Systems and methods for building road models, driver models, and vehicle models and making predictions therefrom

• US 9,165,477 B2
• Filed: 12/08/2014
• Issued: 10/20/2015
• Est. Priority Date: 12/06/2013
• Status: Expired due to Fees

• Current Assignee: Exodus Navigation Systems, Inc.
• Original Assignee: Vehicle Data Science Corporation
• Inventors: Wilson, Christopher Kenneth
• Primary Examiner(s): ARTHUR JEANGLAUD, GERTRUDE
• Application Number:
  US14/563,664
• Publication Number:
  US 20150266455A1
• Time in Patent Office: 316 Days
• Field of Search: 701/93, 701/96, 701/117, 701/400, 701/468, 701/409, 701/538, 701/451, 340/988, 340/990, 340/438, 340/439, 340/905, 340/995.1
• US Class Current: 1/1
• CPC Class Codes: B60W 10/18 including control of braking systems
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 10/30 including control of auxiliary equipment, e.g. air-conditioning compressors or oil pumps
• CPC Class Codes: B60W 30/10 Path keeping cruise control for automatically following a preceding vehicle B60W30/165
• CPC Class Codes: B60W 50/12 Limiting control by the driver depending on vehicle state, e.g. interlocking means for the control input for preventing unsafe operation
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G01C 21/3697 Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence
• CPC Class Codes: G01C 21/3815 Road data
• CPC Class Codes: G01C 21/3841 Data obtained from two or more sources, e.g. probe vehicles
• CPC Class Codes: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa
• CPC Class Codes: G05D 1/0276 using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0137 for specific applications
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/20 Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• CPC Class Codes: G09B 19/10 Modelling
• CPC Class Codes: G09B 25/00 Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes model vehicles, tracks therefor, models in the nature of toys A63H

Abstract

Systems and methods for building road models, driver models, and vehicle models and making predictions may use driving data received from a plurality of vehicles being driving along a path by a driver. The driving data including a minimum of vehicle location preferably supplemented by data related to the time of observations, vehicle dynamics, and various vehicle sensors. The received data may be categorized into a plurality of maneuvers and a plurality of variables that describe the maneuvers and the received driving data may be identified. A road model may then be built for the path based on the identified variables and maneuvers and the behaviors of a particular driver compared to the road model to assess their driving and intervene as appropriate.

Claims

1. A computer implemented method comprising:

receiving driving data from a plurality of vehicles being driving along a path, each of the vehicles of the plurality being driven by a driver, the driving data including vehicle location information;

categorizing the data into a plurality of maneuvers;

identifying a plurality of variables that describe the maneuvers and the received driving data;

building a road model for the path based on the identified variables and maneuvers, the road model including a set of reference trajectories for a subsequent vehicle being driven at an identical or similar location along the path;

receiving driving data from a vehicle separate from the plurality of vehicles as it is being driven on the path by its respective driver;

determining one or more characteristics of the driver of the plurality of drivers using the driving data received from the vehicle;

comparing the characteristics of the driver to the road model to determine driver behavior;

determining whether driver behavior is consistent with the road model; and

executing an action in the vehicle responsively to the determination of whether the driver behavior is consistent with the road model, the action being at least one of providing a message to the driver and automatically adjusting an operation of the vehicle as it is driven.

2. The computer implemented method of claim 1, further comprising:

building a driver model for the driver using the driver behavior;

receiving driver data from a third party; and

updating the driver model to include the driver data received from the third party.

3. The computer implemented method of claim 1, further comprising:

building a driver model for the driver using the driver behavior;

receiving demographic data about the driver; and

segmenting the driver model based on the received demographic data.

4. The computer implemented method of claim 1, further comprising:

building a driver model for the driver using the driver behavior;

comparing the driver behavior with the driver model;

determining whether the driver behavior is consistent with the driver model; and

updating the execution of the action in the vehicle responsively to the determination of whether the driver behavior is consistent with the driver model.

5. The computer implemented method of claim 1, wherein the road model includes maneuvers, stopping locations, and actions to be performed upon approaching a stopping location.

6. The computer implemented method of claim 1, wherein the action to be performed is at least one of decreasing the speed of the vehicle, determining a location at which to begin decreasing the speed of the vehicle, and determining a location at which to come to a stop.

7. The computer implemented method of claim 1, further comprising:

determining one or more characteristics of a vehicle of the plurality of vehicles driven by the driver based on the driving data received from the vehicle;

comparing the characteristics of the vehicle to the road model to determine vehicle behavior; and

building a vehicle model for the vehicle responsive to the comparison of the characteristics of the vehicle to the road model.

