in wireless communication with on-board sensors in the ground vehicle. If a pattern is detected by the surveillance module in the ground vehicle that indicates that an accident in progress or that an accident has happened, this in-turn triggers the launch of the autonomous air vehicle.
• a quadcopter of this size could be launched from a vehicle in a variety of ways: • A rigid quadcopter could be contained in a spherical container housed in a vertical tube imbedded in the vehicle. A spring loaded propulsion mechanism much like the mechanism used to proper a ball bearing in a pin-ball machine could be held in place by a latch. The latch could be triggered by the recognition of an accident pattern.
• the cross arms of the quadcopter could be folded at a point where the two arms cross in the center such that two adjacent motors are nearly touching one another on opposite sides.
• the apparatus in the folded stated could be housed in a bullet or rocket shaped container and launch much like the parachute system of the previous section.
• a rocket is used to deploy payload of a sensor suite attached to a fixed wing or rotary aircraft.
• An example of a vehicle that may be suitable for this type of deployment is show, for example in US Patent US 8444082 B1 .
• sensos there is a variety of sensos that can be used to determine both vehicle movement and behavior and the conditions associated with the vehicle movement and behavior.
• Various type of sensors may be used with aerial vehilces, at fixe ground locations or within vehicles.
• GPS Global Position Satellite Receiver
• This type of device can also be used to determine a low resolution altitude.
• a GPS requires a line-of-site view of 3 (or more) satellites to determine a position, sometimes is may be necessary to augment a location
• Bluetooth Low Energy As part of the protocol for a communication standard such as this, there is a parameter that is a measure of signal strength of the radio frequency signal that is received by a receiver from a transmitter. It is well known in the art that by knowing the signal strength from three different transmitters that are geographic spaced, the relative location of the receiver with respect to the three transmitters can be determined. Of course there is a substantial amount of error in the signal strength measurement so this method only provides an approximate relative location.
• a vehicle is equipped with a radio frequency transmitter and as part of a sensor suite that is deployed using a rocket or a aerial vehicle deployed from the vehicle, there is a directional antenna that receives an indication of signal strength of the transmitted frequency from the radio transmitter, it is possible to determine the relative location of the sensor suite to the vehicle - so that video or other sensors can be directed towards the vehicle.
• the camera would initially point towards the vehicle, and would further register an image of the vehicle and track the vehicle using conventional image analysis software described elsewhere in this document such that the video can be trained on the vehicle and not stay on the anticipated trajectory of the vehicle.
• altimeters There are a variety of altimeters known in the art, which include ones based on barometric pressure and/or a combination of barometric pressure and gps measurements and potential gyroscopic measurements. Altitude is important when dealing with position relative to the earth rather than relative to a moving vehicle.
• a pattern is the term used to describe one or more time-series of sensor readings that can be analyzed to: ⁇ Predict that an accident will happen
• Patterns can comprise a time series of a specific sensor
• acceleration could be measured directly by an accelerometer or inferred from location measurements over time from a GPS receiver and/or a combination of these two types of measurements could be used to determine a mean acceleration for a given time interval by a weighted average of the two measurements, with more weight being attributed to the measurement deemed the most accurate.
• Patterns could also be analyzed in the frequency domain using Fourier analysis
• Patterns are determined by some form of multivariable analysis such as machine learning where data is collected from sensors for many accidents where the extent of damage and severity of impact are known.
• Raster image analysis can be considered another form of pattern analysis. In this case vehicles are identified and tracked.
• Rapid deceleration above a specific threshold that would indicate emergency braking.
• One method of detection of rapid deceleration would be to monitoring vehicle onboard accelerometers and gyros. Airbag deployment
• Patterns may be expressed as polynomial equation; they may be a threshold constant or upper and lower range for a specific sensor; they may be based on frequency and/or amplitude analysis of a single type or multiple types of sensors or they could be a statistical mean value for one or more sensor outputs or environmental factors. Patterns will change over time as more data is added, more sophisticated analysis is performed or more sensor types are available for on-board measurement. Patterns for one type of vehicle may be entirely different than for another type of vehicle. This may be due to different sensor suites being available or different physical attributes of the vehicle. 6.2.13.1 Image analysis software to detect ground vehicles
• one method is to use vehicle recognition software. Patterns in an image that are indicative of a vehicle. There are several methods for analyzing both video, still and infrared imagery to detect vehicles.
