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

Mei, Zhenyu; Wei, Daqin; Ding, Wenchao; Wang, Dianhai; Ma, Dongfang

doi:10.1016/j.cie.2023.109660

Cited by 1 publication

(2 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Conversely, in the latter scenario, the main track remains underutilized while the fast track becomes congested. These findings align with the research conducted by Mei and Qin, with the exception that their vehicle reservations were substituted with passenger reservations [36,37].…”

Section: Simulation Resultssupporting

confidence: 88%

“…Furthermore, when the reservation proportion falls within an appropriate range, it reduces travel time [35]. When Mei et al studied reserved parking spaces, they found that when the proportion of reserved vehicles is not high, congestion in popular parking lots may intensify [36]. Qin et al [37] found that 56% of travelers chose to make parking reservations during the travel process.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Increasing Passenger Efficiency and Minimizing Infection Transmission in Chinese Metro Stations during COVID-19: A Simulation-Based Strategy Analysis

Xue,

Zhang,

Shiwakoti

2023

Systems

View full text Add to dashboard Cite

This study addresses the challenging problem of increasing passengers’ travel efficiency while lowering the infection transmission risk at metro stations during COVID-19 pandemic. To achieve this objective, we deploy Anylogic software and formulate an infection risk model. As a case study, this study focuses on a transfer metro station in Xi’an, China. Firstly, by utilizing Anylogic software, three distinct strategies are simulated: flow-control fences, travel reservation, and the collaborative use of travel reservations and flow-control fences. Secondly, the passenger density and average dwell time under these strategies are assessed while constructing an infection risk model to quantify the risk faced by passengers. Thirdly, when compared to the absence of any strategy, the results are as follows: (1) The flow-control fences strategy: implementing flow-control fences can effectively reduce the risk of passenger infection when the length of the flow-control fences is fixed at 47.5 m, but comes at the cost of a 20.15% decrease in passenger travel efficiency; however, excessively long flow-control fences will neither alleviate congestion nor reduce the infection risk. (2) The travel reservation strategy: the adoption of travel reservations, along with a fast track for reserved users, when the reservation proportion is 40%, leads to a remarkable 29.05% improvement in travel efficiency and reduces the risk of passenger infection by 67.12%. (3) The combined strategy: the combined utilization of travel reservations and flow-control fences enhances travel efficiency by 15.80% and reduces the risk of passenger infection by 56.77% when the reservation proportion is set at 30%. When the reservation proportion is between 10 and 30%, its infection risk reduction effect is better than that of the travel reservation strategy, but this is not necessarily true for their effects on travel efficiency. Finally, this study was compared to an existing study that proposed a new strategy by combining travel reservations with departure intervals, analyzing the effect of the implementation of the strategy with different departure intervals. The findings from this study have implications for developing appropriate strategies to optimize passenger flow without significantly compromising the transmission of infection risk during the pandemic.

show abstract

Section: Simulation Resultssupporting

confidence: 88%