A Simulation of the Impact of Curb Parking Behavior on Traffic Based on a Cellular Automata Model

To analyze the disturbance mechanism of the curb parking behavior on the dynamic traffic volume, we examined the typical curb parking belt in the non-mixed lane. We established the cellular automata model of mixed urban traffic volume considering the curb parking belt based on the conventional NaSch cellular automata model. In the model, we added rules for driving in and out of belts, rules for lane changing and rules for acceleration and deceleration. We then investigated the effects of traffic flow, lane change probability, and parking demand ratio on road traffic flow using our simulation. The results show that parking ratio has a greater impact on the traffic speed than the lane change probability. In addition, the vehicle lanes coordinate with each other and the traffic density eventually tends to equilibrium.