Multi-objective optimization for real time traffic light control and navigation systems for urban saturated networks

• US 9,076,332 B2
• Filed: 10/19/2006
• Issued: 07/07/2015
• Est. Priority Date: 10/19/2006
• Status: Active Grant

• Current Assignee: Makor Issues & Rights Ltd.
• Original Assignee: Makor Issues & Rights Ltd.
• Inventors: Myr, David
• Primary Examiner(s): Lim, Steven
• Assistant Examiner(s): Yacob, Sisay
• Application Number:
  US11/583,333
• Publication Number:
  US 20080094250A1
• Time in Patent Office: 3,183 Days
• Field of Search: 340/901, 340/907, 340/909, 340/910, 340/942, 701/117, 701/202, 701/1, 701/116, 701/118, 702/181, 706 16- 21, 370/437
• US Class Current: 1/1
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/081 Plural intersections under common control
• CPC Class Codes: G08G 1/096811 where the route is computed offboard

Abstract

A multiobjective management system for saturated traffic road networks comprising: green wave coordination of locally adaptive traffic control units, traffic movement optimization and live traffic route guidance. Current traffic congestion measurements on intersections are generated from local traffic cameras and remote air-borne conventional cameras and thermal sensing imaging cameras or satellite radar such as SAR/ISAR using optical image brightness analysis. At the first stage of traffic optimization, individual local intersection green times are computed based on current traffic congestion level. At the second stage optimization, the central traffic server uses a multiobjective approach to coordinate the current locally-optimized green times of the first stage and create input constraints for green-way coordination of plurality of traffic lights. The server updates dynamically current cycle start and green times on all network-connected traffic light controllers and also broadcasts recommended travel times, green times and green waves to all on-line client vehicle navigation units. Traffic server and individual client guidance units utilize novel time-dependent modifications of an A*-type algorithm to update current travel and recommended travel times and to execute fastest route searches.

Claims

1. A method for real time adaptive traffic light control of a plurality of intersection through evaluating traffic flow through the plurality of intersections, said method comprising the steps of:

a) evaluating traffic flow through the plurality of intersections wherein a current vehicle loading and vehicle congestion on the plurality of intersection is generated by measuring from the air or from space an image brightness for each of the plurality of intersections from one or more of a space borne high resolution camera, a thermal imaging camera or air satellite surveillance radar including synthetic aperture radar (SAR); and

b) determining a timing of green lights for said plurality of intersections,

a. wherein in step a) the current vehicle loading is generated by using brightness heterogeneity analysis of approaching lane regions and exit lane regions of the plurality of intersections, and the determining of the timing of the green lights for said plurality of intersections is based on the current vehicle loading, and

b. wherein the brightness heterogeneity analysis is based on pixel brightness variance of image pixel strings inside designated boundary polygon regions that represent the approaching lane regions and the exit lane regions.

2. The method according to claim 1, wherein, for each of the plurality of intersections, a captured image includes bitmap images collected over a short calibration period and estimated vehicle loading is generated using a pixel brightness value on specified traffic lane-regions corresponding to approaching lane regions and exiting lane regions in collected bitmap images.

3. The method according to claim 1, wherein estimated vehicle loading is computed according to a quantity of pixel strings from a captured image in horizontal and vertical directions of a region where a difference of an initial and an ending pixel brightness exceeds a pre-set tolerance brightness value.

4. A method for real time adaptive traffic light control according to claim 1, wherein the vehicle load is generated independently of determining the actual location of each vehicle.

5. A method for real time adaptive traffic light control according to claim 1, wherein step b) includes the step of determining timing of green lights relative to each other for the plurality of intersection.

6. A method for real time adaptive traffic light control according to claim 4, wherein step b) includes the step of determining timing of green lights relative to each other for the plurality of intersection.