Computer Vision as a Traffic Surveillance Tool

Abstract

Traffic flows on major highways have now reached the level that any disruption in flow can lead to severe congestion. Apart from the increased risk of accidents caused by the formation of queues and shock waves, the increase in journey times for road users represents a significant cost to the community. There is a need for systems that can monitor the current state of traffic along critical lengths of highway and report deteriorations in traffic conditions rapidly and consistently to traffic control centres.Currently the most sophisticated traffic surveillance systems combine the output from several point vehicle detectors (e.g. loop detectors) to provide an alarm based on certain combinations of flow, speed and detector occupancy. A CCTV system is often used to look at the highway and verify the alarm. There are two main drawbacks with such systems. Firstly, the traffic data is time based and due to the random features of traffic flow the measurements must be assessed over a period of time in order to prevent too many false alarms. Secondly, the large amount of information available from the CCTV system is largely ignored due to the expense and difficulty of having human operators continually monitoring the TV pictures.This paper describes the use of a commercially available, powerful image processing subsystem hosted by a micro-computer to provide continuous monitoring of the images form a TV camera. By utilising the particular architecture of the sub-system to carry out low level image transformations over a 512 x 512 pixel image at high speed and using the host to perform higher level “vision” an alarm can be generated when the computer detects certain conditions. This can be used at the control centre to attract attention to a particular camera location. The algorithm is based on using the spatial information contained within the image and offers the possibility of rapid response to changes in traffic conditions within the scene.A description of the hardware and the software is given along with details of trials using video recordings of different highway locations. The types of errors found are described and their impact on the likely usage of the system assessed.