METHODS AND SYSTEMS FOR MOVING TRAFFIC OBSTACLE DETECTION

• US 20170357862A1
• Filed: 03/20/2017
• Published: 12/14/2017
• Est. Priority Date: 06/09/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: TATSUBORI, MICHIAKI
• Granted Patent: US 10,176,389 B2
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0238 using obstacle or wall sensors G05D1/0246 and G05D1/0289 take precedence; lidar systems designed for anti-collision purposes G01S17/93
• CPC Class Codes: G06V 10/48 by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/09675 where a selection from the received information takes place in the vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees

Abstract

The disclosure provides systems and methods for detecting, characterizing, and predicting moving traffic obstacles. The systems and methods are suitable for densely populated areas in resource-constrained regions. With the characterizations and predictions of moving traffic obstacles, a variety of benefits can accrue to individuals and devices that use traffic information.

Claims

1. A method for maneuvering a vehicle in a roadway having potential traffic obstacles, the method comprising:

establishing a communications link between a server and a device in a vehicle; and

communicating an alert to the device, wherein the alert is configured to cause the vehicle to maneuver based on a potential moving traffic obstacle path, wherein the potential moving traffic obstacle path is determined based on sensor data for a road segment, the sensor data corresponding to observations of an obstacle at a location along the road segment over a period of time.

2. The method of claim 1, wherein the sensor data is obtained from one or more sensors selected from:

an onboard sensor on one or more probe vehicles as the one or more probe vehicles traverses the road segment;

a fixed location sensor monitoring the road segment; and

a combination thereof.

3. The method of claim 1, wherein the sensor data corresponds to observations of one or more obstacles at one or more locations along the road segment over a period of time.

4. The method of claim 1, wherein the alert is generated when the vehicle comes into proximity of the potential moving traffic obstacle path, and wherein the alert is configured to alter a user interface to display information suitable to cause a driver to initiate a maneuver, or wherein the alert is configured to cause an autonomous vehicle control system to initiate a maneuver.

5. The method of claim 1, wherein determination of the potential moving traffic obstacle path involves:

receiving the sensor data for the road segment by a server via a network;

determining a set of gray scale pixels potentially missing based on the observations, each pixel representing a time and location combination, and having an associated obstacle probability assigned based on the sensor data;

applying a modified Probabilistic Hough Transform to the set of gray scale pixels to obtain a Hough Transform space, wherein each value in the Hough Transform space is a log likelihood supported or opposed by each observation; and

identifying the potential moving traffic obstacle path by identifying a linear arrangement of locally maximum peak values in the Hough Transform space.

6. The method of claim 1, wherein the potential moving traffic obstacle path is stored in a potential moving traffic obstacle path database.

7. The method of claim 1, wherein the communication is configured to cause a change in a graphical user interface on the device such that a user is notified of the potential moving traffic obstacle and is further notified of a suggested maneuver based on the potential moving traffic obstacle.

8. The method of claim 1, wherein the communication is configured to cause an autonomous vehicle control system to maneuver based on the potential moving traffic obstacle.

9. The method of claim 1, wherein the sensor data originates from one or more vehicles traversing the road segment, and wherein the one or more vehicles is a dedicated probe vehicle or is a non-dedicated vehicle having a mobile device configured to collect and transmit the sensor data.

10. The method of claim 1, wherein the sensor data is from a camera, accelerometer, gyroscope, or combination thereof.

11. A method for maneuvering a vehicle in a roadway having potential traffic obstacles, the method comprising:

receiving sensor data for a road segment, the sensor data corresponding to observations of an obstacle at a location along the road segment over a period of time;

determining a set of gray scale pixels potentially missing based on the observations, each pixel representing a time and location combination, and having an associated obstacle probability assigned based on the sensor data;

applying a modified Probabilistic Hough Transform to the set of gray scale pixels to obtain a Hough Transform space, wherein each value in the Hough Transform space is a log likelihood supported or opposed by each observation;

identifying a potential moving traffic obstacle path by identifying a linear arrangement of locally maximum peak values in the Hough Transform space;

adding the potential moving traffic obstacle path to a potential moving traffic obstacle database;

communicating an alert to a device in a vehicle, wherein the communication comprises the potential moving traffic obstacle path and is configured to cause the vehicle to maneuver based on the potential moving traffic obstacle path.

12. A method for instructing a vehicle to maneuver in a roadway, the method comprising:

processing, by a server, sensor data received by the server from at least one device comprising a sensor, the sensor data corresponding to observations of an obstacle at a location along a road segment over a period of time, the processing comprising the steps;

(a) determining a set of gray scale pixels potentially missing based on the observations, each pixel representing a time and location combination, and having an associated obstacle probability assigned based on the sensor data;

(b) applying a modified Probabilistic Hough Transform to the set of gray scale pixels to obtain a Hough Transform space, wherein each value in the Hough Transform space is a log likelihood supported or opposed by each observation; and

(c) identifying a potential moving traffic obstacle path by identifying a linear arrangement of locally maximum peak values in the Hough Transform space;

establishing a communications link between the server and a device onboard a vehicle, the vehicle located on the road segment;

transmitting to the device via the communications link a message comprising information about the potential moving traffic obstacle and instructions for avoiding the potential moving traffic obstacle, wherein the message is configured to alter a graphical user interface of the device or to automatically alter the course of the vehicle.

13. The method of claim 12, wherein the instructions comprise route information configured for display on a GUI and configured to instruct a user to maneuver the vehicle based on the potential moving traffic obstacle.

14. The method of claim 12, wherein the instructions comprise machine-readable instructions configured to cause an autonomous vehicle control system to maneuver the vehicle based on the potential moving traffic obstacle.

15. The method of claim 12, wherein the device comprising a sensor is a fixed device monitoring the road segment or is a mobile device configured to be disposed within a vehicle traversing the road segment.

16. The method of claim 12, further comprising identifying a plurality of potential moving traffic obstacle paths by identifying a plurality of linear arrangements of locally maximum peak values in the Hough Transform space and consolidating the plurality of potential moving traffic obstacle paths.

17. A system comprising a server, the server comprising:

a processor;

a memory coupled to the processor, the memory configured to store program instructions for instructing the processor to carry out a method comprising;

establishing a communications link between a server and a device in a vehicle; and

communicating an alert to the device, wherein the alert is configured to cause the vehicle to maneuver based on a potential moving traffic obstacle path, wherein the potential moving traffic obstacle path is determined based on sensor data for a road segment, the sensor data corresponding to observations of an obstacle at a location along the road segment over a period of time.

18. The system of claim 17, further comprising a mobile device comprising a sensor and configured to be positioned in the vehicle and communicate with the server.

19. A system comprising:

a processor coupled to a memory, the memory comprising machine-readable instructions configured to cause the processor to carry out the following steps;

(a) receiving a plurality of time and location combinations, each combination having an associated obstacle probability assigned based on data from a sensor;

(b) applying a modified Probabilistic Hough Transform to the set of time and location combinations to obtain a Hough Transform space, wherein each value in the Hough Transform space is a log likelihood supported or opposed by each observation; and

(c) identifying a potential moving traffic obstacle path by identifying a linear arrangement of locally maximum peak values in the Hough Transform space;

a communications module coupled to the processor and configured to establish a communications link between the processor and a device in a vehicle and further configured to transmit an alert to the device, the alert generated by the processor based on the vehicle position and the alert containing instructions configured to cause the vehicle to maneuver based on a potential moving traffic obstacle path.

20. The system of claim 19, further comprising a mobile device comprising a sensor and configured to be positioned in the vehicle and communicate with the server.