One-dimensional Cellular Automaton Traffic Flow Model Based on Driving Rules

摘要

A one-dimensional cellular automaton model is developed with considering the single vehicle speed affected by traffic flow density. With the real-time changing of single lane traffic flow density, the model can adaptively determine the traffic flow states, in which free flow state, metastable state, or a congested state. Different driving rules are adopted in different states. The new speed updating rules are proposed for the three traffic flow states. In the free flow state, the vehicle is less affected by external factors, the problem that the simulation speed is less than the actual speed in the NS model is solved by estimating the previous vehicle's speed and increasing instantaneous acceleration. In other states, the random deceleration rules are improved, and the vehicle can drive gently by increasing one random deceleration process before acceleration, so the congestion problem of VE model is eased in high density. The simulation results show that the improved model can increase the average speed and the traffic volume, and reflect more realistic single lane traffic flow characteristics, and it is conducive to ease traffic congestion problems.