Construction and Application of Cellular Automaton Model of Traffic Flow in Freeway Diverging and Merging Areas

The operation and management optimization schemes of freeway always need to be formulated according to the traffic capacity of bottleneck sections. Due to the complexity of the traffic flow characteristics of the bottleneck sections of freeway, the current general calculation formulas of the traffic capacity are limited to many assumptions, and the accuracy is not high and the error is large. This paper attempted to construct a calculation method of traffic capacity in freeway bottleneck sections and verify it by actual measurement. Firstly, UAV technology and software Tracker were used for aerial video recording and dynamic identification and 680 groups of traffic flow data for car-following and lane-changing on freeway was obtained, including position, speed, acceleration, headway and other parameters. Then, the probability models and rule models of lane-changing considering driver characteristics were established according to the obtained traffic flow parameters, and the classical car-following model GHR was calibrated. Finally, a simulation application model of freeway traffic flow based on cellular automaton theory was constructed by the partitioning method, the acceleration requirements of following vehicles were characterized with GHR model, and the effectiveness of the model was verified by the indicators of vehicle lane-changing times and hourly traffic volume with error rates of 12.06% and 3.19%, respectively. The results show that this model can effectively calculate the capacity of freeway diverging and merging areas and design the road parameters such as the length of speed-change lane. In this case, a traffic flow simulation test was conducted on Cencun interchange sections of Guangzhou Northring Freeway, in which the road geometry characteristics, vehicle arrival conditions and traffic flow operation mechanism were simulated. The capacity of the diverging and merging areas is 5456 and 5253 pcu/h, respectively, and the optimization design values for the length of speed-change lanes in the diverging and merging areas are 125 and 200 m, respectively. The cellular automaton model of traffic flow constructed in this paper provides scientific basis for microscopic traffic flow simulation and road parameters design of freeway diverging and merging areas, and helps to improve the level of service and operational quality.