IP Library Granted Patent US 10,181,263
Granted Patent B2
US 10,181,263 · App. 15/363,711 · Granted Jan 15, 2019

Method, apparatus and computer program product for estimation of road traffic condition using traffic signal data

Inventors: Jingwei Xu (Chicago, IL); Xin Gao (Chicago, IL); Weimin Huang (Chicago, IL); Bruce Bernhardt (Chicago, IL)
Assignee: HERE Global B.V.
G08G1/0125G08G1/0112G08G1/0116G08G1/0133G08G1/0141G08G1/0145
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Quick Facts
Patent No.
US 10,181,263
App. No.
15/363,711
Granted
Jan 15, 2019
Kind
B2
Abstract

A method for improved traffic congestion estimation is provided using signal phase and timing data from traffic signals at intersections and probe data from vehicles traversing said intersections. An example method may include: identifying each of a plurality of paths through an intersection; identifying signal phase and timing data for each traffic light associated with each path through the intersection; receiving probe data for vehicles approaching or traversing the intersection; estimating a number of vehicles failing to traverse the intersection along a path through the intersection; estimating a congestion status of the path through the intersection based on the number of vehicles failing to traverse the intersection; and causing the congestion status to be provided to permit updating of a map to reflect the congestion status.

Claims (79)

1. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform:

identify each of a plurality of paths through an intersection;

identify signal phase and timing data for each traffic light associated with each path through the intersection;

receive probe data for vehicles approaching or traversing the intersection;

estimate a number of vehicles in a queue to traverse the intersection along a path of the plurality of paths through the intersection during a red phase of the traffic light controlling the path through the intersection;

identify a green phase of the traffic light controlling the path through the intersection immediately following the red phase of the traffic light controlling the path through the intersection;

estimate a number of vehicles of the vehicles queued to traverse the intersection along the path through the intersection during a next red phase of the traffic light, immediately following the green phase of the traffic light controlling the path through the intersection, that failed to traverse the intersection during the green phase of the traffic light;

estimate a congestion status of the path through the intersection based on the number of vehicles that failed to traverse the intersection during the green phase of the traffic light; and

cause the congestion status to be provided to permit updating of a map to reflect the congestion status.

2. The apparatus of claim 1 , wherein causing the apparatus to estimate a number of vehicles in a queue to traverse the intersection along the path through the intersection comprises causing the apparatus to:

map-match at least a portion of the probe data received for the path through the intersection; and

estimate a number of vehicles in the queue to traverse the intersection along the path through the intersection during the red phase of the traffic light controlling the path through the intersection.

3. The apparatus of claim 2 , wherein causing the apparatus to estimate a congestion status of the intersection comprises causing the apparatus to:

identify a first threshold number of vehicles queued to traverse the intersection along the path through the intersection that fail to traverse the intersection along the path during the green phase of the traffic light;

identify a second threshold number of vehicles queued to traverse the intersection along the path through the intersection that fail to traverse the intersection along the path during the green phase of the traffic light;

estimate the congestion status of the path through the intersection to be heavy in response to the number of vehicles failing to traverse the intersection along the path through the intersection being above the second threshold;

estimate the congestion status of the path through the intersection to be medium in response to a number of vehicles failing to traverse the path through the intersection being above the first threshold, but below the second threshold; and

estimate the congestion status of the path through the intersection to be low in response to the number of vehicles failing to traverse the intersection along the path through the intersection being below the first threshold.

4. The apparatus of claim 3 , wherein the apparatus is further caused to:

provide an indication on a display of a representation of the path through the intersection to be highlighted in a first color in response to the congestion status being low;

provide an indication on the display of a representation of the path through the intersection to be highlighted in a second color in response to the congestion status being medium; and

provide an indication on the display of a representation of the path through the intersection to be highlighted in a third color in response to the congestion status being heavy.

5. The apparatus of claim 1 , wherein the apparatus is further caused to:

calculate an intersection saturation vehicle number for the path through the intersection, wherein the intersection saturation vehicle number is calculated based on a number of vehicles failing to traverse the intersection along the path during a first transition from the green phase to the red phase of the traffic light subtracted from the number of vehicles queued to traverse the intersection along the path; and

estimate the number of vehicles at a start of a next transition from a red phase to a green phase of the traffic light controlling the path through the intersection.

6. The apparatus of claim 5 , wherein the apparatus is further caused to:

determine a congestion condition in response to the estimated number of vehicles at the start of the next transition from a red phase to a green phase of the traffic light being greater than the intersection saturation vehicle number.

7. A method comprising:

identifying each of a plurality of paths through an intersection;

identifying signal phase and timing data for each traffic light associated with each path through the intersection;

receiving probe data for vehicles approaching or traversing the intersection;

estimating a number of vehicles in a queue to traverse the intersection along a path of the plurality of paths through the intersection during a red phase of the traffic light controlling the path through the intersection;

identifying a green phase of the traffic light controlling the path through the intersection immediately following the red phase of the traffic light controlling the path through the intersection;

estimating a number of vehicles of the vehicles queued to traverse the intersection along the path through the intersection during a next red phase of the traffic light, immediately following the green phase of the traffic light controlling the path through the intersection, that failed to traverse the intersection during the green phase of the traffic light;

estimating a congestion status of the path through the intersection based on the number of vehicles that failed to traverse the intersection during the green phase of the traffic light; and

causing the congestion status to be provided to permit updating of a map to reflect the congestion status.

