State monitoring and simulation of parallel mixed traffic flow based on local density

In order to overcome the problems of low accuracy and long time consumption of traditional mixed traffic flow monitoring methods, a parallel mixed traffic flow monitoring simulation method based on local density is proposed. Based on the local density, the basic model of mixed traffic state simulation is constructed, and the delitala tosin model is optimized. From the perspective of space, the vehicle running state model is divided into several parts and defined as a subnet. Many subnets are allocated to different CPU threads, and parallel simulation is carried out through fork / join parallel mode to complete the state monitoring of parallel mixed traffic flow. The experimental results show that this method can improve the simulation accuracy and efficiency of mixed traffic flow condition monitoring and simulation, and the highest monitoring accuracy can reach 99.9%.