Optimal capacity sizing of park-and-ride lots with information-aware commuters

• 成果类型: Article
• 署名作者: Wang, Xinchang; He, Qie
• 署名单位: Washington State University; University of Minnesota System; University of Minnesota Twin Cities
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.14053
• 发表日期: 2023
• 页码: 3614-3633
• 关键词: equilibrium; information-aware commuters; Multinomial logit model; optimal capacity sizing; park and ride

摘要

We study capacity sizing of park-and-ride lots that offer services to commuters sensitive to congestion and parking availability information. The goal is to determine parking lot capacities that maximize the total social welfare for commuters whose parking lot choices are predicted using the multinomial logit model. We formulate the problem as a nonconvex nonlinear program that involves a lower and an upper bound on each lot's capacity, and a fixed-point constraint reflecting the effects of parking information and congestion on commuters' lot choices. We show that except for at most one lot, the optimal capacity of each lot takes one of three possible values. Based on analytical results, we develop a one-variable search algorithm to solve the model. We learn from numerical results that the optimal capacity of a lot with a high intrinsic utility tends to be equal to the upper bound. By contrast, a lot with a low or moderate-sized intrinsic utility tends to attain an optimal capacity on its effective lower bound. We evaluate the performance of the optimal solution under different choice scenarios of commuters who are shared with real-time parking information. We learn that commuters are better off in an average choice scenario when both the effects of parking information and congestion are considered in the model than when either effect is ignored from the model.