WO2014179481A1 - Methods and systems for monitoring roadway parameters - Google Patents

Methods and systems for monitoring roadway parameters Download PDF

Info

Publication number
WO2014179481A1
WO2014179481A1 PCT/US2014/036203 US2014036203W WO2014179481A1 WO 2014179481 A1 WO2014179481 A1 WO 2014179481A1 US 2014036203 W US2014036203 W US 2014036203W WO 2014179481 A1 WO2014179481 A1 WO 2014179481A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
road
computer
data point
implemented method
Prior art date
Application number
PCT/US2014/036203
Other languages
French (fr)
Inventor
Maxim Sokol DIAMOND
Original Assignee
Diamond Maxim Sokol
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Diamond Maxim Sokol filed Critical Diamond Maxim Sokol
Priority to KR1020157034177A priority Critical patent/KR20160021430A/en
Priority to EP14791306.5A priority patent/EP2992425A4/en
Priority to US14/888,052 priority patent/US9869630B2/en
Publication of WO2014179481A1 publication Critical patent/WO2014179481A1/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N19/00—Investigating materials by mechanical methods
    • G01N19/08—Detecting presence of flaws or irregularities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • E—FIXED CONSTRUCTIONS
    • E01—CONSTRUCTION OF ROADS, RAILWAYS, OR BRIDGES
    • E01C—CONSTRUCTION OF, OR SURFACES FOR, ROADS, SPORTS GROUNDS, OR THE LIKE; MACHINES OR AUXILIARY TOOLS FOR CONSTRUCTION OR REPAIR
    • E01C23/00—Auxiliary devices or arrangements for constructing, repairing, reconditioning, or taking-up road or like surfaces
    • E01C23/01—Devices or auxiliary means for setting-out or checking the configuration of new surfacing, e.g. templates, screed or reference line supports; Applications of apparatus for measuring, indicating, or recording the surface configuration of existing surfacing, e.g. profilographs
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • 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
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • 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
    • G08G1/012—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
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • 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

