Promoting Safety At Railroad Crossings By Reducing Traffic Delays
Free (open access)
A G Hobeika & L Zhang
In this study, an artificial neural network traffic control algorithm has been developed to optimize the traffic delays around highway railroad crossings. The algorithm is divided into two steps. The first step is to design a proper preemption phase plan, and the second step is to find the optimized phase length. The objective of designing the preemption plan is to maximize the safety at the grade crossing. This can be achieved by designing the preemption plan so that highway traffic will be prevented from queuing on the grade crossing intersection. The optimized process will use as objective function the traffic delays at the intersections surrounding the grade crossing area. That function will be approximated and represented by neural network. After that function has been developed and trained, mathematical algorithms has been employed to get the optimized length of phases so that total delays can be minimized. This research utilizes the CORSIM simulated traffic network package to conduct its analysis and determine its results.