Determination of roadway features

• US 10,782,704 B2
• Filed: 01/30/2018
• Issued: 09/22/2020
• Est. Priority Date: 01/30/2017
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Motor Engineering & Manufacturing North America Incorporated (Toyota Motor Corporation)
• Inventors: Vladimerou, Vladimeros, Johnson, Miles J., Bansal, Guarav, Sakr, Ahmed
• Primary Examiner(s): Chen, Shelley
• Application Number:
  US15/883,675
• Publication Number:
  US 20180217612A1
• Time in Patent Office: 966 Days
• Field of Search: None
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G01C 21/3819 Road shape data, e.g. outline of a route
• CPC Class Codes: G01C 21/3822 Road feature data, e.g. slope data
• CPC Class Codes: G01C 21/3848 Data obtained from both position sensors and additional sensors
• 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: 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 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/096811 where the route is computed offboard
• CPC Class Codes: G08G 1/096844 where the complete route is dynamically recomputed based on new data

Abstract

One or more roadway features can be determined based on information received from one or more vehicles traveling on a roadway. A data packet can be received from a remote vehicle. The data packet can include data corresponding to locations and headings of the remote vehicle. A path history for the remote vehicle can be determined based on the data packet. The path history can include data points corresponding to a plurality of locations and headings for the remote vehicle. A geometry for a portion of the roadway preceding the remote vehicle can be determined using the path history. The determined geometry of the roadway can be used to determine a driving maneuver for a vehicle and/or to verify a map.

Claims

1. A method of determining one or more features of a roadway, the method comprising:

receiving a data packet from a remote vehicle, the data packet including data corresponding to a first location and a first heading of the remote vehicle;

based on the data packet received from the remote vehicle, determining, using one or more processors, a path history for the remote vehicle, the path history including data points corresponding to a plurality of locations and headings including the first location and the first heading and one or more previous locations and previous headings of the remote vehicle; and

determining, using one or more processors, a geometry for a portion of the roadway preceding the remote vehicle based on the determined path history.

2. The method in claim 1, wherein determining the geometry comprises:

using the path history for the remote vehicle and data corresponding to the remote vehicle and acquired by one or more sensors, determining, using one or more processors, the geometry for the portion of the roadway preceding the remote vehicle.

3. The method of claim 2, wherein the one or more sensors are located along the roadway.

4. The method of claim 1, wherein the path history is a first path history, and wherein the method further comprises:

receiving a subsequent data packet from the remote vehicle including a subsequent location and a subsequent heading of the remote vehicle and data points for a subsequent path history;

determining, based on the subsequent path history, whether any of the data points for the subsequent path history are the same as the data points for the first path history; and

generating, using the subsequent data packet received from the remote vehicle, a modified path history for the remote vehicle, the modified path history including data points for the subsequent path history that do not include data points for the first path history.

5. The method of claim 1, wherein the one or more processors are located on an ego vehicle.

6. The method of claim 5, further comprising:

determining the geometry for a proceeding portion of the roadway for the ego vehicle.

7. The method of claim 6, further comprising:

determining, based on the geometry for the proceeding portion of the roadway for the ego vehicle, a path for the ego vehicle to follow along the proceeding portion of the roadway; and

causing the ego vehicle to implement the path.

8. The method of claim 7, wherein determining the path comprises:

determining, based on the geometry for the proceeding portion of the roadway for the ego vehicle and a lateral offset between a current location of the ego vehicle and one of the previous locations defining the path history of the remote vehicle, the path for the ego vehicle to follow along the proceeding portion of the roadway.

9. The method of claim 6, further comprising:

determining, based on the geometry for the proceeding portion of the roadway for the ego vehicle, an upcoming curve in the roadway; and

causing, as the ego vehicle approaches the upcoming curve in the roadway, a reduction in speed of the ego vehicle.

10. The method of claim 1, further comprising:

storing the first location and heading of the remote vehicle, the first location and heading of the remote vehicle subsequently being re-used in determining the path history upon receipt of subsequent data packets from the remote vehicle.

11. The method of claim 1, further comprising:

comparing the determined geometry for the portion of the roadway preceding the remote vehicle with a digital road geometry associated with a map; and

verifying the digital road geometry based on the comparison.

12. The method of claim 1, further comprising:

providing generated data points between two or more data points along the path history for the remote vehicle, the generated data points and the two or more data points forming an interpolated path history,

wherein determining, using the path history, comprises;

determining, using the interpolated path history, the geometry for the portion of the roadway preceding the remote vehicle.

13. The method of claim 1, wherein the preceding portion of the roadway extends between one or more of the plurality of locations forming the path history.