Definitions

  • the disclosed technology relates to methods and systems for monitoring road parameters, and more particularly, to methods and systems for monitoring pavement and environmental conditions surrounding vehicles.
  • the present disclosure describes methods and systems that can provide for continuous monitoring of road parameters, e.g. the methods and systems can allow for the detection of road quality patterns that indicate future roadway disruptions or allow road maintenance crews to be proactive rather than reactive.
  • a computer-implemented method comprises the steps of: receiving, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates; analyzing the plurality of data points; determining a road condition score for each data point; and applying the road condition score for each data point to a mapping module using the GPS coordinates.
  • each data point can be recorded at a regularly-spaced sampling period, e.g., a defined time or a defined distance.
  • the road condition score can be a standard deviation value calculated for each data point of the plurality of data points.
  • the standard deviation value can be matched to the GPS coordinates to evaluate and model road roughness for a specific section of road.
  • the standard deviation value for each data point can be visualized using a GIS system. That is, the standard deviation value can be color-coded for a specific section of road on a road condition map.
  • the road condition map can be provided to a client device, e.g., a smartphone, computer display or some other visual display, for personal usage or used by municipalities for road monitoring services.
  • the computing device can be integrated with a vehicle computer system or the computing device can be remote from the data collection unit and the computing device receives the plurality of data points over a wireless communication system.
  • the data collection unit can be a smartphone or an accelerometer.
  • the data collection unit can include a storage module for storing the plurality of data points and the GPS coordinates.
  • the data collection unit can be mounted to a vehicle.
  • a system comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: receiving, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates; analyzing the plurality of data points; determining a road condition score for each data point; and applying the road condition score for each data point to a mapping module using the GPS coordinates.
  • the road condition score can be a standard deviation value calculated for each data point of the plurality of data points.
  • the standard deviation value can also be matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
  • a computer-program product the product tangibly embodied in a machine-readable storage medium, including instructions configured to cause a data processing apparatus to: receive, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates; analyze the plurality of data points; determine a road condition score for each data point; and apply the road condition score for each data point to a mapping module using the GPS coordinates.
  • the road condition score can be a standard deviation value calculated for each data point of the plurality of data points and the standard deviation value is matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
  • the methods and systems according to the present disclosure can allow for real-time assessments of road quality and conditions, air quality, nearby traffic conditions, weather conditions, radiation, noise, vehicle speed/trajectory and/or insolation.
  • Figure 1 is a block/flow diagram of a system for monitoring road parameters as disclosed in the specification
  • Figure 2 is a flow chart showing a method for monitoring road parameters as disclosed in the specification
  • Figure 3 is an illustration of a road condition map as disclosed in the specification.
  • Figure 4 is illustrations of road condition monitoring maps as disclosed in the specification.
  • Figure 5 is a flow chart showing a method for monitoring road parameters as disclosed in the specification.
  • Figure 6 shows a schematic diagram of an example of the disclosed technology.
  • FIG. 1 illustrates a block diagram of a system 100 for monitoring road parameters according to the present disclosure.
  • One or more data collection units, e.g., sensors, 150 can be mounted on a vehicle, e.g., cars, trucks, motorcycles, bicycles, or any other mode of transportation used on roads.
  • the sensors 150 can be placed on or installed within the vehicle, e.g., pre-installed by factory during manufacture, or installed by the consumer sometime thereafter.
  • the accelerometer can be located on or nearby a hard mounting point thereby reducing unwanted vibrations. Multiple mounting points, close to the sensor, and/or a thicker PCB also help to reduce the effect of system resonance on the performance of the sensor.
  • the senor can placed on the dashboard of a car with Velcro or the sensor could also be placed on the undercarriage of the car in close proximity to a wheel rim and held in place using a weather-resistant epoxy.
  • a multiplicity of sensors may be used.
  • the sensors 150 can be placed at different locations and mounted using a variety of mounting methods depending on the intended application.
  • the various sensors can be used to log road quality parameters, such as but not limited to accelerometers to measure road quality, carbon dioxide sensors to measure air quality, and any other sensor for detection of the road/pavement or the air or traffic surrounding the vehicle.
  • the accelerometer can have a complete 3-axis acceleration measurement system with selectable measurement ranges, e.g., ⁇ 2 g, ⁇ 4 g, ⁇ 8 g, or ⁇ 16 g.
  • the accelerometer can measure both dynamic acceleration resulting from motion or shock and static acceleration that allows the device to be used as a tilt sensor.
  • the sensor for example, can be a polysilicon surface-micromachined structure built on top of a silicon wafer. Polysilicon springs can suspend the structure over the surface of the wafer and provide a resistance against forces due to applied acceleration. Deflection of the structure is measured using differential capacitors that consist of independent fixed plates and plates attached to the moving mass.
  • Acceleration deflects the proof mass and unbalances the differential capacitor, resulting in a sensor output whose amplitude is proportional to acceleration.
  • Phase-sensitive demodulation is used to determine the magnitude and polarity of the acceleration.
  • the accelerometer can also have several special sensing functions, e.g., to sense activity and inactivity, to detect the presence or lack of motion by comparing the acceleration on any axis with pre-defined thresholds, to detect tap sensing and be used to detect single and double taps in any direction, to measure static acceleration of gravity in tilt- sensing applications and dynamic acceleration resulting from motion or shock.
  • the accelerometer can also have a high resolution (3.9 mg/LSB) that enables measurement of inclination changes less than 1.0°.
  • other parameters can be measured using different data collection units, such as road quality/conditions, air quality, nearby traffic conditions, weather conditions, radiation, noise, vehicle speed/trajectory and/or insolation, and the present disclosure is not limited to any particular data collection unit.
  • the sensor(s) 150 can be used to obtain road pavement parameter data at a pre-determined sampling rate.
  • the sampling rate can be measured in time or distance.
  • the sampling rate can take measurements every 0.2 seconds or every 50 feet, it is understood that other sampling rates are contemplated.
  • the sampling rate can be dependent on, e.g., the rate of speed the car is traveling and the dynamics of the road, e.g., curves, straight, etc.
  • the data obtained by sensors 150 can be paired with a GPS Module 110 in a CPU 170 and the combination can be stored in a secondary storage module 120, such as but not limited to a vehicle computer, an SD card, or other type of memory.
  • the secondary storage 120 can be separate from the computer processing unit (“CPU") 170.
  • CPU computer processing unit
  • a MicroSD card can be connected to the CPU 170 using an SPI interface.
  • secondary storage 120 can be integrated with the CPU 170 if non- volatile memory present on-board the CPU 170 is large and fast enough.
  • a wireless data module 130 such as but not limited to a cellular, WiFi, or other wireless data communication protocol, can be provided where recorded data from the sensors 150 and/or secondary storage 120 can be uploaded to a central server 140 for analysis. This can be done when the vehicle is parked and no data is being logged (e.g., to conserve processing resources). This can also be done in real time, at a time preset by the user or manually by the user.
  • the central server 140 can receive a plurality of data points from at least one data collection unit 150.
  • the central server 140 can be partially integrated with a vehicle computer system or the central server 140 can be independent and remote from the data collection unit 150 and receive the plurality of data points over a wireless communication system 130.
  • Each data point of the plurality of data points can include data related to road conditions for a specific section of road. These data points can be paired with GPS coordinates.
  • the central server 140 analyzes the plurality of data points and determines a road condition score for each data point.
  • the road condition score can be, e.g., a standard deviation value calculated for each data point of the plurality of data points.
