Monitoring traffic flow

• US 10,431,077 B2
• Filed: 10/26/2016
• Issued: 10/01/2019
• Est. Priority Date: 10/30/2015
• Status: Active Grant

• Current Assignee: Optasense Holdings Limited (Luna Innovations, Inc.)
• Original Assignee: Optasense Holdings Limited (Luna Innovations, Inc.)
• Inventors: Martin, Richard, Bruce, Graham
• Primary Examiner(s): Pham, Quang
• Application Number:
  US15/771,503
• Publication Number:
  US 20180342156A1
• Time in Patent Office: 1,070 Days
• CPC Class Codes: G01H 9/004 using fibre optic sensors light guides per se G02B6/00, acousto-optical devices specially adapted for gating or modulating in optical wave guides G02F1/125
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• 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 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/015 with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: G08G 1/07 Controlling traffic signals

Abstract

This application relates to apparatus and methods for traffic monitoring, especially for monitoring of road traffic flow using fiber optic distributed acoustic sensing. The method involves performing distributed acoustic sensing (DAS) using a suitable interrogator unit (103) to provide a measurement signal from each of a plurality of sensing portions of a first length of a sensing optical fiber (102), where the first length of the sensing optical fiber runs alongside a road (101) having a plurality of lanes. The measurement signals from the sensing portions are processed to detect vehicles (104) travelling on the road and to determine at least one detected traffic flow property. The method further involves using a traffic flow model to relate the detected flow property to a modelled flow property, where the traffic flow model is configured to model vehicle detections that will be missed by the distributed acoustic sensing i.e. an indication of vehicles present on the road but not detected by the DAS sensor.

Claims

1. A method for determining traffic flow, the method comprising:

performing, by a distributed acoustic sensing interrogator unit, distributed acoustic sensing repeatedly to provide a measurement signal from each of a plurality of sensing portions of a first length of a sensing optical fibre, wherein the first length of the sensing optical fibre runs alongside a road having a plurality of lanes;

processing, by a processor connected to the distributed acoustic sensing interrogator unit, the measurement signals repeatedly from said sensing portions to detect vehicles travelling on the road and determine at least one detected traffic flow property;

using a traffic flow model, by the processor, to relate the at least one detected flow property to a modelled flow property, the traffic flow model modelling vehicle detections that will be missed by the distributed acoustic sensing; and

outputting, by the processor, an estimate of traffic flow on the road based on the modelled flow property.

2. The method as claimed in claim 1 wherein the traffic flow model comprises an observation probability, the observation probability being the likelihood that detection of a vehicle in one lane will or will not be acoustically masked by a vehicle in a different lane which is closer to the sensing optical fibre.

3. The method as claimed in claim 2 wherein observation probability is determined based on traffic flow conditions.

4. The method as claimed in claim 3 wherein the first and second functions are based on historic flow data.

5. The method as claimed in claim 2 wherein the observation probability for a lane is determined based on an average vehicle spacing in lanes closer to the sensing optical fibre, wherein the average vehicle spacing in a lane is determined according to a first function relating average speed in said lane to total traffic flow and a second function relating traffic lane in said lane to lane to total traffic flow.

6. The method as claimed in claim 2 wherein the observation probability for a lane is determined based on a masking window associated with a vehicles in a lane to the sensing optical fibre.

7. The method as claimed in claim 6 wherein different vehicles are classified into different categories, wherein each category is associated with a masking window of different size.

8. The method as claimed in claim 7 wherein the traffic flow model determines for at least one lane a proportion of vehicles of each category.

9. The method as claimed in claim 2 wherein the traffic flow model comprises a detection probability, the detection probability being the likelihood that a vehicle in a given lane which is not acoustically masked will or will not be detected by the distributed acoustic sensing.

10. The method as claimed in claim 9 wherein the detection probability is based on test data obtained by driving a test vehicle in the along the relevant section of road in the relevant lane at times of low traffic volume.

11. The method as claimed in claim 1 wherein the at least one detected traffic flow property comprises at least one of:

a total detected flow value;

a detected average vehicle speed and a detected spread of vehicle speeds.

12. The method as claimed in claim 1 further comprising:

monitoring traffic flow using a second different traffic monitoring system;

wherein using the traffic flow model to relate the at least one detected flow property to the modelled flow property comprises;

deriving a predicted value of the flow property as said modelled flow property based on the monitored traffic flow and the traffic flow model; and

comparing the predicted and detected flow property.

13. The method as claimed in claim 12 wherein the second different traffic monitoring system comprises a video based traffic monitoring system.

14. The method as claimed in claim 12 wherein the method comprises revising one or more parameters of the traffic flow model based on said comparison.

15. The method as claimed in claim 1 wherein using the traffic flow model to relate the detected flow property to the modelled flow property comprises:

using the traffic flow model to provide an estimate of a true value of the flow property as said modelled flow property based on the at least one detected flow property, wherein the estimate of the true value of the flow property compensates for missed detections.

16. The method as claimed in claim 15 wherein the method comprises estimating flow conditions based on at least one of:

a detected traffic flow value, a detected average traffic speed, a spread of detected traffic speed, wherein the traffic flow model derives the estimate of a true value of the flow property based on the detected flow property and the estimated flow conditions.

17. An apparatus for determining traffic flow, the apparatus being configured to:

receive, by a distributed acoustic sensing interrogator unit, a first data set corresponding to distributed acoustic sensing measurement signals from each of a plurality of sensing portions of a first length of a sensing optical fibre, wherein the first length of the sensing optical fibre runs alongside a road having a plurality of lanes;

process, by a processor connected to the distributed acoustic sensing interrogator unit, the measurement signals repeatedly from said sensing portions to detect vehicles travelling on the road and determine at least one detected traffic flow property; and

using a traffic flow model, by the processor, to relate the at least one detected flow property to a modelled flow property, the traffic flow model modelling vehicle detections that will be missed by the distributed acoustic sensing, and wherein the apparatus outputs an estimate of traffic flow on the road based on the modelled flow property.

18. The apparatus as claimed in claim 17 further comprising said first length of sensing optical fibre and the distributed acoustic sensing interrogator unit interrogates said first length of sensing optical fibre to obtain set first data set.

19. A traffic management system comprising the apparatus for determining traffic flow as claimed in claim 17 provides an estimate of traffic flow and a controller for generating a control signal for controlling at least one road signal based on said estimate of traffic flow.

20. The apparatus of claim 17 further including a controller for generating a control signal for controlling at least one road signal based on the estimate of traffic flow.

21. A method of assessing a distributed acoustic sensor traffic monitoring system having a sensing optical fibre deployed to run alongside a first section of road with multiple lanes, the method comprising:

monitoring traffic flow repeatedly over the first section of road using the distributed acoustic sensor (DAS) traffic monitoring system to provide a DAS detection value;

monitoring traffic flow over at least part of the first section of road using a second different type of traffic monitoring system repeatedly to provide an indication of vehicle flow;

applying, by a processor, a traffic flow model to the indication of vehicle flow to provide an estimate of an expected DAS detection value, the traffic flow model modelling vehicle detections that will be missed by the distributed acoustic sensor traffic monitoring system; and

outputting an estimate of traffic flow on the road based on the modelled flow properly and the DAS detection value.