EAGER: A Living Lab for Smartphone-based Parking Management Services

寻找停车位是许多司机面临的真正难题，尤其是在城市地区。基于智能手机的高级停车管理服务可以提供停车位的实时可用性和价格信息，并指导驾驶者打开停车位。这个早期概念探索性研究资助（EAGER）项目将探索这种基于智能手机的停车管理服务的潜力，以加深对旅行者停车行为的理解，并推进停车解决方案建模和评估的分析基础和方法。这项工作整合了各种利益相关者（个人旅行者、停车行业、交通机构和技术开发商）和多种技术（从用户和机构获取实时数据，预测未来的停车位可用性，通过智能手机应用程序提供信息和指导，并通过分析和模拟模型分析停车游戏）。作为一个生活实验室，该项目将提供独特的机会来收集停车搜索行为的数据，发现基于智能手机的停车管理服务的新兴场景，并评估这些系统在真实环境中的影响。此外，它填补了使用实际数据验证和校准理论和仿真模型的关键空白。通过吸引终端用户、当地运输机构、行业和技术开发人员，它将产生关于各种利益相关者如何相互关联和相互作用的新知识。该项目旨在促进STEM领域的教育和人力资源开发，为停车信息基础设施提供资源，并改善停车用户体验。该项目包括三个主要活动：1)分阶段部署原型Android停车引导应用程序。该团队将与亚利桑那州立大学（ASU）停车和交通服务部门密切合作，在位于亚利桑那州坦佩市中心的亚利桑那州立大学主校区周围实施三个阶段的试点部署。这项工作将吸引最终用户、当地交通机构、行业和技术开发商。2)模型验证与验证。通过智能手机应用程序，收集个人旅行者停车偏好的数据，并用于验证随机停车模型。停车行为模型/参数也将被检查，以校准基于代理的仿真工具。3)评估利益相关者体验的改进。对于个人旅行者来说，寻找停车位的过程将根据一系列性能指标（如巡航时间、访问的停车设施数量、巡航速度等）进行量化。对于机构来说，由巡航停车引起的拥堵将使用从工作和交通网络模型（包括现有模型）收集的真实数据进行评估。

Searching for parking is a real struggle faced by many drivers, especially in urban areas. Smartphone-based advanced parking management services may provide information on real-time availability and prices of parking spaces and guide motorists to open parking spaces. This EArly-concept Grant for Exploratory Research (EAGER) project will explore the potential of such smartphone-based parking management services to deepen understanding of travelers' parking behaviors and advance the analytical foundations and methodologies for modeling and assessing parking solutions. This work integrates various stakeholders (individual travelers, parking industry, transportation agencies, and technology developers) and multiple technologies (retrieving real-time data from both users and agencies, predicting future parking availability, providing information and guidance through smartphone application, and analyzing parking games via both analytical and simulation models). As a living lab, this project will provide unique opportunities to collect data on parking search behaviors, discover emerging scenarios of smartphone-based parking management services, and assess the impacts of such systems in a real environment. Additionally, it fills a critical gap in validating and calibrating the theoretical and simulation models using real data. By engaging end users, local transportation agencies, industry, and technology developers, it will generate new knowledge regarding how various stakeholders are interrelated and interact with each other. The project is expected to promote education and human resources development in STEM fields, contribute resources towards parking information infrastructure, and improve user experience in parking.The project involves three main activities: 1) Staged deployment of a prototype Android parking guidance application. The team will work closely with Arizona State University (ASU) Parking and Transit Services to implement a three-stage pilot deployment around the ASU main campus located in downtown Tempe, AZ. This work will engage end users, local transportation agencies, industry, and technology developers. 2) Model validation and verification. Through the smartphone application, data on individual travelers' parking preferences will be collected and used to validate the stochastic parking models. Parking behavior models/parameters will also be examined in order to calibrate an agent-based simulation tool. 3) Assessing improvement of stakeholder experience. For individual travelers, the process of searching for parking will be quantified in terms of a range of performance measures (such as cruising time, number of parking facilities visited, cruising speed, etc.). For agencies, the congestion caused by cruising for parking will be assessed using a mix of real data collected from the work and transportation network models, including existing models.