A methodology for computing time-dependent alternate routes around freeway incidents

This article introduces an approach that produces dynamic control strategies in the form of alternate routes around freeway incidents in response to the prevailing traffic conditions. The approach consists of a System Optimum Dynamic Traffic Assignment algorithm, a traffic simulator, a heuristic control strategies generation algorithm, and various communication and data processing components. The system is implemented and tested computationally on an example network in a simulated environment under various scenarios of incident severity and congestion levels. The results indicate that the system performs reasonably well for moderately congested networks and severe incidents. Copyright © Taylor and Francis Inc

An intelligent system to enhance traffic safety analysis

Traffic phenomena are characterized by complexity and uncertainty, hence require sophisticated information management to identify patterns relevant to safety. Traffic information systems have emerged with the aim to ease traffic congestion and improve road safety. However, assessment of traffic safety and congestion requires significant amount of data which in most cases is not available. This work illustrates an approach that aims to alleviate this problem through the integration of two mature technologies namely, simulation basedDynamic Traffic Assignment (DTA) and Bayesian Belief Networks (BBN). The former generates traffic information that is utilised by a Bayesian engine to quantify accident risk. Dynamic compilation of accident risks is used to gives rise to overall traffic safety. Preliminary results from this research have been validated