• One example of a method for recognizing vehicles in a image is Real-time People and Vehicle Detection from UAV Imagery by Gaszczak, A, etal (see
• New data is collected from vehicle on-board sensors and from external feeds such as sensor suites that are part of the road network system or for example from weather satellites.
• the data for the last time period is stored and analyzed and the older data is thrown out (provided no patterns of interest were detected).
• the data is stored in a memory stack of a set size where new data is added to top of the stack and the oldest data (at the bottom of the stack) is thrown out.
• an accident pattern or impending accident pattern is looked for. If a patterns is detected, indicating an accident or impending accident has occurred or will occur, then the sampling rate may be increased to acquire more data per time period, and/or other sensor data, previously not being recorded, may be recorded.
• the end of the accident event in an embodiment, is defined when the vehicle is stationary. Once the accident is over, the stored data is analyzed to detect damage and injury patterns. If accident and/or injury patterns are detected, then the location and estimated damage and injury associated with these patterns is recorded and transmitted to pertinent individuals or computer servers.
• FIG 3 illustrates and embodiment using a monitoring system within the vehicle.
• Real-time time series data is acquired from many sensors on-board the vehicle 302 and transmitted to an Accident Prediction Module 310.
• the Accident Prediction Module 310 receives external information from other surveillance systems 308 by wireless communication.
• the Accident Prediction Module 310 performs analysis comparing the sensor data feeds 302, 308 to accident patterns acquired from a historical database 304. If an accident pattern is matched to the sensor feeds, this triggers recording of detailed information and a search for damage and injury patterns within the data. If a damage or injury pattern is detected, then analysis is performed concerning the extent of damage or injury and the location of damage or injury and this information along with the underlying data is transmitted to interested parties.
• Monitor for a prescribed time or until an accident occurs OCR the license plate; send warning message for continued bad driving; citation if bad behavior does not cease.
• Sensor systems within the cars themselves are contacted via wireless communication and instructed to record information at a rapid rate.
• Pre-accident patterns from the vehicle/s are compared with patterns either from macro aerial or local aerial surveillance systems to verify the analysis
• sensors that can be used to detect an adjacent vehicle.
• Video cameras for example could be used in conjunction with vehicle detection software to know when an adjacent vehicle is too close.
• Adjacent vehicles will reflect light and other forms of electromagnetic radiation such as infrared, and / or may be equipped with an active transponder which transmits a signal which can be located and identified.
• Modern vehicles are generally equipped with a variety of sensors that measure physical parameters associated with the moving vehicle. These sensors can be a part of the vehicle or within the vehicle, for example as part of a mobile device.
• Vehicle behavior can be inferred based on patterns exhibited in the sensor data overtime -either from observations of a single type of sensor or a sensor suite, for example a gyroscope and also a 3 component accelerometer. Rapid changes in the orientation of the vehicle may be exhibited by changes in the values measured by a gyroscope and/or accelerometers. It is intuitively known, for example, if a car is spinning on wet pavement or on ice, that there is a strong likelihood that the vehicle will sustain damage and/or passengers will be injured. However, this likelihood can be quantified by tracking patterns in the sensor output leading up to previous accidents with known damage and injury - performing statistical analysis on those patterns.
• Patterns observable from aerial surveillance may indicate: ⁇ A burning vehicle (infrared signature)
• Hardware for an on-board accident detection and analysis system comprises the following components:
• an on-board database comprising: o vehicle specific information; o patterns, for the individual vehicle type, used to analyze sensor data to detect accidents and to assess resulting injury and damage and useful to predict driver behavior and driver / insurance risk; o driver information; o emergency contact information;
• a remote central server in communication with multiple vehicle systems comprising : o one or more computers; o a comprehensive central database located on one or more servers comprising:
• the system will initiate the following sequence: 1 ) launch drone or rocket a) if the vehicle is equipped with a spring loaded hatch, open it b) check the orientation of the car to make sure that the launch will be relatively vertical - based on vehicle sensor input such as magnetometers or accelerometers.
• the following tasks comprise one method to determine accident patterns initially based on accident reports:
• ⁇ Develop transfer functions between observations in historical databases built from accident reports to on-board sensor measurements that are indicative of the observed damage. For example, an accident impact could be inferred when a rapid deceleration is detected either by accelerometer measurements or change in speed measurements. Location, and relative speed of an impact can be inferred based on 3 component acceleration. Alternatively, a side impact can be inferred when a side airbag is deployed. ⁇ Test the transfer function by predicting vehicle damage and resulting cost based on sensor data after an accident. Confirm the prediction based on conventional accident and insurance adjustor reports.
