Managing vehicle efficiency

• US 8,155,868 B1
• Filed: 03/31/2009
• Issued: 04/10/2012
• Est. Priority Date: 03/31/2009
• Status: Active Grant

• Current Assignee: Toyota Infotechnology Center Co., Ltd. (Toyota Motor Corporation)
• Original Assignee: Toyota Infotechnology Center Co., Ltd. (Toyota Motor Corporation)
• Inventors: Melen, Roger D., Xing, Daniel, Rai, Vinuth, Kresse, Matthew, Hong, Kezhu
• Primary Examiner(s): Dickson, Paul N
• Assistant Examiner(s): Freedman, Laura
• Application Number:
  US12/415,877
• Time in Patent Office: 1,106 Days
• Field of Search: 340901-905, 340/988, 340/438, 340/439, 340/441, 340/442, 340/449, 340/500, 340/501, 340/407.1, 340/815.4, 340/384.1, 700/28, 700/29, 700/32, 700/44, 700/45, 701/36, 701/70, 701/99, 701/116, 701/117, 701/123, 701/213
• US Class Current: 701/123
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005

Abstract

Historic vehicle state information specifying a plurality of performance values associated with the plurality of subsystems of the vehicle at a plurality of time points, including a current time point is stored at the vehicle. Historic neighbor vehicle state information specifying a plurality of performance values associated with a plurality of subsystems of a vehicle at a plurality of time points, including a current time point is received from a neighbor vehicle proximate to the vehicle. A forward-looking model is generated based on vehicle state information. An performance value associated with a subsystem of the plurality of subsystems of the vehicle is determined based on the historic vehicle state information, the historic neighbor vehicle state information, and the forward-looking model. A recommendation to a driver of the vehicle is provided based on the optimized performance value.

Claims

1. A computer-implemented method of controlling operation of one or more subsystems of a plurality of subsystems of a vehicle to improve performance, the method comprising:

storing at a vehicle, historic vehicle state information specifying a plurality of performance values associated with a plurality of subsystems of the vehicle at a plurality of time points, including a current time point;

receiving at the vehicle, other state information specifying a plurality of performance values associated with a second system;

generating a forward-looking model, the forward-looking model specifying a relative weighting of the plurality of subsystems of the vehicle being associated with improved performance;

determining a performance value associated with the one or more subsystems of the plurality of subsystems of the vehicle based on the historic vehicle state information, the other state information and the forward-looking model; and

generating and sending a signal based on the performance value.

2. The method of claim 1, further comprising:

identifying a personalization setting associated with a driver of the vehicle, the personalization setting indicating a degree of optimization; and

weighting the performance value using the personalization setting.

3. The method of claim 1, wherein the performance value is a future fuel consumption rate and determining the performance value comprises:

identifying a plurality of acceleration rates associated with a plurality of fuel consumptions based on the historic vehicle state information;

wherein generating the forward-looking model specifies the future fuel consumption rate based on the plurality of acceleration rates associated with the plurality of fuel consumptions; and

applying the forward-looking model to current vehicle state in the historic vehicle state information to determine a fuel consumption cost associated with accelerating the vehicle.

4. The method of claim 3, further comprising:

determining a first fuel consumption cost associated with accelerating the vehicle to an intersection;

determining a second fuel consumption cost associated with decelerating the vehicle to stop at the intersection; and

determining whether to stop the vehicle responsive to determining whether the first fuel consumption cost exceeds the second fuel consumption cost.

5. The method of claim 1, wherein:

the other state information is historic neighbor vehicle state information specifying a plurality of performance values associated with a plurality of subsystems of a neighbor vehicle at the plurality of time points, including the current time point; and

receiving at the vehicle includes receiving the historic neighbor vehicle state information from the neighbor vehicle proximate to the vehicle.

6. The method of claim 5, wherein the performance value indicates a future wait time associated with a queue with the neighbor vehicle and determining the performance value comprises:

identifying for the neighbor vehicle a plurality of green light reaction times based on the historic neighbor vehicle state information;

generating for the neighbor vehicle a neighbor forward-looking model that specifies a relative weighting of a future green light reaction time, based on the plurality of green light reaction times;

applying for the neighbor vehicle the neighbor forward-looking model to the historic neighbor vehicle state information to determine the future green light reaction time associated with the neighbor vehicle; and

generating the future wait time responsive to summing one or more future green light reaction times associated with the queue.

7. The method of claim 5, wherein the performance value indicates a vehicle threat prediction value associated with the neighbor vehicle and determining the performance value comprises:

identifying a plurality of action codes based on the historic neighbor vehicle state information, wherein each action code indicates an action performed by the neighbor vehicle;

wherein the forward-looking model comprises a plurality of relative weightings, wherein each relative weighting indicates a probability that the neighbor vehicle will perform an action corresponding to an action code of the plurality of action codes; and

applying the forward-looking model to the historic neighbor vehicle state information to generate the vehicle threat prediction value.

