Real-time vision-based traffic flow measurements and incident detection

Barak Fishbain*, Ianir Ideses, David Mahalel, Leonid Yaroslavsky

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Visual surveillance for traffic systems requires short processing time, low processing cost and high reliability. Under those requirements, image processing technologies offer a variety of systems and methods for Intelligence Transportation Systems (ITS) as a platform for traffic Automatic Incident Detection (AID). There exist two classes of AID methods mainly studied: one is based on inductive loops, radars, infrared sonar and microwave detectors and the other is based on video images. The first class of methods suffers from drawbacks in that they are expensive to install and maintain and they are unable to detect slow or stationary vehicles. Video sensors, on the other hand, offer a relatively low installation cost with little traffic disruption during maintenance. Furthermore, they provide wide area monitoring allowing analysis of traffic flows and turning movements, speed measurement, multiple-point vehicle counts, vehicle classification and highway state assessment, based on precise scene motion analysis. This paper suggests the utilization of traffic models for real-time vision-based traffic analysis and automatic incident detection. First, the traffic flow variables, are introduced. Then, it is described how those variables can be measured from traffic video streams in real-time. Having the traffic variables measured, a robust automatic incident detection scheme is suggested. The results presented here, show a great potential for integration of traffic flow models into video based intelligent transportation systems. The system real time performance is achieved by utilizing multi-core technology using standard parallelization algorithms and libraries (OpenMP, IPP).

Original languageEnglish
Article number72440I
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume7244
DOIs
StatePublished - 2009
EventReal-Time Image and Video Processing 2009 - San Jose, CA, United States
Duration: 19 Nov 200920 Nov 2009

Keywords

  • Automatic incident detection
  • Intelligent transportation systems
  • Real-time traffic measurements

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