• collisions may be classified based on relative speed of impact, for example. With more accurate speed data from sensors and vehicle weights, the classification could be changed to an impact momentum in N/m 2 using finer ranges for classification rather than simply an approximate relative speed of collision.
• Raw data may need to be parameterized in such a way as they can be used into a numeric model.
• An example of parameterization would be to characterize incidents into a grouping. For example, it may be desirable to collectively refer to impact force based on accelerometer readings in ranges in units of meters/second 2 rather than actual recorded values or as a mean over a time frame.
• Database maintenance comprises removing older or poorer quality data, continually updating the patterns as newer and better information comes on line.
• patterns can be broken into smaller subdivisions, for example, an accident pattern could be vehicle type specific as to vehicle class specific.
• Range of fixed based aerial vehicles and sweep are; length of deployment; weather extremes that operation can occur.
• FIG. 7 is an example of a distributed vehicle database system.
• System hardware is distributed between one or more central servers 702 and client systems 706.
• the client systems can include, for example, passenger vehicles 708, trucks 720, satellite servers 712, external data feeds, such as weather 714 and traffic 718, onboard vehicle monitoring systems and portable devices 710.
• Information is communicated in the form of a query or a notification from the one or more central servers 702 to clients 706 via a radio broadcast 704. All clients have a radio receiver that conforms to the radio frequency and standard of broadcast as the radio broadcast device connected to the central server/s. All of the clients 706 in range of the broadcast receive the broadcast and digest the query or bulletin.
• each client 706 establishes two-way communication, for example, over a mobile network 724, with the central server/s 702 and uploads to the central server/s 702 the requested information for a query or downloads the available information to the clients 706 for a bulletin.
• the data are maintained in the device or system where it was generated and/or in a regional client of some kind. All data does not need to be uploaded to a central server for storage and subsequent analysis unless a central server asked for it.
• a vehicle diagnostic port onboard diagnostics OBD
• OBD onboard diagnostics
• sensors including: mass flow, oxygen, seat belt, air bag, tire pressure, gps, accelerometers, gyroscope, and more.
• VIN and/or make model and model year, accessories such as larger than normal tires, engine type and size, etc.
• the driver may be identified either by manually input, or via automatic connection between the vehicle and a mobile device of the driver, or by visual or audible input query by controlling software within the car. These are just examples and any type of identification of the driver could be used.
• the driver could carry an RFID tag that identifies her, for example.
• Information relayed from roadside sensors or sensors or devices that monitor road conditions or weather can be stored. These can come from Bluetooth connections, side bands on radio stations (for example traffic); internet feeds and peer- to-peer networks from other vehicles.
• Other information may concern repair history of warn vehicle parts as related to all the above mentioned information. This information could be stored directly in a server at a repair shop - for example.
• All information stored in the distributed database is optionally spatially and/or temporally referenced.
• the information can be referenced based on the type of vehicle and/or how the vehicle is equipped and/or by the driver of the vehicle. Patterns that relate changes in one or more sensor and environmental data overtime to events are also stored in the database, both in vehicles were the patterns are pertinent and in a central database located on a central server or in satellite databases.
• Patterns are created by analyzing many datasets with known events happening and developing a predictive model of the event based on the available data. Patterns are updated by a central server in communication with client systems through the process of querying the client system (such as a vehicle fleet) and having clients (vehicles) that match the requirements for the pattern, respond with relaying data for the event in question.
• client system such as a vehicle fleet
• clients vehicles
• FIG. 8 explains how an embodiment of the system is used.
• the system consists of one or more central servers 802 equipped with one or more processors and one or more client devices 804 (see client devices as depicted in FIG. 7).
• the central server/s is configured with software to predict events and to make assessments.
• the central server/s is further equipped with a list of events of interest.
• the central server/s 802 needs to correlate potential contributing factors to particular events or types of events 806. In some embodiments, the prediction or assessment is of regional or local in interest only and this will effect what sources of information are used 810.
