Optimizing Pricing Policies in Park-and-Ride Facilities: A Model and Decision Support System with Application

Park-and-ride facilities are of major importance to the attractiveness and operation of modern transit systems because travelers tend to prefer public transportation when they are able to combine the use of these facilities with their private vehicles. Among those elements examined when developing/operating a park-and-ride facility is the pricing policy to be established for its users. Indeed, the pricing policy is among those tools that can aid transportation agencies in managing park-and-ride facilities, by providing incentives or disincentives of parking for various categories of users. This paper contributes to the literature by offering a new approach for obtaining optimal pricing schemes for a parking facility, with respect to its financial viability. In particular, a financial analysis model is combined with a genetic algorithm for determining the optimal pricing parameters for park-and-ride facilities. The model is applied for a shared-use, park-and-ride facility of the Athens metro network in Greece. Results of the computational study indicate that the model can offer near optimal pricing schemes in a short amount of time. Also, a decision support system is developed for incorporating the model in a user friendly computerized framework.

摘要当私家车的使用可与公共交通结合时，人们会更倾向于乘坐公共交通出行。因此，P+R（停车换乘系统）在为公共交通吸引客流的同时也对公共交通的运营起到重要的作用。在建立和运营P+R系统时，制定合理的用户收费政策是诸多影响因素之一。事实上，收费政策作为调节手段之一，利用其鼓励或约束停车场的各类用户，将有助于交通部门管理和经营P+R设施。基于社会经济水平，本文为确定停车设施最优定价方案提供了一种新方法。结合遗传算法，本文利用财务分析模型确定了P+R设施最优定价方案参数。该模型应用于希腊雅典地铁网络的P+R设施。结果表明，该模型可在短时间内提供近似最优定价方案。另外，本文还在方便用户的计算机框架下结合该模型开发了相应决策支持系统。