Process for monitoring traffic for automatic vehicle incident detection

• US 5,884,212 A
• Filed: 10/15/1996
• Issued: 03/16/1999
• Est. Priority Date: 04/15/1994
• Status: Expired due to Fees

• Current Assignee: Thomson-CSF
• Original Assignee: Thomson-CSF
• Inventors: Lion, Didier
• Primary Examiner(s): NGUYEN, TAN QUANG
• Application Number:
  US08/722,139
• Time in Patent Office: 882 Days
• Field of Search: 701/117, 701/119, 701/96, 340/933, 340/934, 340/935, 340/936, 340/943, 340/903, 340/905, 382/104, 348/148, 348/149
• US Class Current: 701/117
• CPC Class Codes: G01S 13/92 for velocity measurement

Abstract

A process for monitoring traffic for automatic vehicle incident detection using radar waves to detect the vehicles, their instantaneous speed and their distance. The process consists in correlating the information obtained regarding vehicles in one and the same distance bracket during two consecutive processing time intervals, so as to determine, at each instant, the acceleration of each vehicle and a prediction of its speed, and in then detecting an incident in a distance bracket by detecting the passing of the speed of a vehicle below a given speed threshold. The advantages of the process resides in rapid incident detection in regard to a road or motorway network, with a view to informing the users rapidly.

Claims

1. Process for monitoring the traffic of vehicles able to travel on at least two lanes, of the type consisting in transmitting a UFH wave of predetermined form in accordance with a predefined radiation pattern, in receiving signals reflected by the vehicles over a given duration of acquisition T_A, and in processing the signals received in such a way as to detect the vehicles and in calculating, for each distance, the number of vehicles i detected as well as the instantaneous speed V_i (t) at a given instant t of each vehicle, the process wherein, the radiation pattern having an axis of aim substantially parallel to the direction of the lanes, and the steps of acquiring and processing the signals being iterated over consecutive time intervals, it furthermore includes an automatic incident detection phase comprising performing the following iterative steps:

A first step of calculating parameters including;

investigating, at each instant t, whether a vehicle i detected in the current time interval corresponds to a vehicle j detected at an instant of the preceding time interval;

for all the vehicles i corresponding to a vehicle j, calculating at the instant t, their acceleration γ

_i (t) by applying the relation ##EQU7## in which α

t represents the duration between the instants and t, as well as a prediction V_i^P (t+1) of their speed at a time of the following time interval, by applying the relation

space="preserve" listing-type="equation">V.sub.i.sup.P (t+1)=γ

.sub.i (t)×

Δ

t+V.sub.i (t)

for the other vehicles i, initializing their acceleration γ

_i (t) to the zero value;

eliminating from the processing all the other vehicles j not corresponding to any vehicle; and

A second step of incident detection based on the parameters calculated in the first step, by detecting the passing of the speed of a vehicle i below a first predetermined speed threshold V_thresh.

2. Process according to claim 1, wherein the investigating of correspondence between a vehicle i and a vehicle j comprises calculating, for each vehicle i and for each vehicle j, the discrepancy between the prediction V_j^P (t) of the speed of vehicle j and the instantaneous speed V_i (t) of vehicle i, and in then comparing the absolute value of the discrepancy with a predetermined threshold value V_max beyond which vehicles i and j are regarded as distinct.

3. Process according to claim 2, wherein the second step of incident detection comprises comparing, for each vehicle i, the speed V_i (t) with the first speed threshold V_thresh, and the acceleration γ

_i (t) with the zero value, and in detecting an incident when the speed V_i (t) and the acceleration are respectively less than the first speed threshold V_thresh and the zero value.

4. Process according to claim 2, wherein the second step of incident detection comprises comparing, for each vehicle i, the speed V_i (t) and the prediction V_i^P (t+1) of the speed with respect to the said given first speed threshold V_thresh, and in detecting an incident when the speed V_i (t) and the prediction V_i^P (t+1) are respectively greater than and less than the first speed threshold V_thresh.

5. Process according to claim 2, of calculating the means speed of all the vehicles detected, at a given distance k, over a predetermined duration D.

6. Process according to claim 1, wherein the second step of incident detection comprises comparing, for each vehicle i, the speed V_i (t) with the first speed threshold V_thresh, and the acceleration γ

_i (t) with the zero value, and in detecting an incident when the speed V_i (t) and the acceleration are respectively less than the first speed threshold V_thresh and the zero value.

7. Process according to claim 6, of calculating the means speed of all the vehicles detected, at a given distance k, over a predetermined duration D.

8. Process according to claim 1, wherein the second step of incident detection comprises comparing, for each vehicle i, the speed V_i (t) and the prediction V_i (t+1) of the speed with respect to the said given first speed threshold V_thresh, and in detecting an incident when the speed V_i (t) and the prediction V_i^P (t+1) are respectively greater than and less than the first speed threshold V_thresh.

9. Process according to claim 8, further comprising a step of calculating the means speed of all the vehicles detected, at a given distance k, over a predetermined duration D.

10. Process according to claim 1, further comprising a step of calculating the mean speed of all the vehicles detected, at a given distance k, over a predetermined duration D.

11. Processing according to claim 10, further comprising a step of extracting the maximum and minimum speeds calculated in regard to the vehicles detected at a given distance over the duration D.

12. Process according to claim 11, further comprising a step of calculating the standard deviation of the speed over the duration D.

13. Process according to claim 10, further comprising a step of calculating the standard deviation of the speed over the duration D.

14. Processing according to claim 10, further comprising a holdup or slowdown detection step including:

effecting a comparison of the mean speeds V_mean (k) and V_mean (k+1) calculated for two successive distances k, k+1, with respect to a second speed threshold V_mthresh,

detecting a start of slowdown or an end of slowdown on the basis of the result of the comparison.

15. Processing according to claim 14, wherein the holdup detection step disables the automatic incident detection phase when a slowdown has been detected.

16. Process according to claim 1, wherein the automatic incident detection phase is applied to any vehicle whose instantaneous speed is less than a predefined threshold speed V_inf, and in that it furthermore includes a step in which a check is made as to whether a vehicle is still detected after a duration greater than a limit duration D_lim.

17. Process according to claim 1, further comprising several successive phases of automatic detection of incidents, and in that the first step of the said phases is furthermore used to undertake a counting of the vehicles passing through a reference distance bracket k_ref during a predefined analysis period T_ref.

18. Process according to claim 17, further comprising a step of calculating the mean speed V of the vehicles over the distance bracket k_ref during the analysis period T_ref.

19. Process according to claim 17, further comprising a step of calculating the occupancy factor T_occ of the distance bracket k_ref during the analysis period T_ref by applying the relation:

##EQU8## in which;

N₁ is the number of detections per direction of flow obtained according to the process of the invention during the analysis period T_ref,

M is the number of automatic incident detection phases undertaken during T_ref,

Q is the number of lanes in the direction of flow.

20. Process according to claim 17, further comprising a step of calculating the time of presence T_p of a vehicle in the distance bracket k_ref, and its length.