Study On The Impact Factors Of Macroscopic Fundamental Diagram For Urban Traffic System Based On Cellular Automata Model

In recent years,with the rapid development of society,economy and urbanization,the population and scale of cities continuously increase.However,road construction has been difficult to meet the needs of urban transportation,because of the rapid growth of vehicle numbers.Urban traffic congestion has become the biggest obstacle for urban development.In the recent decades,many researchers have done a lot of important research work to alleviate urban traffic congestion,which leads to the traffic flow theory.Many complex traffic flow phenomena have been reproduced and explained by the macroscopic,mesoscopic and microscopic models.Since the 1990s,cellular automata model has been favored by researchers and engineers in the field of transportation,and has become a new research hot spot.In order to alleviate urban traffic congestion,this paper studies the impact of perimeter flow control strategy,advanced information feedback strategy and road network structure on the macroscopic fundamental diagram(MFD).The Manhattan-like urban traffic system is simulated microscopically by using cellular automata model.The simulation considers main features of traffic flow in urban road network,including car-following,lane-changing,intersection-traversing and driver's routing behavior.This paper researches the macroscopic quality of traffic flow,and analyses the impacts of various factors on the MFD for utban traffic system.The main contents of this paper are as follows:(1)Cellular automata model is used to model the urban traffic system,and the perimeter flow control strategy for urban traffic system is simulated and analyzed.We find that the MFD have different shapes and characteristics for the core area and the peripheral area of the urban traffic system.The MFD shows three states in traffic flow:freeflow state,saturate state and congestion state.The perimeter flow control strategy assigns a special prohibiting stage for the surrounding vehicles entering the core area by controlling the perimeter traffic lights for the roads entering the core area.When the vehicle density in the core area exceeds a threshold ?1,all perimeter traffic lights will turn red.When the vehicle density in the core area decreases to another threshold?2(?2<?1),all perimeter traffic lights will return to the normal phases.The two critical densities of the perimeter flow control strategy are determined by the flow-density relationship(namely MFD)of the core area.Simulation results show that the average arrival rate and the average flow will be greatly improved with the perimeter flow control strategy.In addition,the perimeter flow control strategy can increase the critical density of traffic congestion and reduce the gridlock probability of traffic system,and the system can perform well under both closeand open boundary conditions.(2)An improved time shortest path routing strategy(ITSP)based on advanced travel time information feedback is proposed.With the development of modern intelligent traff-ic system technology,the travel time information can be collected and processed to provide route-choice suggestions to travellers.However,due to the complexity of the traffic system,the feedback of traffic information might lead to serious congestion in some concerned areas(such as the Central Business District).We propose an improved time shortest path routing strategy(ITSP)based on advanced travel time information feedback.In the ITSP strategy,the probability of vehicles entering the core area is reduced with creasing the travel-cost-related parameters ? in the core area,and the vehicle density in the core area is reduced.Based on the cellular automata traffic model,we study the effects of ITSP strategy on the traffic performance in a Manhattan-like urban traffic system.We find that when a is slightly larger than 1.0,the performance of the traffic system will be enhanced as compared to the situations of no information feedback(GSP)or providing the real travel time information(TSP).The simulation results show that,ITSP strategy can increase the average arrival rate and the traff-ic flow in scenario of the fixed total number of vehicles.In scenario of varying total number of vehicles,ITSP strategy can reduce vehicle density,which helps to avoid traffic gridlock and improve the system reliability.Furthermore,the effects of different sizes of core areas and different Origin-Destination patterns are also explored.(3)Traffic system performance is investigated with rectangular urban traffic system road network structures of different length-width ratio.The total area of road networks is kept the same.The traffic system performance under both geographic shortest path routing strategy(GSP)and time shortest path routing strategy(TSP)is simulated.Under the close boundary condition,the maximum average arrival rate of square road network is the largest,but with a lowest critical density of congestion.With the increase of length-width ratio,the average arrival rate will decrease,while the critical density of congestion will increase.Under the open boundary condition with time-varying loading process,the square road network has better performance.This phenomenon can be explained by the balance between vehicle's loading rate and arrival rate.The research work could provide theoretical guidance to alleviate urban traffic congestion,and put forward reasonable traffic management measures and control strategies for traffic system.