Travel behavior and mode choice are closely related to how travel demand is addressed. Those who choose to use a bike-share system rely on the availability of a bike when they arrive at a station. This study simulates the existing NYC bike-share program to estimate customers’ wait time and the number of daily bike trips as performance measures. A truck fleet service is added to the simulation environment to transfer the bikes from the high-demand to low-demand stations as a performance improvement strategy. A 24-h simulation reveals that for 65,000 daily bike trips, on average, a user waits half a minute to pick up a bike and 1.5 min to find a vacant return spot. As a result, about 6% of customers change their minds using the program due to the longer than expected wait time. The results show that with a 10-truck fleet as an optimal number of trucks, the wait time reduces by 72%, while the number of daily trips increases by 2.4%. The simulation results, along with a benefit-cost analysis, help balance supply and demand efficiently while improving customer service satisfaction.
A Discrete-Time Simulation Model for New York City Bike-Share System
International Conference on Transportation and Development 2022 ; 2022 ; Seattle, Washington
2022-08-31
Conference paper
Electronic Resource
English
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