TRAFFIC SIMULATION MODEL FOR ACCESS ROADS TO TRANSFER STATIONS CONSIDERING STOP POSITION CHOICE OF KISS-AND-RIDE VEHICLES

IRYO-ASANO, Miho · 2015 · Crossref

DOI: 10.2208/jscejipm.71.i_931

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Summary

This paper addresses the lack of understanding regarding how Kiss-and-Ride (K&R) vehicles choose stop positions in station plazas and how these choices contribute to traffic congestion. While buses and taxis follow designated stops, K&R vehicles select stops freely, often leading to inefficient space usage and congestion that spills over into adjacent streets. The study aims to clarify the relationship between stop position choice behaviors—specifically distinguishing between drop-off and pick-up scenarios—and queue formation patterns, ultimately constructing a quantitative simulation model to reproduce these phenomena. The research methodology combines field observations with theoretical modeling. Data was collected via video observation at the Owa-Ichinomiya Station plaza, a suburban station with high commuter traffic. The analysis focused on vehicle trajectories, stop positions, and dwell times during morning (drop-off dominant) and evening (pick-up dominant) peaks. The authors identified that "double parking" (stopping on the island side behind a vehicle already stopped on the curb side) is a primary cause of congestion. To model this, the authors formulated a utility maximization framework where drivers minimize a cost function comprising passenger walking time, vehicle travel time to the stop, and the psychological burden of delaying subsequent traffic. This model was implemented in a traffic simulation to test its ability to reproduce observed congestion patterns. The findings reveal distinct behavioral patterns based on traffic demand and time of day. In the morning, drop-off vehicles concentrate near the station entrance; despite available curb space, short dwell times encourage double parking, which blocks the lane and extends queues to the plaza entrance. In the evening, pick-up vehicles distribute more evenly along the curb, but short-duration vehicles still engage in double parking near the entrance, causing similar blockages. The simulation results closely matched observed data regarding the proportion of vehicles choosing curb-side stops and the frequency and duration of congestion cycles. Specifically, the model successfully reproduced the mechanism where double parking by short-dwell vehicles triggers queue extension, even when curb space is theoretically available. The significance of this work lies in providing a quantitative tool for evaluating station plaza design and operation. By modeling the specific behavioral drivers of K&R vehicles, particularly the tendency toward double parking, planners can better predict congestion and assess the impact of layout changes or traffic management strategies. The study highlights that current design guidelines, which focus on space supply, fail to account for these behavioral dynamics. Future work is suggested to incorporate geometric constraints like curves and barriers, as well as interactions with buses and taxis, to enhance the model's applicability to more complex plaza environments.

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• traffic density