• the central server/s 802 broadcasts, using a radio broadcast transmitter, a request to all potential clients 804 including identifying parameters of type of information and also what type of vehicle or other source for the information that is needed 812. This request is generated by instructions loaded in one or more processors and referred to as a query engine.
• Clients 804 are typically listening for broadcasts, using a radio broadcast receiver, from the central server/s 802. Once a broadcast is detected by a client, each client 804 parses the query or bulletin that was broadcast and determines whether it is able to comply with all of the
• the client 804 If the client 804 can comply and the request (or query) is for information, the client will 1 ) relay the requested information to the central server/s 802, using a two-way radio transceiver, and/or 2) start collecting the requested information from sensors or other devices. Once a packet of information is acquired, the client 804 establishes a two-way radio communication link using the transceiver and uploads the information 818 to the central server 802 which receives the information on a radio transceiver that is part of the central server/s.
• the central server/s 802 uses a form of statistical analysis to establish a relationship between the uploaded information from numerous clients 804 and creates predictive models 820 in the form of patterns and indicators.
• a broadcast using the transmitter, is made to the clients 804 to let them know the derived patterns, and indicators are available for usage 822.
• FIG. 9 depicts how certain events trigger other events. A follow-on analysis may be necessary after certain types of events are detected to form a proper assessment of needs to be performed.
• a client 902 continuously monitors sensors and external feeds 904 and compares to patterns and indicators to detect an event. If an event is detected 906, pre-programmed activities are initiated that are associated with the event 908. One of these activities may be to inform the central server/s of the event and to upload information pertaining to the event.
• the client 902 establishes two way
• the central server/s 910 receives the information 912 and determines the type of follow-up information that is needed 914.
• An example would be, an accident is detected; it is reported to the central server along with particulars about speed, location, severity of impact.
• the central server may be programmed to determine if the accident caused a traffic slow down; therefore, it would broadcast a bulletin that it is interested in knowing the speed of vehicles that are in the vicinity of the accident so it can determine what, if any, roads were affected by the accident 918.
• other clients 920 that meet the selection criteria would communicate with the central server and upload their speed 922.
• the central server could also send out a request for available tow trucks that could be dispatched immediately to the scene. Yet another request would be to the insurance company of the vehicle involved in the accident; to emergency responders; and the like to send out a representative to the scene. Another example would be notifying local auto body shops of a potential client.
• FIG. 10 describes periodic update of the patterns and indicators stored in the system. Patterns and indicators need to be updated by central server/s. This happens by determining when certain patterns are either too old or new information is available that needs to be incorporated. For example, a new sensor reading may have been determined to be useful in prediction of certain types of events and has previously not been included in the patterns for that event.
• the central server/s 1002 would send out a query for additional information to be used for this update including the type of sensor reading that are needed and other pertinent information 1006.
• Potential clients of interest receive the query and determines if they are a client 1004 of interest (have pertinent information) 1014. Clients 1004 of interest establish a link 1016 with the server/s 1002 and then upload pertinent information 1018.
• the server/s 1002 receives the information 1008, and retires older information 1010 and re-compute updated patterns and indicators 1012.
• Table 1 is an example of information that might be conveyed in a bulletin using the distributed vehicle database system - regarding a terrorist alert status.
• the scenario would be as follows: One or more of the central servers received a statement from the department of Homeland Security (a potential client) indicating that there will be an amber alert for a specific geographic area for a specified period.
• the information in the alert could be represented with fields defined in table 1 and with their XML (extensible markup language) counterpart below that.
• a single active alert Contains the following attributes start
• the central server may be programmed to receive the xml above and parse it. Based on the location fields, the type of alert field and the duration, the server may be further programmed to divert members of a fleet of vehicle away from the alert area if they are scheduled to be in the alert area at the specified time. This would happen by broadcasting a request that all members of the fleet of interest to establish a link with the central server and receive further information about the threat level. This would save having to relay the entire message to all vehicles. In addition, the central server would know have a good indication of how many vehicles in its fleet would be impacted by the alert. Of course other scenarios could be treated in the same manner.
• the prediction of required maintenance and the estimated cost of maintenance is transmitted to the vehicle when service or maintenance is needed.
• the transmission can occur to either the in-vehicle system or to a mobile device carried by a driver or passenger or directly to a service technician.
• results can be displayed either graphically and/or in text on a screen in the vehicle - for example, an infotainment system screen.
• Messaging channels operate. Communication could also be peer-to-peer and/or repeated.
