A systematic approach for microscopic models based on cellular automata for road traffic

Abstract

The transportation infrastructure is one of the most important resources for a country's economic and social well-being. The effectiveness of a country's street network will decide whether it develops further or stagnates. With the increasing number of vehicles on the road and the effects of urbanization, traffic roads are being subjected to a variety of requests and uses for which they were not designed, sized, or predicted. Because of the critical relevance of traffic roads, research must begin to lessen the effects of traffic jams in the streets, determine the appropriate number of traffic lanes, and integrate real-time traffic information into GPS systems. The goal of modeling a traffic-road system is to either build new traffic systems or gain a better knowledge of existing traffic systems so that they can be optimized. The accuracy, performance, stochastic and dynamic behavior of the model produced will be evaluated using a simulation of a genuine traffic system. This paper provides microscopic models based on cellular automation to replicate the behavior of various automobiles on a set of urban streets in Cluj Napoca city downtown. This model includes streets with multiple traffic lanes, various types of vehicles such as automobiles, buses, and trams, intersections with multiple possible upcoming streets controlled by traffic lights, bus stops inside and outside the traffic lane, tram stops inside the traffic lane, pedestrian crosswalks, and parking areas alongside and transversely with the right traffic lane of a street. TCA (Traffic Cellular Automata) is a proposed model that produces adequate findings in urban traffic theory. The results were obtained in both free-flow and traffic-jam conditions.