Study On Agent Based Simulation Of Bus Rapid Transit System

Agent based modeling and simulation (ABMS) is a new modeling approach that has gained increasing attention over the past 10 years. Some contend that ABMS "is a third way of doing science" and could augment traditional deductive and inductive reasoning as discovery methods. This type of simulation is characterized by the existence of many agents who interact with each other with little or no central direction. Based on the mentality of Agent, ABMS simulates the complex systems, and receives the action of the complex systems by describing the interaction among the agents.The emergent properties of an agent-based model are then the result of "bottom-up" processes, rather than "top-down" direction.Based on agent a simulation model of bus rapid transit system was developed. The passengers, buses and signal lights were abstracted as different agents in the model, and vehicle scheduling agent and station management agent were also introduced. The situation of bus rapid transit system was simulated through the interaction among agents. The station management agent was the ligament between the bus agent and the passenger agent. Each station corresponds to a station management agent which is responsible for managing a queue of passenger agents. Vehicle scheduling agent is responsible for the production and scheduling of buses and accepts the messages from bus agents and station management agents, according to the initial set signal light agents alternate the state.The public traffic company develops different time-schedules under the peak and normal of passenger flow. Such a scheme is simple, but it is difficult to resolve when it appears that passengers "merge" in a few stations. In order to reduce passenger waiting time and benefit the public traffic company, a vehicle scheduling algorithm based on dynamic adjustment is proposed. The mean idea of the algorithm is that if the phenomenon of passengers "emerging" in one station appears, a run is in the following:first, the time of direct access to the station from the originating station is forecasted; second, the number of the buses which have not arrived at the station is calculated; third, the maximum capacity for that buses is gained; forth, the number of needing buses is actually calculated; last, the buses move to the station directly with faster than normal.The model based on the Netlogo platform and simulated the Jinan BRT 1. The experiment and analysis indicate the model not only can simulate the situation of Jinan BRT 1, but also can decrease the waiting time of passengers. But the model assumes that the arrival rate of passengers who arrivered at the station and the number of geting-off station are both randomly generated, which have some differences with the reality. In addition, there are multiple bus lines shared the case of certain lanes in reality, so the Simulation and optimization with many bus lines overlapped is further study of this subject.