  • road condition scores from multiple vehicles can be averaged to gain more accurate road condition scores.
  • the road condition scores are matched to the GPS coordinates (Step A4) and can be used to evaluate road roughness for specific sections of roads, (e.g., a number of samples (e.g., 320 samples equating to approximately 1 mile of road) can be collected for a particular section of road; these samples are analyzed as a group and standard deviation values are tabulated for each sample within the group).
  • the road condition score for each data point can be visualized on a map using a Geographic Information System (GIS) associated with the central server 140. (Step A5).
  • GIS Geographic Information System
  • a standard deviation value can be color-coded based on magnitude and visualized on a specific section of road 202 on a road condition map 200.
  • the road condition map 200 can be provided to a client device (Step A6), e.g. a smartphone, a computer monitor or some other visualization device.
  • the road condition map 200 can be used (1) to monitor road erosion of a roadway over time (e.g., see Fig 4, Maps 300, 310, 320), (2) inform municipalities when a road has reached a certain level of road roughness and needs repair, (3) inform municipalities that potholes of a certain size have develop in the roadway and need immediate attention, and (4) predict the development of potholes, sinkholes or breaks in expansion joints.
  • the road condition map can also be used by motorcycle and bicycle enthusiasts so that smooth roads can be mapped for excursions.
  • the road condition map can also be used by insurance companies to evaluate a customer's profile and the road conditions in which the customer typically drives.
  • the central server 140 or the CPU 170 can also be customized to issue a variety of reports, real time alerts regarding a driver's current navigation and routes, e.g., routes that avoid road hazards.
  • the CPU 170 can be located on the vehicle, and can read and record data stream(s) coming from the sensor(s) 150 and the GPS module 110, and can write data to the secondary storage 120.
  • the CPU 170 can also be used to facilitate wireless data upload procedures through an interface with the wireless data module 130.
  • an analog-to-digital converter (“ADC") 160 can be used to convert the analog data to digital data.
  • ADC 160 can also be integrated with the CPU 170. If analog sensors are not being used, the ADC may not be used and can be left out of the systems for the present disclosure.
  • FIG. 5 shows a flow chart for a method that receives, at a computing device, a plurality of data points from one or more data collection unit.
  • Each data point of the plurality of data points can include data related to road conditions for a specific section of road and each data point can be paired with GPS coordinates.
  • the plurality of data points can be analyzed (Step B2) and a road condition score for each data point can be determined. (Step B3).
  • the road condition score for each data point is applied to a mapping module using the GPS coordinates. (Step B4).
  • FIG. 6 is a schematic diagram of an example of a monitoring roadway parameters system 500.
  • the roadway monitoring system 500 includes a data collection server 510, a calculation server 530 and a client device 550.
  • a data collection server 510 receives data from a data collection server 510 and a calculation server 530.
  • a client device 550 receives data from a data collection server 510 and a calculation server 530.
  • the data collection server can be integrated with a client device.
  • the data collection server 510 can include a data collection unit 512, a GPS module 514, a CPU 516, a storage device 518, an input device 520, an interface 522, an operating system 524 and a display 526.
  • the calculation server 530 includes a road parameter database 532, calculation module 534, a processor 536, a storage device 538, an input device 540, an interface 542, an operating system 544 and a display 546.
  • the client device 550 includes a display 552, a map module 554, a processor 556, a storage device 558, an input device 560, an interface 562, an operating system 564 and software 566.
  • the data collection server 510, the calculation server 530 and the device 550 can be connected to one another over an internet connection 570 but more secure connections are contemplated.
  • the system of FIG. 5 can be is split into an environment communicatively connected over the internet 570 with connectors 571, 572, 573 where the one or more servers 510, 530 and devices 550 include hardware as shown in FIG. 5 and also code for providing algorithms used to calculate road roughness data, code for providing mapping functions, code for processing GPS coordinates, and code for interpreting data from the data collection unit.
  • the operating systems 524, 544, 564 can be multi-user, multiprocessing, multitasking, multithreading, real-time and the like.
  • the operating systems 524, 544, 564 may perform basic tasks, including but not limited to: recognizing input from input devices 520, 540, 560; sending output to display devices 526, 546, 552; keeping track of files and directories on computer-readable mediums 518, 538, 558, 532 (e.g., memory or a storage device); controlling peripheral devices (e.g., disk drives, printers, etc.); and managing traffic on the one or more buses 571, 572, 573.
  • peripheral devices e.g., disk drives, printers, etc.
  • sensors and other components of the system according to the present disclosure can be integrated with the vehicle computer system to gain access to vehicle diagnostics and control functions.
  • Various types of sensors can be used for any type of mobile sensing system that utilizes the inherent mobility of a vehicle.
  • the system of the present disclosure can be used by various agencies, such as but not limited to municipalities, public transport systems, taxi cabs, mail/delivery services, insurance companies and/or public or private citizens.
  • a smartphone can be used in lieu of the CPU 170, wireless data module 130, and/or secondary storage 120 if sensor orientation is not an issue for a specific implementation of the present disclosure.
  • Sensors 150 on-board the smartphone can be used or peripheral devices can be used in conjunction with the smartphone.
  • the present disclosure can provide for a lower cost, a higher sampling rate, modularity, simplicity and/or higher accuracy when compared with monitoring systems of the prior art. Rather than relying on an event-based method of road quality monitoring, the present disclosure can upload all data to a central server in unmodified form. Data processing can be performed on the central server, which can free up processing power needs on the vehicle, allowing for the use of lower cost components and higher sensor sampling rates. Because of the modular nature of the design, different types of sensors can be used with the hardware of the present disclosure to monitor various parameters, including road quality.
  • various computing arrangements can be provided, having a processor(s) configured or programmed to perform the steps and/or procedures of the present disclosure described above.
  • Various data described above can be stored in various storage arrangements (e.g., hard drive, memory device, such as RAM, ROM, memory stick, floppy drive, other tangible computer-accessible medium, etc.).
  • the processor(s) can access the storage arrangement(s) to execute a computer program or a set of instructions (stored on or in the storage arrangement) which can perform the procedures according to the methods and systems of the present disclosure.
  • systems and methods disclosed herein may be implemented on various types of computer architectures, such as for example on a single general purpose computer or workstation, or on a network (e.g., local area network, wide area network, or internet), or in a client-server configuration, or in an application service provider configuration.
  • the system's and method's data can be stored as one or more data structures in computer memory and/or storage depending upon the application at hand.
  • the systems and methods may be provided on many different types of computer readable media including instructions being executable by a computer to perform the system and method operations described herein.
  • the systems and methods may also have their information transmitted via data signals embodied on carrier signals (e.g., radio frequency carrier signals) or other communication pathways (e.g., fiber optics, infrared, etc.).
  • a module includes but is not limited to a unit of code that performs a software operation, and can be implemented for example as a subroutine unit of code, or as a software function unit of code, or as an object (as in an object-oriented paradigm), or as an applet, or in a computer script language, or as another type of computer code.
  • the computer components may be located on a single computer or distributed across multiple computers depending upon the situation at hand.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Analytical Chemistry (AREA)
  • Chemical & Material Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Tourism & Hospitality (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Structural Engineering (AREA)
  • Civil Engineering (AREA)
  • Architecture (AREA)
  • Primary Health Care (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biochemistry (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Traffic Control Systems (AREA)
  • Automation & Control Theory (AREA)
  • Development Economics (AREA)
  • Game Theory and Decision Science (AREA)