• the central server/s could broadcast a query or bulletin which is received by a vehicle. The vehicle could then rebroadcast it over a different frequency or using a different protocol - for example Bluetooth.
• Communications between various sensors and a processor in a client can happen via the system bus in the client or via short range wireless or via fiber optics or wired connections.
• the client device is an add-on product or consists of software running on a mobile device within a vehicle, then communication with the integral vehicle sensor may be by using an interface that can read on-board diagnostic (OBD II) codes by interfacing with a vehicle portal designed for external communications.
• OBD II on-board diagnostic
• DTC diagnostic trouble codes
• client device that are in a stationary location, for example, road side sensor suites, an autobody repair facility, communication to a certain server or other nodes could happen over the internet and/or other form of wired and/or satellite communication.
• a client device may communicate with a central server and/or a client device using a per-to-per network where a message is transmitted to one or more other client devices and then the message is repeated for other client that are in communication with the transmitting client device.
• vehicle maintenance and service requirements are predicted by comparing the observed conditions that occur during vehicle operation over time with similar observed conditions for similarly classed vehicle used in similar conditions stored in a historical vehicle maintenance database.
• Algorithms are developed to classify each maintenance or service event as succinctly as possible, given the available data, such that when the conditions requiring maintenance or service for a vehicle in use match a classification, this can be used with a degree of certainty, to predict resulting maintenance required and the parts and services necessary to effect the maintenance.
• the observed conditions of interest during vehicle operation include:
• Raw data that may be used to predict maintenance and service needed can come from a plurality of sources.
• Sources include:
• the database initially will have a mix of more qualitative data, for example from manually entered fleet maintenance records and repair shop invoices and quantitative data, for example, from in-vehicle sensors. As such there is a subjective element in the reporting and the likelihood of human error will reduce the quality of the manually entered data and therefore if the manually entered data makes up the bulk of the available information, the error in prediction of maintenance will be greater.
• the information For information from disparate sources to be compared, the information must be normalized, i.e. converted to the same units of measure and be relative to the same reference frame.
• the quality and precision of the data must also be evaluated and represented within the database in a normalized fashion. In other words, if for example, one speed is known to be accurate within +/- 10 mph, then all speeds in the database should have an error of estimate in mph (as opposed to kph for example). 6.3.5 Components of the system
• One or more processors containing:
• Time period of Interest o Radio Transceiver used to upload and download information to one or more specific client systems after two-way communication has been established by the client
• Radio Receiver for information from central servers via the one-way transmitter and/or other vehicles or systems including:
• Radio Transceiver configured to establish two-way communications with one or more central servers and further used to upload and download information o Sensors (in-vehicle and external to vehicles) ⁇ See listing of sensors elsewhere in this document
• the central server can query the satellite servers for regional information, when, for example, an insurance carrier wants to adjust rates base on region or a fleet management company wants to perform preventative maintenance on their fleet which is region dependent.
• An operator of the system may desire to update the geography of a specific road segment. To do this a query may be sent to all vehicle, requesting a download of gps traces for vehicles that have traversed the segment within a specified time period. Vehicles that meet this requirement and that received the query then respond by sending the appropriate information. Once the information is received, then the GPS traces can be processed to revise the geometry or the road segment in the central database. Transportation network information comprises the physical location of roads, the road condition, traffic density throughout the day or week and typical weather conditions for a given time and relative to a road position and more. [0205] Another example of how the distributed database could be used would be, for example, in the current Volkswagen scandal.
• the central processor/s could send out a query request to all vehicles in the network and request that all vehicles with a specific model and model year and that have the specific engine type of interest, record the above parameters over a period of time and transmit that information back to the central server.
• the vehicles in question will already be recording and storing this information, and can relay this information to the central server for a former time period once it is requested by the central server.
• the central server could send the stored relationship (pattern or indicators) with the query, so that the individual vehicle systems can determine emission values based on the stored pattern and/or indicators and send only the computed emission values back to the central server.
• Another example usage is in comparing vehicle wear as a function of region. Similarly, equipped vehicles will wear out faster or sustain differing levels of damage when involved in an accident depending on where the vehicle is driven. This type of information could be important for determining insurance rates. Corrosion due to salt being used as a de-icer for roads, corrodes vehicle parts significantly faster than when the salt is not applied. Likewise, in an area where there is significant rain, corrosion will be higher than in an arid region.
