Systems and methods for adjusting operation of a vehicle according to HOV lane detection in traffic

• US 10,202,048 B2
• Filed: 06/28/2017
• Issued: 02/12/2019
• Est. Priority Date: 06/28/2017
• 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: Payne, Joshua D., Wrobel, Shannon Alicia, Stefanon, Heraldo F., Aoki, Takanori
• Primary Examiner(s): Frejd, Russell
• Application Number:
  US15/635,938
• Publication Number:
  US 20190001836A1
• Time in Patent Office: 594 Days
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2240/12 Speed
• CPC Class Codes: B60L 2240/54 related to batteries
• CPC Class Codes: B60L 2240/64 Road conditions
• CPC Class Codes: B60L 2240/68 Traffic data
• CPC Class Codes: B60L 2250/22 by presence detection
• CPC Class Codes: B60L 7/18 Controlling the braking effect B60L7/12, B60L7/14, B60L7/16 take precedence
• CPC Class Codes: B60W 10/04 including control of propulsion units
• CPC Class Codes: B60W 10/06 including control of combustion engines
• CPC Class Codes: B60W 10/10 including control of change-speed gearings
• 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 20/13 in order to stay within battery power input or output limits; in order to prevent overcharging or battery depletion
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2420/54 Audio sensitive means, e.g. ultrasound
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/04 Traffic conditions
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: G06V 20/56 : exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/593 : Recognising seat occupancy
• CPC Class Codes: G06V 20/597 : Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 40/18 : Eye characteristics, e.g. of the iris
• CPC Class Codes: Y02T 10/64 : Electric machine technologies in electromobility
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y10S 903/903 : having energy storing means, e.g. battery, capacitor

Abstract

System, methods, and other embodiments described herein relate to preemptively controlling one or more vehicle systems of a vehicle. In one embodiment, a method includes, in response to (i) detecting that a present traffic level along a route of the vehicle satisfies a congestion threshold and (ii) detecting that a type of roadway on which the vehicle is traveling is a highway, determining whether the vehicle is traveling in a high occupancy vehicle (HOV) lane by identifying whether a number of passengers in the vehicle satisfies an HOV threshold. The method includes adjusting the one or more vehicle systems within the vehicle according to whether the number of passengers satisfies the HOV threshold to cause the vehicle to operate efficiently while traveling along the route with the present traffic level.

Claims

1. A traffic system for preemptively controlling one or more vehicle systems of a vehicle, comprising:

one or more processors;

a memory communicably coupled to the one or more processors and storing;

a monitoring module including instructions that when executed by the one or more processors cause the one or more processors to, in response to (i) detecting that a present traffic level along a route of the vehicle satisfies a congestion threshold and (ii) detecting that a type of roadway on which the vehicle is traveling is a highway, determine whether the vehicle is traveling in a high occupancy vehicle (HOV) lane by identifying whether a number of passengers in the vehicle satisfies an HOV threshold to infer that the vehicle is traveling in the HOV lane without directly detecting in which lane the vehicle is traveling; and

a control module including instructions that when executed by the one or more processors cause the one or more processors to adjust operating parameters of the one or more vehicle systems according to whether the number of passengers satisfies the HOV threshold to cause the vehicle to operate efficiently while traveling along the route with the present traffic level.

2. The traffic system of claim 1, wherein the monitoring module further includes instructions to detect the type of the roadway by electronically querying a navigation system of the vehicle to request an identifier of the type of the roadway and, in response to the querying, receive an electronic indicator that specifies the type of the roadway and whether the highway includes the HOV lane.

3. The traffic system of claim 2, wherein the indicator of the type of the roadway further specifies the HOV threshold, and wherein the HOV threshold specifies how many passengers are to be within the vehicle for the vehicle to qualify for driving in the HOV lane.

4. The traffic system of claim 1, wherein the monitoring module further includes instructions to detect that the present traffic level satisfies the congestion threshold by controlling one or more sensors of the vehicle to determine whether traffic along the route and ahead of the vehicle up to a specified range is of at least a density indicated by the congestion threshold, and wherein the congestion threshold specifies a density for the traffic that impedes driving at posted speed limits.

5. The traffic system of claim 1, wherein the monitoring module further includes instructions to identify whether the number of passengers in the vehicle satisfies the HOV threshold by controlling one or more sensors of the vehicle to determine the number of the passengers and whether the number of the passengers exceeds the HOV threshold.

