The Study Of Urban Network Route Guidance Strategy Based On Traffic Information

With the rapid development of economics and the improvement of the urbanization level,the travel requirement of residents and the number of motor vehicle keep increasing.The traffic congestion has been one of bottlenecks restricting cities' development.Route guidance strategy based on traffic flow feature is an effective method to reduce traffic congestion and promote system performance.In recent years,more and more scholars pay attention to different route guidance strategy simulation model in urban traffic network.They explore the influence of different route guidance strategy in the system.In this paper,we use the cellular automaton model to model Manhattan-like urban traffic system.Based on the previous models,we propose the route guidance strategy based on mean speed and the route guidance strategy based on minimum cost maximum flow.By computer simulation,we can explore the features and laws of urban traffic system with route guidance strategy.The main contents of the paper are as follows:1.Based on the previous models,we propose the route guidance strategy based on mean speed information feedback.It is simulated by the cellular automaton model.The simulation results show that the global route guidance strategy increases the maximum flow of the system and the critical density.It is obviously that the new route guidance strategy can improve the system performance.2.By comparing vehicle distribution in the research of the global route guidance strategy,we can find the vehicle detours phenomenon that vehicles will keep away from center area,and drive along the city periphery.3.Not all of the drivers in the reality will obey the guidance information.We define the car which obey the guidance information as dynamic car.We can find the optimal rate of dynamic car by computer simulation.4.In the research of optimal rate,we find that the change of road network scale does not affect the ratio of system optimal dynamic car.The cycle time of guidance information and the ratio of system optimal dynamic car present negative correlation relationship.5.We propose the route guidance strategy based on minimum cost maximum flow.Gurobi mathematical programming optimizer is used for solving minimum cost maximum flow problem.We can determine the turning probability by link flow.We can find that the route guidance strategy improve system arrive rate by cellular automata simulation.6.In a homogeneous network,the value of network maximum flow which is solved by Gurobi is similar to the actual rate of maximum system network flow.There always exist a balance state when network flow rate is lower than the maximum network flow rate.