8. The method of claim 7, wherein the plurality of relative weightings are specific to a geographic position of the neighbor vehicle and applying the forward-looking model to the historic neighbor vehicle state information comprises:

identifying a current geographic position associated with the neighbor vehicle based on the historic vehicle state information; and

determining a relative weighting that the neighbor vehicle will perform an action corresponding to an action code based on the geographic position of the neighbor vehicle specified in the historic neighbor vehicle state information.

9. The method of claim 8, wherein the plurality of relative weightings are each specific to a time when the actions are performed and applying the forward-looking model to the historic neighbor vehicle state information comprises determining a relative weighting that the neighbor vehicle will perform an action corresponding to an action code based on a current time.

10. The method of claim 7, wherein generating and sending a signal based on the performance value includes outputting a recommendation based on the performance value, the recommendation being to wait at an intersection responsive to determining that the vehicle threat prediction value associated with the neighbor vehicle indicates a threat to the vehicle.

11. The method of claim 7, wherein generating and sending a signal based on the performance value includes outputting a recommendation based on the performance value, the recommendation being to paceline with the neighbor vehicle responsive to determining that the vehicle threat prediction value associated with the neighbor vehicle does not indicate a threat to the vehicle.

12. The method of claim 1, wherein generating and sending a signal based on the performance value includes providing the driver of the vehicle with a tactile signal representing a recommendation.

13. The method of claim 1, wherein generating and sending a signal based on the performance value includes providing the driver of the vehicle with an audio signal representing a recommendation.

14. The method of claim 1, wherein generating and sending a signal based on the performance value includes providing the driver of the vehicle with a visual signal representing a recommendation.

15. The method of claim 1, wherein generating the forward-looking model includes:

generating a vehicle forward-looking model based on the historic vehicle state information, the vehicle forward-looking model specifying relative weightings of the plurality of subsystems of the vehicle being associated with improved performance; and

generating a second forward-looking model based on the other state information, the second forward-looking model specifying relative weightings of the plurality of subsystems of the vehicle being associated with improved performance.

16. The method of claim 1, wherein generating and sending a signal based on the performance value includes sending a control signal that automatically adjusts the one or more subsystems of the plurality of subsystems to improve performance of the vehicle.

17. The method of claim 1, wherein the performance is one from a group of energy efficiency and emissions.

18. The method of claim 1 wherein:

the other state information is infrastructure state information specifying a plurality of performance values associated with infrastructure at the plurality of time points, including the current time point; and

receiving at the vehicle includes receiving the infrastructure state information from a roadside access unit proximate to the vehicle.

19. The method of claim 18, wherein the infrastructure state information specifies a value associated with intersections and environmental conditions at the plurality of time points, including the current time point.

20. A system for managing vehicle performance, the system comprising:

an input device for receiving information about a vehicle including historic vehicle state information;

a communication device having an input and an output for receiving other state information;

a forward-looking model specifying relative weightings of one or more subsystems of the vehicle being associated with improved performance; and

a performance management system having inputs and an output for determining a performance value associated with the one or more subsystems of the vehicle based on the historic vehicle state information, the other state information and the forward-looking model.

21. The system of claim 20, wherein the input device is one from a group of a vehicle sensor, an environmental sensor and a global positioning system.

22. The system of claim 20 comprising an automated vehicle adjustment module coupled to receive signals from the performance management system and convert the received signals to signals addressed to and for controlling the one or more subsystems of the vehicle.

23. The system of claim 20 comprising a signaling module coupled to receive signals from the performance management system and convert the received signals to instructions for presentation to a driver.

24. The system of claim 20, wherein the forward-looking model comprises:

a vehicle forward-looking model based on the historic vehicle state information, the vehicle forward-looking model specifying relative weightings of the one or more subsystems of the vehicle being associated with improved performance; and

a second forward-looking model based on the other state information, the second forward-looking model specifying relative weightings of the other state information associated with improved performance.

25. The system of claim 24, wherein the second forward-looking model is a neighbor vehicle forward-looking model based on a plurality of relative weightings, wherein each relative weighting indicates whether a neighbor vehicle will perform an action corresponding to an action code of a plurality of action codes.

26. The system of claim 24, wherein the second forward-looking model is an infrastructure forward-looking model based on a plurality of relative weightings, wherein each relative weighting indicates whether infrastructure information is associated with improved performance.

27. The system of claim 24, wherein the communication device is a wireless communications device and receives one from a group of a Vehicle to Vehicle Message Set and an Infrastructure to Vehicle Message Set.

28. The system of claim 24, comprising a memory register for storing the historic vehicle state information and the other state information, the memory register coupled to the performance management system.

29. The system of claim 24, comprising a lookup table for storing one from a group of calculated distance, recommended speed, queue wait time, queue stop line distance, store distance, and other temporary variables.