8. The computer implemented method of claim 1, further comprising:

dynamically updating the road model based on conditions present on the path.

9. The computer implemented method of claim 1, further comprising:

determining one or more characteristics of a vehicle of the plurality of vehicles driven by the driver based on the driving data received from the vehicle;

comparing the characteristics of the vehicle to the road model to determine vehicle behavior;

building a vehicle model for the vehicle using the vehicle behavior;

comparing the vehicle behavior with the driver model and the road model;

determining whether the vehicle behavior is consistent with the driver model and the road model; and

updating the execution of the action in the vehicle responsively to the determination of whether the driver behavior is consistent with the driver model and the road model.

10. The computer implemented method of claim 1, further comprising:

predicting how the vehicle will be driven along the path based on at least one of the road model and the driver behavior; and

updating the execution of the action in the vehicle responsively to the prediction.

11. The computer implemented method of claim 1, wherein adjusting the operation of the vehicle as it is driven includes at least one of braking, continued application of cruise control, removal of cruise control, redirecting a trajectory of the vehicle, accelerating the vehicle, modifying an operation of sensor systems resident in the vehicle, modifying an operation of actuator systems resident in the vehicle, modifying a setting of the vehicles suspension apparatus, adjusting an operation of headlights resident in the vehicle, adjusting an operation of turn indicators, and adjusting a configuration of one or more components of the vehicle'"'"'s powertrain.

12. The computer implemented method of claim 1, wherein adjusting the operation of the vehicle as it is driven is responsive to at least one of the road model, the characteristics of the driver, driver behavior, and a driver preference.

13. The computer implemented method of claim 1, further comprising:

selecting a driver model from a plurality of previously generated driver models using at least one of a characteristic of the driver driving the vehicle and the driver behavior;

comparing the characteristics of the driver to the selected driver model to determine driver behavior;

determining whether driver behavior is consistent with the driver model; and

executing a predetermined action in the vehicle responsively to the determination, the predetermined action being at least one of providing a message to the driver and automatically adjusting the operation of the vehicle as it is driven.

14. The computer implemented method of claim 1, wherein a plurality of road models for the path have been generated, the method further comprising:

selecting a road model of the plurality of road models prior to the comparison of the driver to the road model to determine driver behavior; and

comparing the characteristics of the driver to the selected road model to determine driver behavior.

15. The computer implemented method of claim 1, wherein the road model is selected responsively to a driver characteristic, the driver behavior, a vehicle characteristic, an environmental condition associated with the path, and a traffic congestion characteristic of the path.

16. The computer implemented method of claim 1, wherein the driving data received from the vehicle separate from the plurality further includes an indication of a driving condition along the path, the method further comprising:

determining whether driving condition is consistent with the road model, wherein the executed action is responsive the determination of whether driving condition is consistent with the road model.

17. A computer implemented method comprising:

selecting a driver model from a plurality of driver models based on a characteristic of a driver driving a vehicle along a path;

receiving driving data from the vehicle as it is being driven on the path;

selecting a road model for the path based on a characteristic of at least one of the path, a driver of the vehicle, and an environmental condition present along the path;

comparing the received driving data to the driver model and the road model to determine driver behavior;

determining whether driver behavior is consistent with the driver model and the road model; and

executing an action in the vehicle responsively to the determination, the action being at least one of providing a message to the driver and automatically adjusting an operation of the vehicle as it is driven.

18. The computer implemented method of claim 17, further comprising:

comparing the characteristic of the driver to characteristics of the plurality of driver models prior to the selection of the driver model, where selection of the driver model is responsive to the comparison.

19. A computer implemented method comprising:

selecting a vehicle model from a plurality of vehicle models based on a characteristic of a driver driving a vehicle;

receiving driving data from the vehicle as it is being driven on a path by the driver;

selecting a road model for the path based on a characteristic of at least one the path, a driver of the vehicle, and an environmental condition present along the path;

comparing the received driving data to the vehicle model and the road model to determine vehicle behavior;

determining whether vehicle behavior is consistent with the vehicle model and the road model; and

executing an action in the vehicle responsively to the determination, the action being at least one of providing a message to the driver and automatically adjusting an operation of the vehicle as it is driven.

20. The computer implemented method of claim 19, further comprising:

comparing the characteristic of the vehicle to characteristics of the plurality of vehicle models prior to the selection of the vehicle model, where selection of the vehicle model is responsive to the comparison.