Accident avoidance is a very important part of enhancing road safety. Thedevelopment of a queue-end warning system for highway work zones which automatically predicts queue-end location and alert drivers so that rear-endcollisions can be avoided is described. The research methodology consistsof calibration and validation of a microsimulator, simulation of traffic with sensors and queue counter looped-in, the use of simulation results for training and validation of artificial neural network (ANN) models for queue-end prediction, and the synthesis of the information system that integrates the ANN models, sensors and intelligent systems. Selected results ofANN models illustrate their application in the queue-end warning system. For the covering abstract see ITRD E134653.
Abstract