14. The method of claim 1, wherein determining the geometry for the portion of the roadway preceding the remote vehicle comprises:

determining, using at least one of an Unscented Kalman filter and a Cubature Kalman filter, the geometry for the portion of the roadway preceding the remote vehicle based, at least in part, on the path history and data generated by one or more sensors and corresponding to the remote vehicle.

15. A system for determining one or more features of a roadway, the system comprising:

a communications device configured to receive a data packet from a remote vehicle, the data packet including data corresponding to a first location and a first heading of the remote vehicle;

a processor operatively connected to the communications device; and

memory operatively connected to the processor, the memory storing instructions that, when executed by the processor, cause the processor to;

determine, based on the data packet received from the remote vehicle, a path history for the remote vehicle, the path history including data points corresponding to a plurality of locations and headings including the first location and heading and one or more previous locations and headings; and

determine, using on the path history, a geometry for a portion of the roadway preceding the remote vehicle.

16. The system in claim 15, further comprising:

one or more sensors positioned to observe the remote vehicle as the remote vehicle travels along the roadway over time and capture data corresponding to the location of the remote vehicle over time, and wherein determine the geometry comprises;

determine, using the path history for the remote vehicle and data generated by the one or more sensors, the geometry for the portion of the roadway preceding the remote vehicle.

17. The system of claim 15, wherein the path history is a first path history, and wherein the memory further stores instructions to:

receive a subsequent data packet from the remote vehicle including a subsequent first location and heading of the remote vehicle and data points for a subsequent path history;

determine, based on the subsequent path history, whether any of the data points for the subsequent path history are the same as the data points for the first path history; and

generate, using the subsequent data packet received from the remote vehicle, a modified path history for the remote vehicle based on the subsequent path history, the modified path history including data points for the subsequent path history that do not include data points for the first path history.

18. The system of claim 15, wherein the system is at least partially implemented on an ego vehicle.

19. The system of claim 18, wherein the memory further stores instructions to:

determine a geometry for a proceeding portion of the roadway for the ego vehicle based at least partially on the determined geometry for the preceding portion of the roadway for the remote vehicle.

20. The system of claim 19, further comprising:

one or more actuators operatively connected to one or more components of the ego vehicle, the one or more actuators usable to control the one or more components of the remote vehicle and thereby at least partially control maneuvering of the remote vehicle, and wherein the memory further stores instructions to;

determine, based on the determined geometry for the proceeding portion of the roadway for the ego vehicle, a path for the ego vehicle to follow along the proceeding portion of the roadway; and

cause the ego vehicle to implement the path.

21. The system of claim 20, wherein determine the path for the ego vehicle to follow along the proceeding portion of the roadway comprises:

determine, based on the determined geometry for the proceeding portion of the roadway for the ego vehicle and a lateral offset between a current location of the ego vehicle and one of the previous locations defining the path history of the remote vehicle, the path for the ego vehicle to follow along the proceeding portion of the roadway.

22. The system of claim 20, wherein the memory further stores instructions to:

identify, based on the determined geometry for the proceeding portion of the roadway for the ego vehicle, an upcoming curve in the roadway; and

cause, as the ego vehicle approaches the upcoming curve in the roadway, a reduction in speed of the ego vehicle.

23. The system of claim 15, further comprising:

a map accessible by the communications device and the processor, the map including data corresponding to a digital road geometry for the portion of the roadway preceding the remote vehicle, wherein the memory further stores instructions to;

compare the determined geometry for the portion of the roadway preceding the remote vehicle with the digital road geometry corresponding to the map; and

verify the digital road geometry based on the comparison.

24. The system of claim 15, wherein the memory further stores instructions to:

provide generated data points between two or more data points along the path history for the remote vehicle, the generated data points and the two or more data points forming an interpolated path history, and wherein determine, using the path history, comprises determine, using the interpolated path history, the geometry for the portion of the roadway preceding the remote vehicle.

25. The system of claim 15, wherein the preceding portion of the roadway extends between two or more of the plurality of locations forming the path history.

26. The system of claim 15, wherein determine the geometry for the portion of the roadway preceding the remote vehicle comprises:

determine, using at least one of an Unscented Kalman filter and a Cubature Kalman filter, the geometry for the portion of the roadway preceding the remote vehicle based, at least in part, on the path history and data generated by one or more sensors and corresponding to the remote vehicle.

27. The system of claim 15, wherein the determined geometry is expressed as any one of piecewise polynomial segments and clothoids.

28. The system of claim 15, wherein the data packet further includes the one or more previous locations and headings of the remote vehicle.