Customization of automatic incident detection algorithms for signalized urban arterials

Abstract

Non - recurrent congestion or incidents are detrimental to the operability and efficiency of busy urban t ransport networks. There exist s multiple Automatic Incident Detection Algorithms (AIDA) to remotely detect the occurrence of an incident in highway or freeway scenarios, however very little research has been performed to automatically detect incidents in signalised urban arterials . This limited research attention has mostly been focussed on developing new urban arterial specific algorithms rather than identifying alternative methods to synthesize existing freeway based algorithms to urban conditions. The main hindrance to such synthesis is that the traffic patterns on the signalised urban arterials are significantly different from the same on highways/freeways due to the presence of traffic intersections. This paper introduces a new strategy of customis ing the existing AIDAs (freeway base d or otherwise) to significantly improve their adaptability to signalised urban arterial transport networks. The new strategy focuses on preprocessing the tr affic information before being used as input to a freeway/highway based AIDA to lessen the effect o f traffic signals and to imitate the input patterns in highway/freeway based incident conditions. The effectiveness of this new strategy has been established with the help of four existing AIDAs. The proposed strategy is a simple solution to implement exis ting algorithms to signalised urban networks without any further instrumentation or operational cost.