• the present invention may be conveniently implemented using one or more conventional general purpose or specialized digital computers or microprocessors programmed according to the teachings of the present disclosure, or a portable device (e.g., a smartphone, tablet computer, computer or other device), equipped with including one or more sensors (e.g., accelerometers, GPS) or where the portable device are connected to the data collection devices that are remote to the portable device, or that are connected via wired or wireless means.
• a portable device e.g., a smartphone, tablet computer, computer or other device
• sensors e.g., accelerometers, GPS
• Appropriate software coding can readily be prepared by skilled programmers based on the teachings of the present disclosure, as will be apparent to those skilled in the software art.
• the present invention includes a computer program product which is a non-transitory storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the present invention.
• the storage medium can include, but is not limited to, any type of disk including floppy disks, optical discs, DVD, CD-ROMs, micro drive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
• a vehicle accident surveillance network comprises at least one of: a) one or more surveillance systems which in turn comprises:
• a sensor suite configured to observe ground based vehicles
• a pattern recognition module configured to interpret the sensor suite readings as vehicle movements, locations, pending accidents, and accident incidents and to identify specific vehicles
• a wireless transceiver configured to transmit and receive the identity and location of specific vehicles that had pattern identified, to surveillance systems
• one or more deployable aerial surveillance systems comprising:
• an airframe configured to launch from one of a ground based vehicle, and fixed base station, and a larger airframe, wherein a launch is triggered by detection of a pattern indicative of an accident occurring or about to occur as detected by one or more of the surveillance systems;
• a second wireless transceiver configured to receive the identity and location of the vehicle or vehicles which correspond to identified patterns from one or more surveillance systems;
• a directional sensor suite configured to be directed towards the identified vehicle or vehicles after deployment of the aerial surveillance system
• an aerial surveillance module configured to:
• a deployable aerial surveillance system is configured with a receiver that can identify a location beacon (for example attached to a vehicle) and track the location beacon.
• deployable aerial surveillance systems are deployed by an operator when the system is provided with one or more of: a) coordinates of a vehicle to be surveyed;
• Vehicle accident surveillance network can be one or more of: a) an airborne surveillance system; b) a ground based vehicle equipped with a surveillance system; and c) a ground based stationary surveillance system.
• airborne surveillance systems are configured: a) with image detection sensors that observe the earth below in a plurality of
• the pattern detection module is configured to detect vehicles using image
• Surveillance systems in an embodiment comprises a memory cache configured to store sensor data from sensors for a predetermined time prior to the present time and further configured to save this data upon detection of a pattern and continue to save incoming sensor data for a predetermined time after the pattern is detected.
• An embodiment of a vehicle accident surveillance system installed in a ground vehicle comprises: a) an on-vehicle sensor suite configured to observe location and motions of the ground vehicle;
• a pattern recognition module configured to interpret the sensor suite readings as pending accidents, and accident incidents
• a deployable aerial surveillance system comprising:
• an airframe configured to launch from the vehicle when triggered by detection of a pattern indicative of an accident occurring or about to occur.
• a directional sensor suite configured to be directed towards the vehicle after deployment of the aerial surveillance system
• an aerial surveillance module configured to:
• a vehicle accident surveillance system installed in a ground vehicle can optionally be configure with a directional sensor suite that contains one or more cameras.
• a transceiver in an accident surveillance system is optionally configured to: a) communicate with other accident surveillance systems;
• a vehicle accident surveillance system installed in a ground vehicle comprises: a) an on-vehicle sensor suite configured to observe location and motions of the ground vehicle;
• a pattern recognition module configured to interpret the sensor suite readings as pending accidents, and accident incidents
• a wireless transmitter configured to transmit a request to nearby surveillance systems to deploy and monitor the ground vehicle should the pattern recognition module detect a pattern indicative of a potential accident or accident.
• a system to create, manage and utilize a vehicle diagnostic distributed database comprises:
• At least one central server operable on one or more computers configured with at least: i) a radio transmitter configured to broadcast a query; ii) a first radio transceiver configured to perform two-way communications with the one or more client devices; and iii) a query engine configured to generate a query containing:
• a query is a request to upload information that is specific for a particular vehicle type or component and related to known vehicle events or situations and comprises one or more of:
• vehicle component replacement and maintenance records a) vehicle component replacement and maintenance records; b) vehicle sensor data referenced in space and time; and c) environmental data referenced in space and time.
