Vehicle route selection based on energy usage

• US 8,290,701 B2
• Filed: 09/26/2011
• Issued: 10/16/2012
• Est. Priority Date: 11/24/2009
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Telogis Incorporated (Verizon Communications Inc.)
• Inventors: Mason, Ralph, Koch, Jason, Jelinek, Howard
• Primary Examiner(s): Tran, Dalena
• Assistant Examiner(s): HOLLOWAY, JASON R
• Application Number:
  US13/245,217
• Publication Number:
  US 20120022904A1
• Time in Patent Office: 386 Days
• Field of Search: 701411-417, 701422-424, 701/428, 701/436, 701/457, 701/521, 340/441, 340/994, 705/7.13, 705/333, 705/336, 705/338, 705/341
• US Class Current: 701/422
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: G01C 21/3469 Fuel consumption; Energy use; Emission aspects
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 10/083 Shipping
• CPC Class Codes: G06Q 10/0833 Tracking
• 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: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching

Abstract

Vehicle management systems and associated processes can consider energy consumption when selecting routes for fleet vehicles. Vehicle management systems and associated processes are described that, in certain embodiments, evaluate vehicle energy usage based on factors such as terrain or elevation, vehicle characteristics, driver characteristics, road conditions, traffic, speed limits, stop time, turn information, traffic information, and weather information, and the like. The features described herein may also be implemented for non-fleet vehicles, such as in personal vehicle navigation systems.

Claims

1. A method for optimizing energy use of a fleet of powered vehicle assets, the method comprising:

identifying a plurality of destinations to be visited by a fleet of vehicle assets,

wherein each of said destinations is defined by three-dimensional location data having a latitude component, a longitude component, and an elevation component;

identifying two or more vehicles, each of said vehicles having a corresponding vehicle type,

wherein the vehicle type is internal combustion, electric or hybrid;

identifying two or more drivers capable of operating said vehicles, each driver having a corresponding driver profile,

wherein the driver profile comprises information regarding past driver behavior that is reflective of energy use; and

by using one or more computing devices, determining two or more combinations of a vehicle, a driver, and a transportation route, wherein a transportation route comprises a subset of the plurality of destinations, wherein the combinations are configured to reduce the total amount of energy required for said vehicles to visit the plurality of destinations, and wherein the determination of the two or more combinations is based, at least in part, on the vehicle type and the driver profile, and wherein the determination of the two or more combinations is implemented by one or more computing devices comprising one or more processors and memory.

2. The method of claim 1, further comprising outputting the transportation routes to the drivers on a graphical user interface display integrated within each of the vehicles.

3. The method of claim 1, further comprising outputting the transportation routes to each of the drivers on a graphical user interface display of a mobile device.

4. The method of claim 1, further comprising calculating real-time vehicle speed recommendations for at least some portions of the transportation routes, the real-time vehicle speed recommendations being calculated to reduce energy use along the portions of the transportation routes.

5. The method of claim 4, wherein at least one of the calculated real-time vehicle speed recommendations for a particular portion of a transportation route is a speed that is lower than a posted speed limit for the particular portion of the transportation route.

6. The method of claim 4, further comprising outputting the calculated vehicle speed recommendations to the driver.

7. The method of claim 1, wherein the driver profile comprises information regarding one or more of the following:

acceleration habits of the driver, speeding habits of the driver, and work habits of the driver.

8. The method of claim 1, wherein the driver profile comprises information related to one or more of the following;

age, preferred driving times, preferred days of work, wage information, overtime information, experience level, and driver training information.

9. The method of claim 1, wherein the total amount of energy required for said vehicles to visit the plurality of destinations is determined based, at least in part, on elevation changes between the destinations.

10. The method of claim 1, wherein determining said transportation routes comprises determining a plurality of candidate transportation routes based on shortest distance and/or estimated travel time;

calculating an energy use estimate for each of the candidate transportation routes;

ranking the candidate transportation routes based, at least in part, on the calculated energy use estimate of each of the candidate transportation routes; and

identifying a preferred transportation route from the candidate transportation routes based, at least in part, on the calculated energy use estimates of the candidate transportation routes.

