Traffic Simulation Research Based On Cooperative Vehicle Infrastructure System

The transport system is a typical complex system which is randomness, non-linear and has lots of key elements. Considering traditionally only form the roads and vehicles, it is difficult to solve the problems of the worsening traffic congestion, frequent accidents hair, environmental pollution, etc. CVIS is a people, vehicles, roads integration Intelligent Transport System which uses of the information between vehicle-vehicle and vehicle-road. It has very important significance to improve the efficiency and security of the transport system and to achieve the sustainable development of the transport system. The CVIS is in its infancy in China now. And we need to research from multiple levels like theory, system and technology. The study of CVIS simulation method will provide actual system theoretical support and practical guidance.This dissertation focuses on the traffic simulation of CVIS. We use Paramics to establish a road network, and complying extracting information and controlling the key elements of the system by programmer. The paper studies the basic theory of the CVIS traffic simulation comprehensively, and analyzes the key issues related to the simulation. As the simulation data is the basis of the simulation, the paper researches the mechanisms of the data extraction and data control. There are two ways getting data, one is real-time style through the API application program and the other is to read the simulation data files after the simulation. And to the deviation in the vehicle coordinate conversion, the paper uses applicable map matching method to calibrate.This dissertation selects the car following model and traffic signal control model in CVIS to study. Through the study of the traditional car following model and the problem that in car following model in Paramics the safe distance value is not accurate, we design of a new minimum safe distance car following model based on Paramics car following model and the data exchange in CVIS. And we proposed a signal control strategy in main road control in CVIS based on fuzzy adjust on traffic phases. We use the ratio of the car total number in non-main road to the car total number in main road as the input, the phase gain as output to improve the phase and Green Wave to improve the efficiency of road traffic. Finally, we design the CVIS traffic simulation platform and compare it with the traditional safe distance of the car following model and phase adjustment with non-fuzzy control model. Form the simulation data, we can see that the minimum safety distance car following model and the phase fuzzy control signal method based on CVIS is more efficiency.