Lane-level vehicle navigation for vehicle routing and traffic management

• US 10,794,720 B2
• Filed: 05/04/2018
• Issued: 10/06/2020
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Caliper Corporation
• Original Assignee: Caliper Corporation
• Inventors: Slavin, Howard, Yang, Qi, Morgan, Daniel, Rabinowicz, Andres, Brandon, Jonathan, Balakrishna, Ramachandran
• Primary Examiner(s): Kerrigan, Michael V
• Application Number:
  US15/971,010
• Publication Number:
  US 20180299290A1
• Time in Patent Office: 886 Days
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G01C 21/3658 Lane guidance
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

Lane-level vehicle routing and navigation apparatus includes a simulation module that performs microsimulation of individual vehicles in a traffic stream, and a lane-level optimizer that evaluates conditions along candidate paths from an origin to a destination as determined by the simulation module, and determines recommended lane-level maneuvers along the candidate paths. A link-level optimizer determines the candidate paths based on link travel times determined by the simulation module. The simulation may be based on real-time traffic condition data. Recommended candidate paths may be provided to delivery or service or emergency response vehicles, or used for evacuation planning, or to route vehicles such as garbage or postal trucks, or snowplows. Corresponding methods also may be used for traffic planning and management, including determining, based on microsimulation, (a) altered road geometry, (b) altered traffic signal settings, such as traffic signal timing, and/or (c) road pricing.

Claims

1. A traffic signal system comprising:

a computing unit including;

a simulation module that performs, faster than real time, microsimulation of individual vehicles in a traffic stream, and

a lane-level route optimizer that evaluates predicted conditions simultaneously along multiple alternative candidate paths, including at least one multi-lane path segment, from an origin to a destination as determined by said simulation module, and determines predicted performance measures; and

a traffic signal controller that receives instructions from the computing unit, based on the predicted performance measures, and adjusts traffic signals for managing traffic.

2. The traffic signal system of claim 1 wherein the traffic signal controller adjusts traffic signals to optimize signal timing, phasing and coordination.

3. The traffic signal system of claim 1 wherein the predicted performance measures comprise at least one of delays, throughput, number of stops, and percentage of vehicles arriving at green signals.

4. The traffic signal system of claim 1 wherein the computing unit receives real-time traffic data for use in at least one of the simulation module and the lane-level route optimizer.

5. The traffic signal system of claim 4 further comprising inputs for the real-time traffic data.

6. The traffic signal system of claim 5 wherein the inputs for the real-time traffic data comprise at least one magnetic loop detector.

7. The traffic signal system of claim 5 wherein the inputs for the real-time traffic data comprise at least one traffic camera.

8. A traffic signal control method comprising:

performing, faster than real time, in a simulation module of a computing unit, microsimulation of individual vehicles in a traffic stream, and

evaluating, in a link-optimizing engine, predicted conditions, simultaneously along multiple alternative candidate paths, including at least one multi-lane path segment, from an origin to a destination as determined by said simulation module, to determine predicted performance measures; and

providing instructions from the computing unit to a traffic signal controller, based on the predicted performance measures, to adjust traffic signals for managing traffic.

9. The traffic signal control method of claim 8 wherein the providing instructions comprises adjusting traffic signals to optimize at least one of signal timing, phasing and coordination.

10. The traffic signal control method of claim 8 wherein the predicted performance measures comprise at least one of delays, throughput, number of stops, and percentage of vehicles arriving at green signals.

11. The traffic signal control method of claim 8 further comprising receiving real-time traffic data at the computing unit for use in at least one of the performing microsimulation and the evaluating predicted conditions.

12. The traffic signal control method of claim 11 wherein the receiving real-time traffic data comprises receiving data from at least one magnetic loop detector.

13. The traffic signal control method of claim 11 wherein the receiving real-time traffic data comprises receiving data from at least one traffic camera.