Abstract

A method and system receives, at a computing device, a plurality of data points from one or more data collection units. Each data point of the plurality of data points can include data related to road conditions for a specific section of road and each data point can be paired with GPS coordinates. The plurality of data points can be analyzed and a road condition score for each data point can be determined. The road condition score for each data point is applied to a mapping module using the GPS coordinates.

Description

METHODS AND SYSTEMS FOR MONITORING ROADWAY PARAMETERS FIELD OF THE DISCLOSURE
[0001] The disclosed technology relates to methods and systems for monitoring road parameters, and more particularly, to methods and systems for monitoring pavement and environmental conditions surrounding vehicles.
BACKGROUND INFORMATION
[0002] Civil infrastructure, construction and maintenance represent a large societal investment. Construction and road maintenance often occurs after damage to the roads and pavement, which can be due to, e.g., traffic and weather. Roadway work zones used for assessment and repair are a major source of traffic congestion, which results in lost productivity and waste. For example, lanes are often closed on highways and bridges for construction or repair, which can lead to major traffic congestion.
[0003] Current methods of road quality monitoring are reactive. Potholes and other road quality issues are usually fixed after they are spotted. Road quality issues are usually found as discoveries by road maintenance crews or through voluntary reports by drivers. Specialized vehicles are also sometimes used, but often these are slow, can cause traffic congestion, and do not provide for a measure of modularity that allows for monitoring of other road parameters besides road quality.
[0004] Thus, there is a need for methods and systems to monitor road and pavement conditions at an early stage so that repair can be provided before major potholes or other damage is caused. Further, there is a need for detecting parameters other than road and/or pavement quality. SUMMARY
[0005] The present disclosure describes methods and systems that can provide for continuous monitoring of road parameters, e.g. the methods and systems can allow for the detection of road quality patterns that indicate future roadway disruptions or allow road maintenance crews to be proactive rather than reactive.
[0006] In one implementation, a computer-implemented method comprises the steps of: receiving, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates; analyzing the plurality of data points; determining a road condition score for each data point; and applying the road condition score for each data point to a mapping module using the GPS coordinates. In some implementations, each data point can be recorded at a regularly-spaced sampling period, e.g., a defined time or a defined distance.
[0007] In other implementations, the road condition score can be a standard deviation value calculated for each data point of the plurality of data points. The standard deviation value can be matched to the GPS coordinates to evaluate and model road roughness for a specific section of road. The standard deviation value for each data point can be visualized using a GIS system. That is, the standard deviation value can be color-coded for a specific section of road on a road condition map. The road condition map can be provided to a client device, e.g., a smartphone, computer display or some other visual display, for personal usage or used by municipalities for road monitoring services.
[0008] In some implementations, the computing device can be integrated with a vehicle computer system or the computing device can be remote from the data collection unit and the computing device receives the plurality of data points over a wireless communication system. [0009] In some implementations, the data collection unit can be a smartphone or an accelerometer. In some implementations, the data collection unit can include a storage module for storing the plurality of data points and the GPS coordinates. In some implementations, the data collection unit can be mounted to a vehicle.
[0010] In another implementation, a system comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: receiving, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates; analyzing the plurality of data points; determining a road condition score for each data point; and applying the road condition score for each data point to a mapping module using the GPS coordinates.
[0011] In some implementations, the road condition score can be a standard deviation value calculated for each data point of the plurality of data points. The standard deviation value can also be matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
[0012] In another implementation, a computer-program product, the product tangibly embodied in a machine-readable storage medium, including instructions configured to cause a data processing apparatus to: receive, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates; analyze the plurality of data points; determine a road condition score for each data point; and apply the road condition score for each data point to a mapping module using the GPS coordinates. In some implementations, the road condition score can be a standard deviation value calculated for each data point of the plurality of data points and the standard deviation value is matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
[0013] The methods and systems according to the present disclosure can allow for real-time assessments of road quality and conditions, air quality, nearby traffic conditions, weather conditions, radiation, noise, vehicle speed/trajectory and/or insolation.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] Figure 1 is a block/flow diagram of a system for monitoring road parameters as disclosed in the specification;
[0015] Figure 2 is a flow chart showing a method for monitoring road parameters as disclosed in the specification;
[0016] Figure 3 is an illustration of a road condition map as disclosed in the specification;
[0017] Figure 4 is illustrations of road condition monitoring maps as disclosed in the specification;
[0018] Figure 5 is a flow chart showing a method for monitoring road parameters as disclosed in the specification; and
[0019] Figure 6 shows a schematic diagram of an example of the disclosed technology.
[0020] Throughout the figures, the same reference numerals and characters, unless otherwise stated, are used to denote like features, elements, components or portions of the illustrated implementations. Moreover, while the subject disclosure will now be described in detail with reference to the figures, it is done so in connection with the illustrative implementations. It is intended that changes and modifications can be made to the described implementations without departing from the true scope and spirit of the subject disclosure. DETAILED DESCRIPTION
[0021] Figure 1 illustrates a block diagram of a system 100 for monitoring road parameters according to the present disclosure. One or more data collection units, e.g., sensors, 150 can be mounted on a vehicle, e.g., cars, trucks, motorcycles, bicycles, or any other mode of transportation used on roads. For example, the sensors 150 can be placed on or installed within the vehicle, e.g., pre-installed by factory during manufacture, or installed by the consumer sometime thereafter.
[0022] If the sensor 150 is an accelerometer, the accelerometer can be located on or nearby a hard mounting point thereby reducing unwanted vibrations. Multiple mounting points, close to the sensor, and/or a thicker PCB also help to reduce the effect of system resonance on the performance of the sensor.
