Research on traffic state of private car in urban area based on agent cellular automata model

For the local urban regional traffic with multiple road intersections, the modeling and simulation are carried out in combination with the background of private car commuting, and a private car travel model based on agent cellular automata model is proposed. The effectiveness of the model is verified by analyzing the real traffic scenarios such as recurrence following, acceleration and deceleration, and starting and stopping at traffic lights. The impact of the number of private cars and whether traffic lights are set on the roads on the traffic efficiency of urban areas at multiple intersections is discussed with the average waiting time as the index. The results show that the model can effectively simulate the driving behavior of private cars. The average speed is inversely proportional to the number of private cars and directly proportional to the average waiting time. Setting traffic lights can increase the number of stops. When local traffic flow is not saturated, setting traffic lights will affect traffic efficiency. When local traffic flow is saturated, setting traffic lights can reduce traffic delay and waiting time.