• a system to create, manage and utilize a vehicle diagnostic distributed database has at least one central server that is further configured to develop at least one of patterns and indices to predict vehicle events and identify situations based on information, from the one or more client devices, that was previously uploaded to the central server.
• a system to create, manage and utilize a vehicle diagnostic distributed database comprises query engine that generates a bulletin apprising clients of interest on the availability for download of, one or more of patterns and indices and instructions for the usage of the one or more patterns and indices and a radio transmitter broadcasts the query.
• a system to create, manage and utilize a vehicle diagnostic distributed database clients of interest establish communication with central servers using a radio transceiver and download patterns and indices to predict events and identify situations.
• a selection criteria comprising at least one of make, model, year of manufacturer and optional equipment of a vehicle is used.
• a selection criteria comprises at least one of a geographic region, a climate zone, and within a political boundary.
• a request can be made for GPS traces along roads a client vehicle has traversed.
• a server can receive a requested GPS trace/s and is configured to update road geometry based on the GPS trace/s.
• identified events and situations can be:
• client device can be a:
• a database comprises at least one:
• the system comprises:
• one or more computer based servers configured with at least: i) a broadcast radio transmitter; ii) a first radio transceiver; and b) one or more client devices configured with at least: i) a broadcast radio receiver; ii) a second radio transceiver; the one or more computer based servers transmits, using the broadcast radio
• the transmitter a request to one or more of upload and download information and further containing selection criteria
• the one or more client devices a) listen for and receive the transmission, utilizing the broadcast radio receiver; b) determines whether the selection criteria are met; and c) if the selection criteria are met, establish communication between the first and second radio transceivers and perform the request.
• a communication method is used to operate a distributed vehicle diagnostic database which comprises:
• the broadcast contains a query or bulletin including a client selection criteria
• b) listening for and receiving the broadcast utilizing the broadcast radio receiver that is part of a client device and determining whether the client device meets the client selection criteria, and if the client device meets the client selection criteria, establish communication between a first radio transceiver that is part of the client device and second radio transceivers that is part of the one or more central servers, and moving information between the one or more computer servers and the client device that meets the client selection criteria.
• a communication method is used to operate a distributed vehicle diagnostic database and comprises:
• a communication method is used to operate a distributed vehicle diagnostic database with a client device that is one of a:
• a communication method is used to operate a distributed vehicle diagnostic database with a client transceiver of the one or more client devices configured to also act as a repeater transmitting information to another client device which in turn can repeat the information and further transmit to yet another client or one or more of the computer based servers.
• a vehicle accident surveillance network comprises: a) one or more surveillance systems comprising:
• a sensor suite configured to observe ground based vehicles
• a pattern recognition module configured to interpret the sensor suite readings as vehicle movements, locations, pending accidents, and accident incidents and to identify specific vehicles
• a computer processor configured to receive a query from the broadcast radio receiver and evaluate it; and b) at least one central server operable on one or more computers configured with at least:
• a radio transmitter configured to broadcast a query
• a second radio transceiver configured to perform two-way communications with the one or more surveillance systems
• a query engine configured to generate a query wherein the one or more surveillance systems: a) detects patterns, b) identifies a vehicle or vehicles associated with the patterns; c) determines the location of the vehicle or vehicles; d) transmits this information using the first radio transmitter to the second radio transmitter of the at least one central server; and wherein the at least one central server:
• surveillance systems in proximity to the vehicles or vehicles identified in the query respond by: a) recording information using the sensor suite about the vehicle or vehicles and in the vicinity of the vehicle or vehicles;
• the surveillance systems can be deployable aerial surveillance systems further comprising: a) an airframe configured to launch from one of a ground based vehicle, and fixed base station, and a larger airframe, wherein a launch is triggered by receiving a query from the at least one central server if the aerial surveillance system is in proximity to the vehicle or vehicles;
• a directional sensor suite configured to be directed towards the identified vehicle or vehicles after deployment
• an aerial surveillance module configured to launch the deployable aerial
• the surveillance system and after being launched, determine the relative location of the identified vehicle or vehicles, and one or more of: approach the identified vehicle or vehicles, circle the vehicle or vehicles at a predetermined circumference and altitude, and point the directional sensors towards the vehicle or vehicles and record the sensor data.

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