IDENTIFICATION OF VEHICLE PARKING USING DATA FROM VEHICLE SENSOR NETWORK

• US 20160300486A1
• Filed: 04/08/2015
• Published: 10/13/2016
• Est. Priority Date: 04/08/2015
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: Jing Liu, Jun Liu, Siyi Chen, Yinling Ni
• Inventors: HU, Junpeng, NI, Yinling, LI, Yongxun, CHEN, Siyi, LIU, Jun, LIU, Jing
• Granted Patent: US 9,607,509 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01S 1/026 of associated receivers
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0125 Traffic data processing
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/017 identifying vehicles G08G1/015, G08G1/054 take precedence
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules
• CPC Class Codes: G08G 1/144 on portable or mobile units, e.g. personal digital assistant [PDA]
• CPC Class Codes: G08G 1/147 where the parking area is within an open public zone, e.g. city centre

Abstract

A framework for identifying parking areas from vehicle trajectory data is described herein. Vehicle trajectory data collected from a sensor network having a plurality of sensor stations for detecting vehicles is provided. The vehicle trajectory data is pre-processed to generate a tracking table of vehicles and analysed to determine an interstation parking area between first and second sensor stations of interest based on input parameters from a user.

Claims

1. A computer-implemented method for identifying parking areas comprising:

providing vehicle trajectory data of vehicles collected from a sensor network having a plurality of sensor stations for detecting vehicles, the sensor stations of the sensor network are distributed in a geographical area of interest, the vehicle trajectory data is stored as vehicle trajectory data records in a vehicle trajectory table, wherein a vehicle trajectory data record of the vehicle trajectory data comprises,

a vehicle id identifying the vehicle detected,

a sensor station id identifying the sensor station detecting the vehicle, and

a captured time which is the time that the sensor station detected the vehicle;

pre-processing the vehicle trajectory data records by an analysis system to generate a tracking table of vehicles;

storing the tracking table in a data model of an analyzer of the analysis system; and

analyzing the data model to determine an interstation parking area between first and second sensor stations of interest based on input parameters from a user.

2. The computer-implemented method of claim 1 wherein pre-processing the vehicle

trajectory data comprises discarding dirty data records of the vehicle trajectory data, wherein a dirty data record is a vehicle trajectory record having a difference in capture time with a capture time of a previous vehicle trajectory data record with the same vehicle id is greater than a threshold value.

3. The computer-implemented method of claim 2 wherein the tracking table comprises a plurality of tracking tables based on vehicle id.

4. The computer-implemented method of claim 1 wherein pre-processing the vehicle trajectory data comprises:

discarding dirty data records, wherein a dirty data record is a vehicle trajectory record having a difference in capture time with a capture time of a previous vehicle trajectory data record with the same vehicle id is greater than a threshold value; and

wherein the tracking table comprises a plurality of tracking tables based on vehicle id.

5. The computer-implemented method of claim 1 wherein a process of generating the tracking table comprises:

caching a current vehicle trajectory data record received;

searching the vehicle trajectory table to determine if a previous vehicle trajectory data record with the same vehicle id as that of the current vehicle trajectory data record exist;

if the previous vehicle trajectory data record does not exist, terminate the process;

if the previous vehicle trajectory data record does exist, calculate the time difference between a current_captured time of the current vehicle trajectory data record with a last_captured time of the previous vehicle trajectory data record;

if the difference between the current_captured time and the last_captured time is not less than a threshold value, the process terminates; and

if the difference between the current_captured time and the last captured time is less than a threshold value,

the current vehicle trajectory data record is processed to form a tracking table record,

inserting the tracking table record into the tracking table, and

the process terminates.

6. The computer-implemented method of claim 5 wherein the tracking table comprises a plurality of tracking tables based on vehicle id.

7. The computer-implemented method of claim 5 wherein a tracking record in the tracking table comprises:

the vehicle id identifying the vehicle detected;

the previous sensor station id of the previous trajectory data record;

the previous_captured time of the previous trajectory data record;

the current_sensor station id of the current trajectory data record; and

the current_captured time of the current trajectory data record.

8. The computer-implemented method of claim 7 wherein the tracking table comprises a plurality of tracking tables based on vehicle id.

9. The computer-implemented method of claim 1 wherein a tracking record in the tracking table comprises:

the vehicle id identifying the vehicle detected;

a from_sensor station id identifying the sensor station detecting the vehicle;

a from_captured time which is the time that the from sensor station detected the vehicle;

a to_sensor station id identifying the to sensor station detecting the vehicle; and

a to_captured time which is the time that the to sensor station detected the vehicle.

