ERI: Decision Models for Designing and Managing the Curb Spaces in Urban Mobility Systems

作为智能城市倡议的一部分，该工程研究启动(ERI)奖将专注于城市路缘空间的管理。随着新的移动服务的到来和对货物递送需求的增加，路边空间发展非常迅速。目前，路边停车位不仅被用于停车，还被用于拼车服务的上落客区、共享单车或滑板车停车架、网上购物公司的送货区等。出于有效使用路边停车位的需要，这项研究旨在最大化三个核心指标：可获得性(确保车辆可以找到路边停车位)、及时性(确保尽快进入路边停车位的能力)，以及所有居民的经济机会(城市不仅从停车而且从路边停车位的其他使用中获得收入的能力)。更广泛地说，这项研究有可能减少二氧化碳排放，减少交通时间，减少交通危险，由于更准时的交付而提高业务满意度，并减少拥堵。这项研究还将积极吸引女性和少数族裔研究生和本科生，并促进工程教育。该项目利用与密歇根州大急流市的合作，获得有意义的真实世界数据，用于验证模型和得出解决方案。它的目的是创建严格的分析方法，以促进对城市机动性中车辆动力学的更广泛了解，并为城市路缘空间的运营设计提供信息。本研究的具体任务包括：(1)开发用于路缘空间管理的随机动态容量分配和定价模型；(2)扩大容量和需求的范围，以包括除停车外的所有可能的路缘空间用途(例如，上/落、上/卸)；(3)测试新的动态定价模型的运营和财务可行性，该模型考虑了具有不同需求的所有不同的路缘用途。这项研究将导致移动系统建模和解决方案方法的进步。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Engineering Research Initiation (ERI) award will focus on the management of the curb spaces in cities as part of the smart city initiative. Curb spaces have evolved very rapidly with the arrival of new mobility services and increased needs for goods delivery. Currently, curb spaces are not only used for parking but also used for the pick-up/drop-off zone of ridesharing services, bike-share or scooter parking racks, delivery zones for online shopping companies, etc. Motivated by the need for effective use of curbs, this research aims to maximize three core metrics: access (ensuring that vehicles can find a curb space), timeliness (the ability to secure access to curb space as soon as possible), and economic opportunity for all residents (the ability of the city to have earnings not only from the parking but also from the other uses of the curb space). More broadly, this research has the potential to result in reduced carbon dioxide emissions, less time spent in traffic, decreased traffic hazards, increased business satisfaction due to more on-time deliveries, and less congestion. This research will also actively engage female and minority graduate and undergraduate students and promote engineering education.This project takes advantage of collaborating with the City of Grand Rapids in Michigan to acquire meaningful real-world data for validating the models and deriving solutions. It aims to create rigorous analytical approaches to promote a broader understanding of the vehicle dynamics in urban mobility and inform the operational design of curb spaces in the city. The specific tasks of this research include: (1) development of stochastic dynamic capacity allocation and pricing models for curb space management; (2) expanding the purview of capacity and demand to include all possible uses of curb space other than parking (e.g., pickup/drop-off, loading/ unloading); and (3) testing the operational and financial viability of new dynamic pricing models that consider all different curb uses with varying demands. This research will lead to advances in mobility systems modeling and solution approaches.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.