8. The method of claim 7 , wherein estimating a number of vehicles in a queue to traverse the intersection along the path through the intersection comprises:

map-matching at least a portion of the probe data received for the path through the intersection; and

estimating a number of vehicles in the queue to traverse the intersection along the path through the intersection during the red phase of the traffic light controlling the path through the intersection.

9. The method of claim 8 , wherein estimating a congestion status of the intersection comprises:

identifying a first threshold number of vehicles queued to traverse the intersection along the path through the intersection that fail to traverse the intersection along the path during the green phase of the traffic light;;

identifying a second threshold number of vehicles queued to traverse the intersection along the path through the intersection that fail to traverse the intersection along the path during the green phase of the traffic light;;

estimating the congestion status of the path through the intersection to be heavy in response to the number of vehicles failing to traverse the intersection along the path through the intersection being above the second threshold;

estimating the congestion status of the path through the intersection to be medium in response to a number of vehicles failing to traverse the path through the intersection being above the first threshold, but below the second threshold; and

estimating the congestion status of the path through the intersection to be low in response to the number of vehicles failing to traverse the intersection along the path through the intersection being below the first threshold.

10. The method of claim 9 , further comprising:

providing an indication on a display of a representation of the path through the intersection to be highlighted in a first color in response to the congestion status being low;

providing an indication on the display of a representation of the path through the intersection to be highlighted in a second color in response to the congestion status being medium; and

providing an indication on the display of a representation of the path through the intersection to be highlighted in a third color in response to the congestion status being heavy.

11. The method of claim 7 , further comprising:

calculating an intersection saturation vehicle number for the path through the intersection, wherein the intersection saturation vehicle number is calculated based on a number of vehicles failing to traverse the intersection along the path during a first transition from the green phase to the red phase of the traffic light subtracted from the number of vehicles queued to traverse the intersection along the path; and

estimating the number of vehicles at a start of a next transition from a red phase to a green phase of the traffic light controlling the path through the intersection.

12. The method of claim 11 , further comprising:

determining a congestion condition in response to the estimated number of vehicles at the start of the next transition from a red phase to a green phase of the traffic light being greater than the intersection saturation vehicle number.

13. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising:

program code instructions to identify each of a plurality of paths through an intersection;

program code instructions to identify signal phase and timing data for each traffic light associated with each path through the intersection;

program code instructions to receive probe data for vehicles approaching or traversing the intersection;

program code instructions to estimate a number of vehicles in a queue to traverse the intersection along a path of the plurality of paths through the intersection during a red phase of the traffic light controlling the path through the intersection;

program code instructions to identify a green phase of the traffic light controlling the path through the intersection immediately following the red phase of the traffic light controlling the path through the intersection;

program code instructions to estimate a number of vehicles of the vehicles queued to traverse the intersection along the path through the intersection during a next red phase of the traffic light, immediately following the green phase of the traffic light controlling the path through the intersection, that failed to traverse the intersection during the green phase of the traffic light;

program code instructions to estimate a congestion status of the path through the intersection based on the number of vehicles that failed to traverse the intersection during the green phase of the traffic light; and

program code instructions to cause the congestion status to be provided to permit updating of a map to reflect the congestion status.

14. The computer program product of claim 13 , wherein the program code instructions to estimate a number of vehicles in a queue to traverse the intersection along the path through the intersection comprises:

program code instructions to map-match at least a portion of the probe data received for the path through the intersection; and

program code instructions to estimate a number of vehicles in the queue to traverse the intersection along the path through the intersection during the red phase of the traffic light controlling the path through the intersection.

15. The computer program product of claim 14 , wherein the program code instructions to estimate a congestion status of the intersection comprises:

program code instructions to identify a first threshold number of vehicles queued to traverse the intersection along the path through the intersection that fail to traverse the intersection along the path during the green phase of the traffic light;

program code instructions to identify a second threshold number of vehicles queued to traverse the intersection along the path through the intersection that fail to traverse the intersection along the path during the green phase of the traffic light;

program code instructions to estimate the congestion status of the path through the intersection to be heavy in response to the number of vehicles failing to traverse the intersection along the path through the intersection being above the second threshold;

program code instructions to estimate the congestion status of the path through the intersection to be medium in response to a number of vehicles failing to traverse the path through the intersection being above the first threshold, but below the second threshold; and

program code instructions to estimate the congestion status of the path through the intersection to be low in response to the number of vehicles failing to traverse the intersection along the path through the intersection being below the first threshold.

16. The computer program product of claim 15 , further comprising:

program code instructions to provide an indication on a display of a representation of the path through the intersection to be highlighted in a first color in response to the congestion status being low;

program code instructions to provide an indication on the display of a representation of the path through the intersection to be highlighted in a second color in response to the congestion status being medium; and

program code instructions to provide an indication on the display of a representation of the path through the intersection to be highlighted in a third color in response to the congestion status being heavy.

17. The computer program code of claim 13 , further comprising:

program code instructions to calculate an intersection saturation vehicle number for the path through the intersection, wherein the intersection saturation vehicle number is calculated based on a number of vehicles failing to traverse the intersection along the path during a first transition from the green phase to the red phase of the traffic light subtracted from the number of vehicles queued to traverse the intersection along the path; and

program code instructions to estimate the number of vehicles at a start of a next transition from a red phase to a green phase of the traffic light controlling the path through the intersection.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 13, 2017
From: GAO, XIN; HUANG, WEIMIN; XU, JINGWEI; BERNHARDT, BRUCE
To: HERE GLOBAL B.V.
Reel/Frame 041240/0828 →
Continuity (1)
Related Publication 20180151064A1 · May 31, 2018
Cited By (1)
US 12,347,317