[0023] In one implementation, the sensor can placed on the dashboard of a car with Velcro or the sensor could also be placed on the undercarriage of the car in close proximity to a wheel rim and held in place using a weather-resistant epoxy. In some implementations, a multiplicity of sensors may be used. The sensors 150 can be placed at different locations and mounted using a variety of mounting methods depending on the intended application.
[0024] The various sensors can be used to log road quality parameters, such as but not limited to accelerometers to measure road quality, carbon dioxide sensors to measure air quality, and any other sensor for detection of the road/pavement or the air or traffic surrounding the vehicle.
[0025] In one implementation, if an accelerometer is used, the accelerometer can have a complete 3-axis acceleration measurement system with selectable measurement ranges, e.g., ±2 g, ±4 g, ±8 g, or ±16 g. The accelerometer can measure both dynamic acceleration resulting from motion or shock and static acceleration that allows the device to be used as a tilt sensor. The sensor, for example, can be a polysilicon surface-micromachined structure built on top of a silicon wafer. Polysilicon springs can suspend the structure over the surface of the wafer and provide a resistance against forces due to applied acceleration. Deflection of the structure is measured using differential capacitors that consist of independent fixed plates and plates attached to the moving mass. Acceleration deflects the proof mass and unbalances the differential capacitor, resulting in a sensor output whose amplitude is proportional to acceleration. Phase-sensitive demodulation is used to determine the magnitude and polarity of the acceleration. The accelerometer can also have several special sensing functions, e.g., to sense activity and inactivity, to detect the presence or lack of motion by comparing the acceleration on any axis with pre-defined thresholds, to detect tap sensing and be used to detect single and double taps in any direction, to measure static acceleration of gravity in tilt- sensing applications and dynamic acceleration resulting from motion or shock. The accelerometer can also have a high resolution (3.9 mg/LSB) that enables measurement of inclination changes less than 1.0°.
[0026] In other implementations, other parameters can be measured using different data collection units, such as road quality/conditions, air quality, nearby traffic conditions, weather conditions, radiation, noise, vehicle speed/trajectory and/or insolation, and the present disclosure is not limited to any particular data collection unit.
[0027] In one implementation, as a vehicle is traveling, the sensor(s) 150 can be used to obtain road pavement parameter data at a pre-determined sampling rate. The sampling rate can be measured in time or distance. For example, the sampling rate can take measurements every 0.2 seconds or every 50 feet, it is understood that other sampling rates are contemplated. The sampling rate can be dependent on, e.g., the rate of speed the car is traveling and the dynamics of the road, e.g., curves, straight, etc.
[0028] The data obtained by sensors 150 can be paired with a GPS Module 110 in a CPU 170 and the combination can be stored in a secondary storage module 120, such as but not limited to a vehicle computer, an SD card, or other type of memory. The secondary storage 120 can be separate from the computer processing unit ("CPU") 170. For example, a MicroSD card can be connected to the CPU 170 using an SPI interface. However, secondary storage 120 can be integrated with the CPU 170 if non- volatile memory present on-board the CPU 170 is large and fast enough.
[0029] A wireless data module 130, such as but not limited to a cellular, WiFi, or other wireless data communication protocol, can be provided where recorded data from the sensors 150 and/or secondary storage 120 can be uploaded to a central server 140 for analysis. This can be done when the vehicle is parked and no data is being logged (e.g., to conserve processing resources). This can also be done in real time, at a time preset by the user or manually by the user.
[0030] As shown in Figure 2, the central server 140 can receive a plurality of data points from at least one data collection unit 150. (Step Al). The central server 140 can be partially integrated with a vehicle computer system or the central server 140 can be independent and remote from the data collection unit 150 and receive the plurality of data points over a wireless communication system 130. Each data point of the plurality of data points can include data related to road conditions for a specific section of road. These data points can be paired with GPS coordinates. (Step A2). The central server 140 analyzes the plurality of data points and determines a road condition score for each data point. (Step A3). The road condition score can be, e.g., a standard deviation value calculated for each data point of the plurality of data points. In some implementations, road condition scores from multiple vehicles can be averaged to gain more accurate road condition scores. The road condition scores are matched to the GPS coordinates (Step A4) and can be used to evaluate road roughness for specific sections of roads, (e.g., a number of samples (e.g., 320 samples equating to approximately 1 mile of road) can be collected for a particular section of road; these samples are analyzed as a group and standard deviation values are tabulated for each sample within the group). The road condition score for each data point can be visualized on a map using a Geographic Information System (GIS) associated with the central server 140. (Step A5).
[0031] As shown in Figure 3, a standard deviation value can be color-coded based on magnitude and visualized on a specific section of road 202 on a road condition map 200. The road condition map 200 can be provided to a client device (Step A6), e.g. a smartphone, a computer monitor or some other visualization device.
[0032] The road condition map 200 can be used (1) to monitor road erosion of a roadway over time (e.g., see Fig 4, Maps 300, 310, 320), (2) inform municipalities when a road has reached a certain level of road roughness and needs repair, (3) inform municipalities that potholes of a certain size have develop in the roadway and need immediate attention, and (4) predict the development of potholes, sinkholes or breaks in expansion joints. The road condition map can also be used by motorcycle and bicycle enthusiasts so that smooth roads can be mapped for excursions. The road condition map can also be used by insurance companies to evaluate a customer's profile and the road conditions in which the customer typically drives. The central server 140 or the CPU 170 can also be customized to issue a variety of reports, real time alerts regarding a driver's current navigation and routes, e.g., routes that avoid road hazards.
[0033] In some implementations, the CPU 170 can be located on the vehicle, and can read and record data stream(s) coming from the sensor(s) 150 and the GPS module 110, and can write data to the secondary storage 120. The CPU 170 can also be used to facilitate wireless data upload procedures through an interface with the wireless data module 130.
[0034] If the sensors 150 contain an analog sensor, an analog-to-digital converter ("ADC") 160 can be used to convert the analog data to digital data. Different analog sensors can operate at a variety of voltages, so that a reference voltage can be given to the ADC 160 so it can map data properly according to the operating voltage of the sensor. The ADC 160 can also be integrated with the CPU 170. If analog sensors are not being used, the ADC may not be used and can be left out of the systems for the present disclosure.
