Agent Based Simulation of the Movement of Bus Rapid Transit Fleets (BRT)

Today, ground transportation systems are facing a major challenge which has come to be known as traffic congestion. Since traffic and congestion are complex and dynamic phenomena, it is difficult and sometimes impossible to apply conventional mathematical models on them. Thus agent-based technologies with high compatibility with the afore-mentioned characteristics can be used to model the phenomenon of congestion and detect effective congestion mitigation/aggravation parameters. Considering the role of bus rapid transit in the transportation of passengers, mitigation of congestion and reduction of passenger waiting time and travel time are among the objectives of the present study. Therefore, agent-based simulation of the movement of bus rapid transit (BRT) fleets is used to achieve the afore-mentioned goal. In the present study, NetLogo is used to code the model and run the simulation. Three different scenarios were taken into account in this study. Change of effective factors in each of the three scenarios led to significant improvements in the BRT performance analysis results. Finally, after general analysis and comparison of different scenarios, results and suggestions were presented to improve the performance of BRT fleets. In the attempt to achieve the goals (i.e. reduction of passenger waiting time at stations and reduction of travel time), the bridge scenario was found to be more suitable and effective than the smart light and status quo scenarios.