Method and device for classifying vehicles

• US 20030163263A1
• Filed: 01/10/2003
• Published: 08/28/2003
• Est. Priority Date: 07/13/2000
• Status: Active Grant

• Current Assignee: Laboratoire Central Des Ponts et Chaussees, Alcatel-Lucent SA (Nokia Corporation)
• Original Assignee: Laboratoire Central Des Ponts et Chaussees, Alcatel SA (Nokia Corporation)
• Inventors: Bertrand, Jean, Dicko, Mamadou
• Granted Patent: US 6,865,518 B2
• Time in Patent Office: Days
• US Class Current: 702/65
• CPC Class Codes: G08G 1/042 using inductive or magnetic detectors

Abstract

A device for obtaining vehicle electromagnetic signature data from electromagnetic signals includes means (16) for obtaining a digitized signal from measured electromagnetic signals. The device further includes means (20) for determining if a digitized signal is a vehicle electromagnetic signature signal. The means (20) then calculate electromagnetic signature data of a vehicle from the digitized signal, and time-stamp each data point of the electromagnetic signature. Vehicles can therefore be classified in accordance with several criteria by specific processing of the digitized electromagnetic signature signals.

Claims

1. A signal processor device for obtaining vehicle electromagnetic signature data from electromagnetic signals, the device comprising:

means (16) for obtaining a digitized signal from the electromagnetic signals,

means (20, 30, 36) for determining if a digitized signal is a vehicle electromagnetic signature signal, and

means (20, 36) for calculating electromagnetic signature data of a vehicle from the digitized signal, and for sequencing and time-stamping each electromagnetic signature data point in synchronized and real-time manner.

2. A device according to claim 1, wherein the means (20, 30, 36) for determining if a digitized signal is a vehicle electromagnetic signature signal include means (30) for storing the digital data of each signal during a predetermined time period (t1) and means (36) for comparing the stored data with a threshold value.

3. A device according to claim 1 or claim 2, wherein the means for time-stamping each vehicle electromagnetic signature data point include clock means (26) and/or timer means (28).

4. A device according to any one of claims 1 to 3, wherein the electromagnetic signals are frequency, phase, amplitude, or impedance variation signals.

5. A device according to any one of claims 1 to 3, including an oscillator and means for producing electromagnetic signals representative of oscillator frequency variations and from which the vehicle electromagnetic signature data are produced.

6. A device according to any one of claims 1 to 5, further including means for adapting the time interval between signature data points as a function of the real duration of the electromagnetic signature signal.

7. A system for acquiring vehicle electromagnetic signature data, the system comprising:

a single electromagnetic loop (10), and

a device according to any one of claims 1 to 6.

8. A signal processing device or a data acquisition system according to any preceding claim, further comprising classification means (22, 54) for classifying vehicles into two or more categories (C1, . . . , C14) of silhouettes as a function of the digitized electromagnetic signals.

9. A device according to claim 8, wherein the classification means process the digitized electromagnetic signature signals using a plurality of decision trees.

10. A device according to claim 9, wherein the classification means sample each electromagnetic signature signal beforehand and produce a set of digitized data and data characteristic of a number of harmonics of the electromagnetic signature signal.

11. A device according to claim 10, wherein the data characteristic of harmonics of the electromagnetic signature signal includes amplitude, phase, harmonic content, and harmonic amplitude ratio data for the electromagnetic signature signal.

12. A device according to any one of claims 8 to 11, wherein the classification means (22, 54) can also classify vehicles into long vehicles and short vehicles.

13. A device according to any one of claims 7 to 12, further including means (22, 54) for calculating the speed of a vehicle.

14. A method of processing vehicle electromagnetic signature signals, the method comprising:

producing electromagnetic signature signals that are digitized, sequenced and time-stamped in a synchronized manner and in real time,

classifying vehicles into two or more silhouette categories (C1, . . . , C14) as a function of the digitized, sequenced and time-stamped electromagnetic signature.

15. A method according to claim 14, wherein vehicles are classified with the aid of a shape classification algorithm or method including a plurality of decision trees.

16. A method according to claim 15, wherein the electromagnetic signature signals are sampled and subjected to harmonic analysis processing to determine therefrom data representative of some of their spectral components.

17. A method according to any one of claims 14 to 16, wherein the vehicles are classified into 14 categories.

18. A method according to any one of claims 14 to 17, wherein classification includes a step of classification into two categories, namely a long vehicle category and a short vehicle category.

19. A method according to any one of claims 14 to 18, wherein the speed of the vehicles is estimated from the digitized signature data.

20. A method of generating a program for classifying vehicles into two or more predetermined silhouette categories as a function of signals representative of electromagnetic signatures of the vehicles, the method comprising:

processing the signals in the time domain to produce a first set of digitized data,

processing the signals in the frequency domain to produce a second state of data containing the signal harmonic characteristics,

making a first random selection of n data points from the data of the first and second sets,

generating a first decision tree for classifying the vehicles into said predetermined categories as a function of the n data points obtained in the first random selection of data,

making one or more second random selections of n data points from the data points of the first and second sets, and

generating one or more second decision trees for classifying the vehicles into said predetermined categories as a function of the n data points obtained during the second random selection of data.

21. A method according to claim 20, wherein the signals representative of electromagnetic signatures are digitized signals.

22. A method of using electromagnetic signals to obtain electromagnetic signature data of vehicles on a road having lanes each provided with an electromagnetic loop, the method comprising the following steps:

obtaining a digitized signal from the electromagnetic signals,

determining if a digitized signal is a vehicle electromagnetic signature signal, and

calculating electromagnetic signature data of a vehicle from the digitized signal, and sequencing and time-stamping each electromagnetic signature data point in synchronized real-time manner.

23. A method according to claim 22, further comprising a step of storing the digital data of each signal during a predetermined time period (t1) and of comparing the stored data with a threshold value.

24. A method according to claim 22 or claim 23, wherein the electromagnetic signals are frequency, phase, amplitude, or impedance variation signals.

25. A method according to any one of claims 22 to 24, the road having two lanes, and wherein vehicles straddling both lanes are identified.

26. A method according to any one of claims 22 to 25, wherein moving vehicle signature data is also acquired superposed on a signature of a stationary vehicle.

27. A method according to claim 26, wherein the signature data for moving vehicles is isolated from the signature data for stationary vehicles.