[0035] Figure 5 shows a flow chart for a method that receives, at a computing device, a plurality of data points from one or more data collection unit. (Step Bl). Each data point of the plurality of data points can include data related to road conditions for a specific section of road and each data point can be paired with GPS coordinates. The plurality of data points can be analyzed (Step B2) and a road condition score for each data point can be determined. (Step B3). The road condition score for each data point is applied to a mapping module using the GPS coordinates. (Step B4).
[0036] Figure 6 is a schematic diagram of an example of a monitoring roadway parameters system 500. The roadway monitoring system 500 includes a data collection server 510, a calculation server 530 and a client device 550. For ease of explanation only one of each device is shown but more than one of each is contemplated and combinations devices are also contemplated, e.g., the data collection server can be integrated with a client device.
[0037] The data collection server 510 can include a data collection unit 512, a GPS module 514, a CPU 516, a storage device 518, an input device 520, an interface 522, an operating system 524 and a display 526.
[0038] The calculation server 530 includes a road parameter database 532, calculation module 534, a processor 536, a storage device 538, an input device 540, an interface 542, an operating system 544 and a display 546.
[0039] The client device 550 includes a display 552, a map module 554, a processor 556, a storage device 558, an input device 560, an interface 562, an operating system 564 and software 566. [0040] The data collection server 510, the calculation server 530 and the device 550 can be connected to one another over an internet connection 570 but more secure connections are contemplated.
[0041] In some implementations, the system of FIG. 5 can be is split into an environment communicatively connected over the internet 570 with connectors 571, 572, 573 where the one or more servers 510, 530 and devices 550 include hardware as shown in FIG. 5 and also code for providing algorithms used to calculate road roughness data, code for providing mapping functions, code for processing GPS coordinates, and code for interpreting data from the data collection unit.
[0042] The operating systems 524, 544, 564 can be multi-user, multiprocessing, multitasking, multithreading, real-time and the like. The operating systems 524, 544, 564 may perform basic tasks, including but not limited to: recognizing input from input devices 520, 540, 560; sending output to display devices 526, 546, 552; keeping track of files and directories on computer-readable mediums 518, 538, 558, 532 (e.g., memory or a storage device); controlling peripheral devices (e.g., disk drives, printers, etc.); and managing traffic on the one or more buses 571, 572, 573.
[0043] Various other considerations and modifications can be provided. For example, various microcontrollers, GPS units, storage devices, wireless communication modules, and user interface (UI) controls can be used, all of which can be enabled through software modification. The sensors and other components of the system according to the present disclosure can be integrated with the vehicle computer system to gain access to vehicle diagnostics and control functions. Various types of sensors can be used for any type of mobile sensing system that utilizes the inherent mobility of a vehicle. The system of the present disclosure can be used by various agencies, such as but not limited to municipalities, public transport systems, taxi cabs, mail/delivery services, insurance companies and/or public or private citizens.
[0044] Further, a smartphone can be used in lieu of the CPU 170, wireless data module 130, and/or secondary storage 120 if sensor orientation is not an issue for a specific implementation of the present disclosure. Sensors 150 on-board the smartphone can be used or peripheral devices can be used in conjunction with the smartphone.
[0045] The present disclosure can provide for a lower cost, a higher sampling rate, modularity, simplicity and/or higher accuracy when compared with monitoring systems of the prior art. Rather than relying on an event-based method of road quality monitoring, the present disclosure can upload all data to a central server in unmodified form. Data processing can be performed on the central server, which can free up processing power needs on the vehicle, allowing for the use of lower cost components and higher sensor sampling rates. Because of the modular nature of the design, different types of sensors can be used with the hardware of the present disclosure to monitor various parameters, including road quality.
[0046] Various other considerations can also be addressed in the exemplary applications described. For example, various computing arrangements can be provided, having a processor(s) configured or programmed to perform the steps and/or procedures of the present disclosure described above. Various data described above can be stored in various storage arrangements (e.g., hard drive, memory device, such as RAM, ROM, memory stick, floppy drive, other tangible computer-accessible medium, etc.). The processor(s) can access the storage arrangement(s) to execute a computer program or a set of instructions (stored on or in the storage arrangement) which can perform the procedures according to the methods and systems of the present disclosure.
[0047] It is noted that the systems and methods disclosed herein may be implemented on various types of computer architectures, such as for example on a single general purpose computer or workstation, or on a network (e.g., local area network, wide area network, or internet), or in a client-server configuration, or in an application service provider configuration. Also, the system's and method's data can be stored as one or more data structures in computer memory and/or storage depending upon the application at hand. The systems and methods may be provided on many different types of computer readable media including instructions being executable by a computer to perform the system and method operations described herein. The systems and methods may also have their information transmitted via data signals embodied on carrier signals (e.g., radio frequency carrier signals) or other communication pathways (e.g., fiber optics, infrared, etc.).
[0048] The computer components, software modules, functions and data structures described herein may be connected directly or indirectly to each other in order to allow the flow of data needed for their operations. It is also noted that a module includes but is not limited to a unit of code that performs a software operation, and can be implemented for example as a subroutine unit of code, or as a software function unit of code, or as an object (as in an object-oriented paradigm), or as an applet, or in a computer script language, or as another type of computer code. The computer components may be located on a single computer or distributed across multiple computers depending upon the situation at hand.
[0049] The foregoing Detailed Description is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the invention disclosed herein is not to be determined from the Detailed Description, but rather from the claims as interpreted according to the full breadth permitted by the patent laws. It is to be understood that the implementations shown and described herein are only illustrative of the principles of the present invention and that various modifications may be implemented by those skilled in the art without departing from the scope and spirit of the invention. Those skilled in the art could implement various other feature combinations without departing from the scope and spirit of the invention.