10. The computer-implemented method of claim 9 wherein tracking records in the tracking table comprises a difference between the from_capture time and the to_capture time is less than a threshold value.

11. The computer-implemented method of claim 10 wherein the tracking table comprises a plurality of tracking tables based on vehicle id.

12. The computer-implemented method of claim 1 wherein the sensor stations comprise fixed traffic sensors, wherein a fixed sensor station comprises an RFID sensor, a license plate recognition sensor or both.

13. The computer-implemented method of claim 1 wherein identifying parking areas comprises identifying interstation parking areas between first and second contiguous sensor stations of a set of stations.

14. The computer-implemented method of claim 13 comprises determining a convex hull surrounding the first and second sensor stations, wherein the parking areas are disposed within the convex hull.

15. The computer-implemented method of claim 12 wherein identifying interstation parking areas between first and second contiguous sensor stations of a set of stations comprises:

calculating probabilities Pr(b_i|S₁,S₂) for b_iε

A₂, where i=1, . . . N−

2;

sorting the probabilities Pr(b_i|S₁,S₂); and

selecting first K stations based on

K=max{θ

₁,argmin_K[Σ

_k=0^KPr(b<sub>iN−

k−

2</sub>|S₁,S₂)≧

θ

₂]}.

16. The computer-implemented method of claim 15 comprises determining a convex hull surrounding the first and second sensor stations in which the parking areas are disposed, where determining the convex hull comprises determining a set of points by {S₁,S₂}∪

B_K, where B_K={b<sub>iN−

2</sub>, . . . , b<sub>n−

K−

2</sub>}, wherein the set of points is used to generate the convex hull to form a convex polygon enclosing the set of points.

17. A parking area analysis system comprising:

a data storage module for storing a vehicle trajectory table, the vehicle trajectory table includes vehicle trajectory data records collected from a sensor network having a plurality of sensor stations for detecting vehicles, the sensor stations of the sensor network are distributed in a geographical area of interest, wherein a vehicle trajectory data record comprises,

a vehicle id identifying the vehicle detected,

a sensor station id identifying the sensor station detecting the vehicle, and

a captured time which is the time that the sensor station detected the vehicle;

a pre-processor for analyzing the vehicle trajectory data set to generate a tracking table of vehicles, wherein the tracking table is stored in a data model;

an analyzer for analyzing the data model to determine an interstation parking area between first and second sensor stations of interest based on input parameters from a user, wherein the parking area is disposed within a convex hull surrounding the first and second sensor stations.

18. The system of claim 17 wherein a tracking record in the tracking table comprises:

the vehicle id identifying the vehicle detected;

a from_sensor station id identifying the sensor station detecting the vehicle;

a from_captured time which is the time that the from sensor station detected the vehicle;

a to_sensor station id identifying the to sensor station detecting the vehicle; and

a to_captured time which is the time that the to sensor detected the vehicle.

19. A non-transitory computer-readable medium having stored thereon a program code, the program code executable by a computer for identifying parking areas comprising:

providing vehicle trajectory data of vehicles collected from a sensor network having a plurality of sensor stations for detecting vehicles, the sensor stations of the sensor network are distributed in a geographical area of interest, the vehicle trajectory data is stored as vehicle trajectory data records in a vehicle trajectory table, wherein a vehicle trajectory data record of the vehicle trajectory data comprises,

a vehicle id identifying the vehicle detected,

a sensor station id identifying the sensor station detecting the vehicle, and

a captured time which is the time that the sensor station detected the vehicle;

pre-processing the vehicle trajectory data records to generate a tracking table of vehicles;

storing the tracking table in a data model of an analyzer of the analysis system; and

analyzing the data model to determine an interstation parking area between first and second sensor stations of interest based on input parameters from a user, wherein the parking area is disposed within a convex hull surrounding the first and second sensor stations.

20. The non-transitory computer-readable medium of claim 19 wherein the convex hull is determined by:

calculating probabilities Pr(b_i|S₁,S₂) for b_iε

A₂, where i=1, . . . N−

2;

sorting the probabilities Pr(b_i|S₁,S₂); and

selecting first K stations based on

K=max{θ

₁,argmin_K[Σ

_k=0^KPr(b<sub>iN−

k−

2</sub>|S₁,S₂)≧

θ

₂]}.