››› Session 3

Automated Incident Detection Algorithms

Dr Hussein Dia   School of Engineering, The University of Queensland

The high cost of congestion caused by incidents such as accidents, disabled vehicles, construction work and other events that result in a capacity reduction of roads has prompted a growing worldwide interest in developing efficient and effective incident management programs. The success of incident management programs will depend to a large extent on the development of reliable and efficient automated incident detection (AID) algorithms. These software programs analyse data collected from traffic detection devices to determine whether an incident has occurred and alert operators in the traffic control centre to abnormal traffic conditions. This paper will provide a background to automated incident detection algorithms and describe some of the most widely used freeway AID models. Common measures of performance and criteria used to evaluate the efficiency and effectiveness of these algorithms will then be presented. The traffic detection, software and hardware requirements needed for the development and implementation of these models will also be described. A comparative evaluation between a number of AID algorithms is then presented. The paper will conclude by highlighting current state-of-the-art techniques in the development of AID algorithms on both freeway and arterial roads and the benefits to be gained from the implementation of quick and reliable incident detection systems.