Heavy vehicle traffic flow optimization

• US 9,111,443 B2
• Filed: 11/29/2011
• Issued: 08/18/2015
• Est. Priority Date: 11/29/2011
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Lynar, Timothy M., Steer, Kent C.
• Primary Examiner(s): Badii, Behrang
• Assistant Examiner(s): GREENE, DANIEL LAWSON
• Application Number:
  US13/306,015
• Publication Number:
  US 20130138331A1
• Time in Patent Office: 1,358 Days
• Field of Search: 701/117, 701/118, 701/119
• US Class Current: 1/1
• 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 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/042 using inductive or magnetic detectors
• CPC Class Codes: G08G 1/07 Controlling traffic signals
• CPC Class Codes: G08G 1/081 Plural intersections under common 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

Abstract

There is provided a method for heavy vehicle traffic flow optimization. The method includes determining location information and destination information of qualifying heavy vehicles. The method further includes modifying one or more traffic signal sequences to optimize a traffic flow of the qualifying heavy vehicles responsive to the location information and the destination information. Each of the qualifying heavy vehicles has a respective associated weight greater than a predetermined weight threshold.

Claims

1. A method for heavy vehicle traffic flow optimization, comprising:

reading, from vehicles using cameras, indicia on the vehicles indicative of the vehicles being qualifying heavy vehicles;

predicting whether respective weights of the vehicles are indicative of the vehicles being the qualifying heavy vehicles based on observed overall dimensions of the vehicles from images captured by the cameras;

determining location information and destination information of the qualifying heavy vehicles; and

modifying one or more traffic signal sequences to optimize a traffic flow of the qualifying heavy vehicles responsive to the location information and the destination information,

wherein each of the qualifying heavy vehicles has a respective associated weight greater than a predetermined weight threshold, and

wherein the one or more traffic signal sequences are modified to optimize the traffic flow of the qualifying heavy vehicles while minimizing a total pavement damage caused by the qualifying heavy vehicles using a minimization function that considers a vehicle position, a vehicle velocity, and a vehicle acceleration.

2. The method of claim 1, wherein the associated weight of a given one of the qualifying heavy vehicles is an axle weight of the given one of the qualifying heavy vehicles.

3. The method of claim 1, wherein the axle weight is an actual axle weight or an expected axle weight.

4. The method of claim 1, wherein at least one of the location information and the destination information is inferred.

5. The method of claim 1, wherein at least one of the location information and the destination information is explicitly provided by the qualifying heavy vehicles.

6. The method of claim 1, wherein at least one of the location information and the destination information is provided using a combination of inferred information for some of the qualifying heavy vehicles and explicitly provided information for other ones of the qualifying heavy vehicles.

7. The method of claim 1, wherein the destination information is provided from statistics.

8. The method of claim 1, wherein said modifying step selectively implements one of a plurality of different levels of control to the traffic signal sequences depending on the respective associated weight of a given one of the qualifying heavy vehicles currently under consideration.

9. The method of claim 1, wherein heavier ones of the qualifying heavy vehicles, as based on a different weights or weight ranges, are afforded a greater degree of freedom of travel than lighter ones of the qualifying heavy vehicles.

10. The method of claim 1, wherein said predicting step compares the overall dimensions to vehicle pictures stored in a database, the vehicle pictures having weight data associated therewith.

11. The method of claim 1, wherein said modifying step comprises the step of clearing a respective path for one or more of the qualifying heavy vehicles.

12. The method of claim 11, wherein said step of clearing a respective path comprises making cars at a traffic intersection to be passed by the one or more qualifying heavy vehicles wait longer or stop earlier so that the one or more qualifying heavy vehicles do not have to stop at the traffic intersection and can simply proceed unimpeded through the intersection.

13. The method of claim 1, wherein the location information is provided using the cameras disposed along a route of one or more of the qualifying heavy vehicles.

14. The method of claim 13, further comprising repurposing the cameras from another intended use.

15. The method of claim 1, wherein the location information is provided using induction loops disposed along a route of one or more of the qualifying heavy vehicles.

16. The method of claim 15, further comprising repurposing the induction loops from another intended use.

17. A non-transitory computer readable storage medium comprising a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the following:

read, from vehicles using cameras, indicia on the vehicles indicative of the vehicles being qualifying heavy vehicles;

predict whether respective weights of the vehicles are indicative of the vehicles being the qualifying heavy vehicles based on observed overall dimensions of the vehicles from images captured by the cameras;

receive location information and destination information of the qualifying heavy vehicles; and

modify one or more traffic signal sequences to optimize a traffic flow of the qualifying heavy vehicles responsive to the location information and the destination information,

wherein each of the qualifying heavy vehicles has a respective associated weight greater than a predetermined weight threshold, and

wherein the one or more traffic signal sequences are modified to optimize the traffic flow of the qualifying heavy vehicles while minimizing a total pavement damage caused by the qualifying heavy vehicles using a minimization function that considers a vehicle position, a vehicle velocity, and a vehicle acceleration.

18. A system having at least a processor and a memory device for implementing a method for heavy vehicle traffic flow optimization, comprising:

cameras for reading from vehicles indicia on the vehicles indicative of the vehicles being qualifying heavy vehicles, and for capturing images that include observed overall dimensions of the vehicles;

weight evaluating circuitry for predicting respective weights of the vehicles indicative of the vehicles being qualifying heavy vehicles based on the observed overall dimensions of the vehicles from the images captured by the cameras;

a receiver for receiving location information and destination information of the qualifying heavy vehicles; and

a controller, operatively coupled to the receiver, for modifying one or more traffic signal sequences to optimize a traffic flow of the qualifying heavy vehicles responsive to the location information and the destination information,

wherein each of the qualifying heavy vehicles has a respective associated weight greater than a predetermined weight threshold, and

wherein the one or more traffic signal sequences are modified to optimize the traffic flow of the qualifying heavy vehicles while minimizing a total pavement damage caused by the qualifying heavy vehicles using a minimization function that considers a vehicle position, a vehicle velocity, and a vehicle acceleration.

19. The system of claim 18, wherein the cameras are disposed along a route of one or more of the qualifying heavy vehicles for providing the location information.

20. The system of claim 18, further comprising induction loops disposed along a route of one or more of the qualifying heavy vehicles for providing the location information.

21. The system of claim 18, wherein said modifying step comprises the step of clearing a respective path for one or more of the qualifying heavy vehicles.

22. The system of claim 21, wherein said step of clearing a respective path comprises making cars at a traffic intersection to be passed by the one or more qualifying heavy vehicles wait longer or stop earlier so that the one or more qualifying heavy vehicles do not have to stop at the traffic intersection and can simply proceed unimpeded through the intersection.

23. The system of claim 18, wherein said controller selectively implements one of a plurality of different levels of control to the traffic signal sequences depending on the respective associated weight of a given one of the qualifying heavy vehicles currently under consideration.

24. The system of claim 23, wherein heavier ones of the qualifying heavy vehicles, as based on a different weights or weight ranges, are afforded a greater degree of freedom of travel than lighter ones of the qualifying heavy vehicles.