Multi-agent simulation for multi-mode travel policy to improve park and ride efficiency

Abstract

The efficiency of the existing park and ride transfer system is often restricted by the supply level of public transport and parking shortage. We aim to analyze multiple policy scenarios such as public transport supply and parking reservation through simulation to provide operable suggestions for urban traffic managers. So, an agent-based model (ABM) is established by us to simulate a multi-mode network that includes roads, buses, metro, and walking. Through this network, the whole travel process of travellers’ parking, transferring to public transport, and then walking to their destination can be simulated. Taking Suzhou Guanqian Street Commercial District as a case shows that compared with reducing the existing public transport fares, reducing the waiting time can attract car travellers to choose park and ride. Under the coexistence of reserved and non-reserved parking vehicles, with the increase in the proportion of reservations, the system can reduce cruising-for-parking and improve the traffic environment in the downtown area. In addition, the combination strategy simulation is employed to investigate the effects of various strategies on the urban traffic system. This approach offers a basis for policymakers to formulate informed decisions.