Claims

IN THE CLAIMS
1. A computer-implemented method comprising the steps of:
receiving, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates;
analyzing the plurality of data points;
determining a road condition score for each data point; and
applying the road condition score for each data point to a mapping module using the GPS coordinates.
2. The computer-implemented method of Claim 1 wherein each data point is recorded at a regularly-spaced sampling period.
3. The computer-implemented method of Claim 2 wherein the regularly-spaced sampling period is a defined time.
4. The computer-implemented method of Claim 2 wherein the regularly-spaced sampling period is a defined distance.
5. The computer-implemented method of Claim 1 wherein the road condition score is a standard deviation value calculated for each data point of the plurality of data points.
6. The computer-implemented method of Claim 5 wherein the standard deviation value is matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
7. The computer-implemented method of Claim 6 wherein the standard deviation value for each data point is visualized in a GIS system.
8. The computer-implemented method of Claim 7 wherein the standard deviation value is color-coded for the specific section of road on a road condition map.
9. The computer-implemented method of Claim 8 further comprising the step of: providing the road condition map to a client device.
10. The computer-implemented method of Claim 1 wherein the computing device is partially integrated with a vehicle computer system.
11. The computer-implemented method of Claim 1 wherein the computing device is remote from the data collection unit and the computing device receives the plurality of data points over a wireless communication system.
12. The computer-implemented method of Claim 1 wherein the at least one data collection unit is a smartphone.
13. The computer-implemented method of Claim 1 wherein the at least one data collection unit is an accelerometer.
14. The computer-implemented method of Claim 1 wherein the at least one data collection unit includes a storage module for storing the plurality of data points and the GPS coordinates.
15. The computer-implemented method of Claim 1 wherein the at least one data collection unit is mounted to a vehicle.
16. A system comprising :
one or more processors;
one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including:
receiving, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates;
analyzing the plurality of data points;
determining a road condition score for each data point; and
applying the road condition score for each data point to a mapping module using the GPS coordinates.
17. The system of claim 16 wherein the road condition score is a standard deviation value calculated for each data point of the plurality of data points.
18. The system of claim 17 wherein the standard deviation value is matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
19. A computer-program product, the product tangibly embodied in a machine -readable storage medium, including instructions configured to cause a data processing apparatus to: receive, at a computing device, a plurality of data points from at least one data collection unit, each data point including data related to road conditions for a specific section of road, and each data point being paired with GPS coordinates;
analyze the plurality of data points;
determine a road condition score for each data point; and
apply the road condition score for each data point to a mapping module using the GPS coordinates.
20. The computer-program product of claim 15 wherein the road condition score is a standard deviation value calculated for each data point of the plurality of data points and the standard deviation value is matched to the GPS coordinates to evaluate and model road roughness for the specific section of road specific.
PCT/US2014/036203 2013-04-30 2014-04-30 Methods and systems for monitoring roadway parameters WO2014179481A1 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
KR1020157034177A KR20160021430A (en) 2013-04-30 2014-04-30 Methods and systems for monitoring roadway parameters
EP14791306.5A EP2992425A4 (en) 2013-04-30 2014-04-30 Methods and systems for monitoring roadway parameters
US14/888,052 US9869630B2 (en) 2013-04-30 2014-04-30 Methods and systems for monitoring roadway parameters

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201361817357P 2013-04-30 2013-04-30
US61/817,357 2013-04-30

Publications (1)

Publication Number Publication Date
WO2014179481A1 true WO2014179481A1 (en) 2014-11-06

Family

ID=51843930

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2014/036203 WO2014179481A1 (en) 2013-04-30 2014-04-30 Methods and systems for monitoring roadway parameters

Country Status (4)

Country Link
US (1) US9869630B2 (en)
EP (1) EP2992425A4 (en)
KR (1) KR20160021430A (en)
WO (1) WO2014179481A1 (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016179233A1 (en) * 2015-05-04 2016-11-10 Joy Mm Delaware, Inc. Systems and methods for evaluating underground road conditions using accelerometers
CN109154498A (en) * 2016-02-22 2019-01-04 追踪器连接私人有限公司 Road monitoring method and system

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11346677B2 (en) * 2017-12-04 2022-05-31 University Of Massachusetts Method to measure road roughness characteristics and pavement induced vehicle fuel consumption
US20200023846A1 (en) * 2018-07-23 2020-01-23 SparkCognition, Inc. Artificial intelligence-based systems and methods for vehicle operation
KR102074999B1 (en) * 2019-02-19 2020-02-10 포항공과대학교 산학협력단 System and method of measuring pedestrain environment data being based on block chain and computer readable medium
JP7344583B2 (en) * 2021-06-24 2023-09-14 株式会社リガク Information processing device, information processing method and program

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070008090A1 (en) * 2003-06-04 2007-01-11 Daimlerchrysler Ag Curve rollover warning system for trucks
US20110052042A1 (en) * 2009-08-26 2011-03-03 Ben Tzvi Jacob Projecting location based elements over a heads up display
US20130016106A1 (en) * 2011-07-15 2013-01-17 Green Charge Networks Llc Cluster mapping to highlight areas of electrical congestion

