NETWORK COMPUTER SYSTEM FOR ANALYZING DRIVING ACTIONS OF DRIVERS ON ROAD SEGMENTS OF A GEOGRAPHIC REGION

• US 20170236411A1
• Filed: 12/16/2016
• Published: 08/17/2017
• Est. Priority Date: 02/17/2016
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Sumers, Theodore Russell
• Granted Patent: US 10,297,148 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2520/125 Lateral acceleration
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/06 Road conditions
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G06F 18/2433 Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
• CPC Class Codes: G06F 18/256 of results relating to different input data, e.g. multimodal recognition
• CPC Class Codes: G06F 3/016 Input arrangements with force or tactile feedback as computer generated output to the user
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information

Abstract

Examples include a network computer system and/or service which operates to remotely monitor vehicles to detect and characterize driving actions of drivers with respect to specific road segments of a roadway.

Claims

1. A method for analyzing driving behavior of a population on road segments of a geographic region, the method being performed by one or more processors and comprising:

receiving, over one or more networks, vehicle data from each of multiple vehicles that individually traverse a given road segment of a geographic region, the vehicle data of each of the multiple vehicles being indicative of attributes of that vehicle'"'"'s motion while the vehicle is traversing the given road segment;

for each of the multiple vehicles, determining, from the vehicle data of that vehicle, a characterization of at least one driving action performed using that vehicle at the given road segment;

aggregating the characterizations determined for each of the multiple vehicles; and

determining, for the given road segment, a baseline or model of the characterization for the at least one driving action based at least in part on the aggregated characterizations.

2. The method of claim 1, further comprising evaluating individual drivers by comparing vehicle data, obtained from individual drivers traversing the given road segment, to the baseline or model of the characterization.

3. The method of claim 1, further comprising validating vehicle data transmitted from the vehicles of individual drivers by comparing the vehicle data to the baseline or model.

4. The method of claim 1, wherein the characterization of at least one driving action includes a numerical categorization.

5. The method of claim 1, wherein the baseline or model is based on a statistical distribution.

6. The method of claim 1, further comprising:

communicating information corresponding to the baseline or model of the characterization to a group of drivers within the geographic region.

7. The method of claim 1, further comprising:

determining, from the baseline or model, one or more road segments of the geographic region which include a road hazard.

8. The method of claim 6, further comprising:

obtaining contextual information in conjunction with vehicle data that is received from each of the multiple vehicles; and

wherein determining the characterization of the baseline includes determining the characterization of the baseline based at least in part on a context identified from the contextual information.

9. The method of claim 8, wherein the identified context includes one or more of:

time of day, day of week, month of year, weather condition, temporary road condition, or a public event in the geographic region.

10. The method of claim 9, wherein the baseline of the characterization is specific to the identified context.

11. The method of claim 1, wherein the vehicle data includes vehicle state information determined from a motion measuring component that resides within each of the vehicles.

12. The method of claim 11, wherein the motion measuring component of at least one of the multiple vehicles includes at least one of an accelerometer or inertial measurement unit (“

IMU”

) that is provided within a mobile computing device of a driver of that vehicle.

13. The method of claim 1, wherein receiving the vehicle data includes receiving multiple types of vehicle state information from the multiple vehicles, each type of vehicle state information corresponding to one of Global Positioning System (“

GPS”

) data, accelerometer data, gyroscopic data, or inertial measurement unit (“

IMU”

) data.

14. The method of claim 13, wherein determining the characterization of at least one driving action includes determining a magnitude of an acceleration action performed by the driver.

15. The method of claim 14, wherein the acceleration action corresponds to a braking action or a steering action of the driver.

16. The method of claim 1, wherein the acceleration action corresponds to a pedal action of the driver.

17. The method of claim 1, further comprising:

evaluating a driving performance of a driver of each of the multiple vehicles based at least in part on a comparison of the characterization of the driving action that is determined for the vehicle of that driver and the baseline of the characterization.

18. The method of claim 1, wherein determining the characterization of the at least one driving action includes:

(a) communicating with a mobile computing device of a driver of each of the multiple vehicles to obtain vehicle state information;

(b) determining a characterization of each of multiple driving actions performed by the driver of each of the multiple vehicles;

(c) correlating at least one of the multiple driving actions performed by the driver of each of the multiple vehicles to one of a plurality of road segments for the geographic region.

19. A computer system comprising:

a network computer system; and

a plurality of service applications which individually execute on a computing device that is carried within a vehicle, each service application of the plurality of service applications being under programmatic control of the network computer system to (i) interface and obtain vehicle data from one or more components on the computing device or accessible to the computing device within the vehicle, and (ii) transmit the vehicle data to the network computer system over one or more networks;

wherein the network computer system includes one or more processors and a memory to store instructions, the instructions causing the one or more processors to;

receive, over one or more networks, vehicle data from each of multiple vehicles that individually traverse a given road segment of a geographic region, the vehicle data of each of the multiple vehicles being indicative of attributes of that vehicle'"'"'s motion while the vehicle is traversing the given road segment;

for each of the multiple vehicles, determine, from the vehicle data of that vehicle, a characterization of at least one driving action performed using that vehicle at the given road segment;

aggregate the characterizations determined for each of the multiple vehicles; and

determine, for the given road segment, a baseline or model of the characterization for the at least one driving action based at least in part on the aggregated characterizations.

20. A non-transitory computer-readable medium that stores instructions, which when executed by one or more processors, cause a computing system of the one or more processors to perform operations that include:

receiving, over one or more networks, vehicle data from each of multiple vehicles that individually traverse a given road segment of a geographic region, the vehicle data of each of the multiple vehicles being indicative of attributes of that vehicle'"'"'s motion while the vehicle is traversing the given road segment;

for each of the multiple vehicles, determining, from the vehicle data of that vehicle, a characterization of at least one driving action performed using that vehicle at the given road segment;

aggregate the characterizations determined for each of the multiple vehicles; and

determine, for the given road segment, a baseline or model of the characterization for the at least one driving action based at least in part on the aggregated characterizations.