Abstract: This paper proposes the Road Network-based Cellular Automata model（RN-CA） for simulation of moving objects in traffic flow.Defects of existing models are discussed.RN-CA model not only simulates the traffic behavior of moving objects of vehicles，but also proposes the departure，following，overtaking and correction model with different types of cars and roads，making simulation more accurate and reliable.Dijkastra algorithm is adopted in this paper for the dynamic selection of optimal path，factors such as the length of the road，the number of lanes，traffic，and average speed are considered.For total driven time estimation，this paper merges simulation model and prediction model，combining the current traffic information and historical traffic information.For improving the efficiency of the prototype system，the strategy of dynamic adjusting threads is applied.

Key words: cellular automaton model, multiple lane cellular automaton model, Dijkastra algorithm, optimal path

摘要： 对于交通流移动对象的模拟，论述了现有模型的不足，并提出基于道路网的元胞自动机模型（RN-CA）。该模型不仅模拟移动对象在交通流中的行为，还引入不同类型道路和车辆情况下的发车、跟车、超车和矫正模型，使模拟更精确、可靠。采用Dijkastra算法，综合考虑道路长度、车道数、流量、平均速度等因素动态计算最优行驶路径。对于行车时间预估，采用模拟加预估的方式，综合考虑当前和历史路况。为了改进系统的性能，系统采用可调节线程数目的模拟方式。

关键词: 元胞自动机微观模型, 多车道元胞自动机微观模型, Dijkastra算法, 最优路径