11. The method of claim 1, further comprising receiving real-time data having a potential to affect the total amount of energy required for said vehicles to visit the plurality of destinations and determining a modified transportation route for each of said vehicles based, at least in part, on said received real-time data, wherein said modified transportation routes are configured to reduce the total amount of energy required to visit the plurality of destinations.

23. The system of claim 1, wherein vehicles with a vehicle type that is electric or hybrid are matched with a plurality of destinations that have more elevation changes between the destinations.

24. The system of claim 1, wherein drivers with a driving profile that indicates aggressive driving behavior are matched with a plurality of destinations that have fewer elevation changes between the destinations.

27. The method of claim 1, wherein the method is configured to be implemented by the one or more computing devices.

28. The method of claim 1, wherein the determination of the two or more combinations is performed substantially in real time by the one or more computing devices and a memory.

12. A system for optimizing energy use of a fleet of powered vehicle assets, comprising:

a database comprising first data representing a fleet of vehicles, each of said vehicles having a corresponding vehicle type,

wherein the vehicle type is internal combustion, electric or hybrid;

the database further comprising second data representing two or more drivers capable of operating at least one vehicle in said fleet,

wherein the second data for each driver comprises a driver profile that comprises information regarding past driver behavior that is reflective of energy use; and

a computer system comprising computer hardware configured to identify a plurality of destinations to be visited by the fleet of vehicles, wherein each of said destinations is defined by three-dimensional location data having a latitude component, a longitude component, and an elevation component and to determine two or more combinations of a vehicle, a driver, and transportation route, wherein a transportation route comprises a subset of the plurality of destinations, wherein the combinations are configured to reduce the total amount of energy required for said vehicles to visit the plurality of destinations, and wherein the determination of the two or more combinations is based, at least in part, on the vehicle type and the driver profile.

13. The system of claim 12, further comprising a user interface display integrated within each of the vehicles, wherein the computer system is further configured to output the transportation routes to in-vehicle devices integrated within each of the vehicles over a communications network.

14. The system of claim 12, wherein the computer system is further configured to output the transportation routes to mobile devices carried by the drivers over a communications network, wherein the transportation route is displayed on a graphical user interface display of the mobile device.

15. The system of claim 12, wherein the computer system is further configured to calculate real-time vehicle speed recommendations for at least some portions of the transportation routes, the real-time vehicle speed recommendations being calculated to reduce energy use along the portions of the transportation routes.

16. The system of claim 15, wherein at least one of the calculated real-time vehicle speed recommendations for a particular portion of a transportation route is a speed that is lower than a posted speed limit for the particular portion of the transportation route.

17. The system of claim 15, wherein the computer system is further configured to output the calculated vehicle speed recommendations to the in-vehicle or mobile devices over the communications network.

18. The system of claim 12, wherein the driver profile comprises information regarding one or more of the following:

acceleration habits of the driver, speeding habits of the driver, and work habits of the driver.

19. The system of claim 12, wherein the driver profile comprises information related to one or more of the following;

age, preferred driving times, preferred days of work, wage information, overtime information, experience level, and driver training information.

20. The system of claim 12, wherein the total amount of energy required for said vehicles to visit the plurality of destinations is determined based, at least in part, on elevation changes between the destinations.

21. The system of claim 12, wherein determining said transportation routes comprises determining a plurality of candidate transportation routes based on shortest distance and/or estimated travel time;

calculating an energy use estimate for each of the candidate transportation routes;

ranking the candidate transportation routes based, at least in part, on the calculated energy use estimate of each of the candidate transportation routes; and

identifying a preferred transportation route from the candidate transportation routes based, at least in part, on the calculated energy use estimates of the candidate transportation routes.

22. The system of claim 12, further comprising receiving real-time data having a potential to affect the total amount of energy required for said vehicles to visit the plurality of destinations and determining a modified transportation route for each of said vehicles based, at least in part, on said received real-time data, wherein said modified transportation routes are configured to reduce the total amount of energy required to visit the plurality of destinations.

25. The system of claim 12, wherein vehicles with a vehicle type that is electric or hybrid are matched with a plurality of destinations that have more elevation changes between the destinations.

26. The system of claim 12, wherein drivers with a driving profile that indicates aggressive driving behavior are matched with a plurality of destinations that have fewer elevation changes between the destinations.

29. The system of claim 12, wherein the computer system comprises one or more processors.