Optimal time-differentiated pricing for a competitive mixed traditional and crowdsourced event parking market
Optimal time-differentiated pricing for a competitive mixed traditional and crowdsourced event parking market
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DOI：
10.1016/j.trc.2021.103409
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发表时间：
2021-11
期刊：
影响因子：
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通讯作者：
Hossein Fotouhi;Elise Miller-Hooks
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文献类型：
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作者：
Hossein Fotouhi;Elise Miller-Hooks
提出了一个基于事件的停车定价问题，即众包事件停车市场定价问题，其中停车场所有者和其他愿意出租私人车位的人竞争吸引正在寻找可用停车位的司机。每个停车位所有者的问题被建模为一个双层计划，其中上层停车库、个人和整合者(参与者)竞争客户，根据底层追随者的反应设定价格以最大化收入。较低级别的追随者根据他们从车位获得的效用来选择他们的停车位置，这是车位距离目的地、停车费和拥挤程度的函数。价格是根据预订时间而定的。基于预订时间的定价可以为后来者提供差异化的价格，要么是在预计空间过剩时以较低的价格吸引最后一分钟的客户，要么是以较高的价格(如果预计几乎没有空位)的形式。给出了众包活动停车市场定价问题的多周期、带均衡约束的随机均衡问题(EPEC)公式，并提出了求解带均衡约束的个体参与者数学规划(MPECs)的对角化方法和嵌入梯度上升算法。供给侧和需求侧的不确定性都被明确建模。解决方案为每个停车设施提供由预订时间设定的具有竞争力的停车价格，无论该设施涉及大型停车库还是单个停车位所有者。通过数值实验来说明所提出的概念，并评估众包停车位对停车市场的潜在影响。结果显示，当众包停车位占停车市场的7%时，社会福利增加了5%以上。额外的数值实验结果表明，忽略随机性会导致所有停车主的收入损失。开发的技术旨在促进现有和新的停车设施所有者参与众包活动停车市场。
An event-based parking pricing problem, the Crowdsourced Event Parking Market Pricing Problem, is proposed wherein parking lot owners and others who are willing to rent out privately owned spaces compete to attract drivers who are looking for available parking spaces. Each parking location owner’s problem is modeled as a bi-level program, where the upper-level parking garages, individuals and consolidators (the players) compete for customers, setting their prices to maximize revenue given the response of the lower-level followers. The lower-level followers choose their parking locations based on the utilities they derive from the spaces, which is a function of the proximity of the spaces to their destinations, parking fees and crowdedness. Prices are set as a function of the time of reservation. Reservation-time based pricing enables price differentiation for late comers either in the form of lower prices to attract last-minute customers when excess spaces are anticipated or higher-pricing if few spaces are expected to remain empty. A multi-period, stochastic Equilibrium Problem with Equilibrium Constraints (EPEC) formulation of the Crowdsourced Event Parking Market Pricing Problem is presented, and a diagonalization method with embedded gradient ascent approach for solution of individual player Mathematical Programs with Equilibrium Constraints (MPECs) is proposed for its solution. Both supply- and demand-side uncertainties are explicitly modeled. Solutions provide competitive parking prices set by reservation time for each parking facility, whether the facility involves a large parking garage or single parking space owner. Numerical experiments were conducted to illustrate the proposed concepts and assess the potential impact of crowdsourced parking spaces on the parking market. The results show that social welfare increases by more than 5% when crowdsourced parking locations account for 7% of the parking market. Results from additional numerical experiments show that ignoring stochasticity results in revenue loss for all parking owners. The developed techniques aim to facilitate existing and new parking facility owners to participate in crowdsourced event-parking markets.