Simulation of traffic flow in Pedro Gil Street, Manila using cellular automata model

Abstract

Traffic simulation has become an important tool for studying and understanding traffic flow under certain congestion-causing conditions. In this study, the proponents employed the three-lane traffic flow simulation using Cellular Automata model to capture characteristics of traffic flow at a portion in Pedro Gil Street - one of the busiest secondary roads in Manila. The three-lane traffic model employed in this study used the same principles in the Nagel-Schreckenberg model for single-lane road systems incorporating traffic lights and lane-changing probability factors to depict a more realistic traffic phenomenon. Data on traffic density, traffic flow rate, and average speed were collected at every increment of 20 time-steps starting from 0 to 200, for a given combination of lane-changing probability and traffic light duration. Their behavior as time increases were generally observed to follow the fundamental traffic flow relationship. Results show that lane-changing probability and traffic light duration affect the rate of decrease of average speed with increasing density. The highest rate was found at low lane-change probabilities and longer traffic light durations, while the slowest rate was found at low lane-change probabilities and shorter traffic light durations.