6. The traffic system of claim 1, wherein the control module further includes instructions to adjust the one or more vehicle systems by adjusting a boundary level for a state of charge (SOC) of a vehicle battery within the vehicle to pre-charge the battery to the boundary level to account for traffic flow while traveling in the present traffic level.

7. The traffic system of claim 1, wherein the control module further includes instructions to adjust the one or more vehicle systems by controlling the vehicle to pre-charge a vehicle battery.

8. The traffic system of claim 1, wherein the vehicle is a hybrid electric vehicle.

9. A non-transitory computer-readable medium for controlling one or more vehicle systems of a vehicle and storing instructions that when executed by one or more processors cause the one or more processors to:

in response to (i) detecting that a present traffic level along a route of the vehicle satisfies a congestion threshold and (ii) detecting that a type of roadway on which the vehicle is traveling is a highway, determine whether the vehicle is traveling in a high occupancy vehicle (HOV) lane by identifying whether a number of passengers in the vehicle satisfies an HOV threshold to infer that the vehicle is traveling in the HOV lane without directly detecting in which lane the vehicle is traveling; and

adjust operating parameters of the one or more vehicle systems according to whether the number of passengers satisfies the HOV threshold to cause the vehicle to operate efficiently while traveling along the route with the present traffic level.

10. The non-transitory computer-readable medium of claim 9, wherein the instructions to detect the type of the roadway include instructions to electronically query a navigation system of the vehicle to request an identifier of the type of the roadway and, in response to the querying, receive an electronic indicator that specifies the type of the roadway and whether the highway includes the HOV lane.

11. The non-transitory computer-readable medium of claim 10, wherein the indicator of the type of the roadway further specifies the HOV threshold, and wherein the HOV threshold specifies how many passengers are to be within the vehicle for the vehicle to qualify for driving in the HOV lane.

12. The non-transitory computer-readable medium of claim 9, wherein the instructions to detect that the present traffic level satisfies the congestion threshold include instructions to control one or more sensors of the vehicle to determine whether traffic along the route and ahead of the vehicle up to a specified range is of at least a density indicated by the congestion threshold, and wherein the congestion threshold specifies a density for the traffic that impedes driving at posted speed limits.

13. The non-transitory computer-readable medium of claim 9, wherein the instructions to identify whether the number of passengers in the vehicle satisfies the HOV threshold include instructions to control one or more sensors of the vehicle to determine the number of the passengers and whether the number of the passengers exceeds the HOV threshold.

14. A method for preemptively controlling one or more vehicle systems of a vehicle, comprising:

in response to (i) detecting that a present traffic level along a route of the vehicle satisfies a congestion threshold and (ii) detecting that a type of roadway on which the vehicle is traveling is a highway, determining whether the vehicle is traveling in a high occupancy vehicle (HOV) lane by identifying whether a number of passengers in the vehicle satisfies an HOV threshold to infer that the vehicle is traveling in the HOV lane without directly detecting in which lane the vehicle is traveling; and

adjusting operating parameters of the one or more vehicle systems within the vehicle according to whether the number of passengers satisfies the HOV threshold to cause the vehicle to operate efficiently while traveling along the route with the present traffic level.

15. The method of claim 14, wherein detecting that the type of the roadway includes electronically querying a navigation system of the vehicle to request an identifier of the type of the roadway and, in response to the querying, receiving an electronic indicator that specifies the type of the roadway and whether the highway includes the HOV lane.

16. The method of claim 15, wherein the indicator of the type of the roadway further specifies the HOV threshold, and wherein the HOV threshold specifies how many passengers are to be within the vehicle for the vehicle to qualify for driving in the HOV lane.

17. The method of claim 14, wherein detecting that the present traffic level satisfies the congestion threshold includes controlling one or more sensors of the vehicle to determine whether traffic along the route and ahead of the vehicle up to a specified range is of a density indicated by the congestion threshold, wherein the congestion threshold specifies a density for the traffic that impedes driving at posted speed limits.

18. The method of claim 14, wherein identifying whether the number of passengers in the vehicle satisfies the HOV threshold includes controlling one or more sensors of the vehicle to determine the number of the passengers and whether the number of the passengers exceeds the HOV threshold.

19. The method of claim 14, wherein adjusting the one or more vehicle systems includes adjusting a boundary level for a state of charge (SOC) of a vehicle battery within the vehicle to account for improved traffic flow of the HOV lane in comparison to further lanes of the highway.

20. The method of claim 14, wherein adjusting the one or more vehicle systems includes controlling the vehicle to pre-charge a vehicle battery.