Development of dynamic traffic signal control based on Monte Carlo simulation approach

Abstract

This study addresses the maximum queue length problem arises when the arriving traffic exceeds the sensors' detection area, especially for the over-saturated condition. The paper presents an adaptive system working Monte Carlo based Signal Timing (MCaST) algorithm based on microscopic scale vehicle arrival. Since the algorithm works as an adaptive system, two new mathematical formulas for the delay and queue length calculations have been proposed instead for fixed time formulas. Based on both queue length and intersection delay, the intersection performance has been calculated and used as a slave method to optimize the cycle length. The suggested MCaST algorithm has been tested using real field data, and the delay is decreased by 30.2% less during peak hour traffic. Besides, the delay results from the algorithm have been compared with Webster's and Highway Capacity Manual 2010 delay formulas and VISSIM software. Results of the numerical experiments show the MCaST algorithm's validity.