The Demand for the Curb and Optimal Allocation: Data, Technology, Research and Experimentation
Abstract
The emergence of various new forms of urban mobility services in recent years is leading to new pressures on curbside space. Municipalities, the entities typically responsible for managing the curbside, are in many instances handling these growing pressures by reallocating portions of the curbside away from traditional uses (such as metered and residential parking) in favor of uses such as ridehailing, scooter and bike-share corrals. However, such actions are being undertaken on an ad-hoc basis, due to the rapidly growing complexity of the curbside and the lack of standard analytical approaches. This lack of analytical capability is due to the traditional focus of transportation network modeling being focused predominantly on the interaction of supply and demand on links and nodes, with limited focus on link edges (the curbside). In this presentation we address this research need by proposing a framework for modeling inter-modal competition for curbside space, inspired by the classical Bid-Rent Model of urban land use, intended to support curb managers to move towards maximizing the aspects of economic welfare that relate to curb access. In the bi-level model, choices made by the curbside manager impact travelers’ mode choices, and vice versa. We then present a sample numerical case study to demonstrate the properties of the proposed model, showing its tractability, flexibility, and intuitive sensitivity to systematic variation in inputs. This presentation demonstrates the type of adaptive and evolving approach needed to maximize benefits from increasingly dynamic curb management strategies. The presentation also covers the importance of real-world data – supply (infrastructure) or the “what’s at the curb?” and demand or the “what’s happening at the curb? Who uses the curb?” and discusses future research needs, technology applications and field experimentation to advance this line of inquiry for a more sustainable transportation system.
The Demand for the Curb and Optimal Allocation: Data, Technology, Research and Experimentation
Category
Policy, Decision-Making, Data
Description
Presenter: Alejandro Henao
Agency Affiliation: NREL
Session: Technical Session B2: Modeling Energy Impacts of Future Mobility
Date: 6/1/2022, 10:30 AM - 12:00 PM
Presenter Biographical Statement: Dr. Alejandro Henao is a research scientist with the Center for Integrated Mobility Sciences at the National Renewable Energy Laboratory (NREL). He first joined NREL as a postdoctoral researcher in March 2017. Dr. Henao is a noted expert in the research associated with ridesourcing (e.g., Uber) related impacts. His passion for transportation, people, cities and the environment has driven him – literally – to explore the field first-hand. He brings a unique firsthand perspective on ridesourcing issues through his time driving for Uber and Lyft as part of his PhD research. His current research focuses on the synergies between transportation and energy, with an emphasis on data collection strategies and innovation to answer key research questions including impacts of emerging modes and future mobility, curb management, and performance metrics for mobility and energy efficiency. With a strong background in engineering, data & research, and a diverse skill set; he continues to work in topics that will meaningfully influence the future of mobility. Dr. Henao serves on the Transportation Research Board, National Academy of Science, Standing Committee on Emerging and Innovative Public Transport and Technologies, and he has also served as a co-chair of the Mobility Choice Initiative in Colorado and other initiatives. He has numerous publications and continuously presents at national and international conferences. Prior to obtaining his PhD and working as a research assistant and lecturer at the University of Colorado, he worked as a structural engineer and construction management engineer at a few firms in Colorado. He is originally from Cali, Colombia and have live in Colorado and the Pacific Northwest after moving to the US.