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5880362A (en) * 1995-09-06 1999-03-09 Engineering Technology Associates, Inc. Method and system for simulating vehicle and roadway interaction
JP4076740B2 (en) * 2001-06-22 2008-04-16 住友ゴム工業株式会社 Road surface gradient determination apparatus and method, and gradient determination program
DE602004028568D1 (en) 2004-02-20 2010-09-23 Harman Becker Automotive Sys Apparatus and method for generating environmental parameters and for determining weather information
US7430141B2 (en) 2004-11-16 2008-09-30 Texas Instruments Incorporated Method and apparatus for memory data deskewing
US7554440B2 (en) 2006-07-25 2009-06-30 United Parcel Service Of America, Inc. Systems and methods for monitoring travel conditions
US20100271191A1 (en) * 2008-10-07 2010-10-28 De Graff Bassel Systems, devices, and methods utilizing stretchable electronics to measure tire or road surface conditions
US8260496B2 (en) * 2009-06-18 2012-09-04 Honda Motor Co., Ltd. Adaptive active suspension and aware vehicle network system and method
US8320282B2 (en) 2009-07-30 2012-11-27 Calix, Inc. Automatic control node selection in ring networks
US9108640B2 (en) 2012-01-31 2015-08-18 Google Inc. Systems and methods for monitoring and reporting road quality
JP5613195B2 (en) * 2012-04-11 2014-10-22 住友ゴム工業株式会社 Tire simulation method
JP5937921B2 (en) * 2012-08-09 2016-06-22 株式会社ブリヂストン Road surface condition determination method and apparatus
CA2888335A1 (en) * 2012-10-19 2014-04-24 Roadroid Ab Method and system for monitoring road conditions
US9448073B2 (en) 2013-06-10 2016-09-20 Google Inc. System and method for assessing road quality using data collected from a mobile device
US9751533B2 (en) * 2014-04-03 2017-09-05 The Goodyear Tire & Rubber Company Road surface friction and surface type estimation system and method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070008090A1 (en) * 2003-06-04 2007-01-11 Daimlerchrysler Ag Curve rollover warning system for trucks
US20110052042A1 (en) * 2009-08-26 2011-03-03 Ben Tzvi Jacob Projecting location based elements over a heads up display
US20130016106A1 (en) * 2011-07-15 2013-01-17 Green Charge Networks Llc Cluster mapping to highlight areas of electrical congestion

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP2992425A4 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016179233A1 (en) * 2015-05-04 2016-11-10 Joy Mm Delaware, Inc. Systems and methods for evaluating underground road conditions using accelerometers
CN107735689A (en) * 2015-05-04 2018-02-23 乔伊·姆·特拉华公司 Use the system and method for accelerometer evaluation of subterranean condition of road surface
GB2554825A (en) * 2015-05-04 2018-04-11 Joy Mm Delaware Inc Systems and methods for evaluating underground road conditions using accelerometers
RU2713168C2 (en) * 2015-05-04 2020-02-04 ДЖОЙ ГЛОБАЛ АНДЕРГРАУНД МАЙНИНГ ЭлЭлСи Systems and methods for estimating underground road conditions using accelerometers
GB2554825B (en) * 2015-05-04 2020-12-23 Joy Global Underground Mining Llc Systems and methods for evaluating underground road conditions using accelerometers
CN109154498A (en) * 2016-02-22 2019-01-04 追踪器连接私人有限公司 Road monitoring method and system
US11054256B2 (en) 2016-02-22 2021-07-06 Tracker Connect (Pty) Limited Road monitoring method and system
EP3420308B1 (en) * 2016-02-22 2022-02-16 Tracker Connect (PTY) Limited Road monitoring method and system
EP4008994A1 (en) * 2016-02-22 2022-06-08 Tracker Connect (PTY) Limited Road monitoring method and system

Also Published As

Publication number Publication date
US20160076991A1 (en) 2016-03-17
KR20160021430A (en) 2016-02-25
US9869630B2 (en) 2018-01-16
EP2992425A1 (en) 2016-03-09
EP2992425A4 (en) 2016-11-16

Similar Documents

Publication Publication Date Title
US9869630B2 (en) Methods and systems for monitoring roadway parameters
Islam et al. Measurement of pavement roughness using android-based smartphone application
US10782138B2 (en) Method, apparatus, and computer program product for pedestrian behavior profile generation
Alessandroni et al. Smartroadsense: Collaborative road surface condition monitoring
EP3064901B1 (en) Turn lane configuration
CN104164829B (en) Detection method of road-surface evenness and intelligent information of road surface real-time monitoring system based on mobile terminal
CN101907714B (en) GPS aided positioning system and method based on multi-sensor data fusion
US11782129B2 (en) Automatic detection of overhead obstructions
Janani et al. Influence of surface distresses on smartphone-based pavement roughness evaluation
US9983093B2 (en) Assessing the road quality of one or more road segments in a road network
Masino et al. Learning from the crowd: Road infrastructure monitoring system
US10096173B2 (en) Parking payment detection
US20170075036A1 (en) Weather condition information based on magnetometers
US20220057218A1 (en) Method and apparatus for automatic generation of context-based guidance information from behavior and context-based machine learning models
CN102509493B (en) Monitoring system for automobile driver road test evaluation
Mandal et al. City traffic speed characterization based on city road surface quality
BR102012007325A2 (en) DRIVER PROPENSION ANALYSIS AND DRIVER PROPENSION ANALYSIS METHOD USING THE APPLIANCE
JP2016191592A (en) Road surface smoothness evaluation method
Botshekan et al. Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory
Shen et al. Data Collection and Processing Methods for the Evaluation of Vehicle Road Departure Detection Systems
Zhao et al. IRI measurement using dynamic tire pressure sensor with an axle accelerometer
Limkar et al. Small effort to build Pune as a smart city: Smart real-time road condition detection and efficient management system
Kortmann et al. Creating value from in-vehicle data: Detecting road surfaces and road hazards
Arce-Sáenz et al. Road surface data acquisition system with fog computing v2i networks in smart cities
US20230100346A1 (en) Method, apparatus, and system for detecting and characterizing parking events based on sensor data

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14791306

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

WWE Wipo information: entry into national phase

Ref document number: 2014791306

Country of ref document: EP

ENP Entry into the national phase

Ref document number: 20157034177

Country of ref document: KR

Kind code of ref document: A