Thursday, November 4, 2021 @ 12:00PM (EDT)
About the Webinar:
Urban parcel delivery has emerged as a high growth market, fueled by burgeoning e-commerce. Due to the COVID-19 pandemic, beginning in March 2020, many regions in the United States experienced rapid changes in travel patterns, which led to an increase in the use of retail purchase pick-up and delivery services. As a result of the large volume of parcel delivery, we are seeing an increasing number of delivery trucks and vans entering and driving around cities every day, contributing to greater traffic congestion, air pollution, noise, road deterioration, and safety concerns. For example, when unable to locate a parking spot near the destination, Delivery Service Provider vehicles may sometimes park in street lane, thereby creating a bottleneck. With rapid technological change in parcel delivery system, the conventional model of a dedicated delivery person operating a van is shifting to new classes of vehicles such as drones, autonomous ground vehicles, cargo bikes and non-motorized vehicles, and combined with new delivery models featuring crowdsourcing, parcel lockers, and mobile lockers. Multiple modes can be used synergistically to manage urban road congestion from parcel delivery system, for example combining trucks and UAV. In order to attain the full potential of these changes to reduce costs and increase convenience, it is necessary to develop a complementary set of management strategies that will enable the next-generation parcel delivery system to mitigate current traffic congestion problems and avoid creating new ones. Against this backdrop, in this seminar we will focus on three main topics. First, we will review projections of future growth in urban parcel delivery. Second, we will present a model of urban congestion that is sensitive to parcel delivery activities, including double parking, and employ the model to understand the congestion implications of parcel delivery growth in dense urban areas. Finally, we will assess the potential of drone delivery to operate at a sufficient scale to significantly reduce surface vehicle delivery traffic and its attendant congestion impacts.
About the Presenter:
Mark Hansen is a Professor of Civil and Environmental Engineering at the University of California, Berkeley. He graduated from Yale with a Bachelor’s degree in Physics and Philosophy in 1980, and has a PhD in Engineering Science and a Masters in City and Regional Planning from UC Berkeley. Prior to graduate school, Dr. Hansen worked as a physicist at the Environmental Protection Agency. Since joining the Berkeley faculty in 1988, he has led transportation research projects in urban transportation planning, air transport systems modeling, air traffic flow management, aviation systems performance analysis, aviation safety, aviation environmental analysis, and air transport economics. He has taught graduate and undergraduate transportation courses in economics, systems analysis, planning, probability and statistics, and air transportation. Professor Hansen is the Berkeley co-director of the National Center of Excellence in Aviation Operations Research, a multi-university consortium sponsored by the Federal Aviation Administration. He is former Chair of Transportation Research Board Committee AV-060, Airport and Airspace Capacity and Delay. He has served as Associate Editor of Operations Research and Transportation Research E.
Ang Li is a fourth-year doctoral student, advised by Prof. Mark Hansen, in Transportation Engineering at UC Berkeley. Her research interest focuses on Unmanned Aircrafts Systems Traffic Management (UTM), and regional Air Traffic Management (ATM) using operations research and machine learning techniques. She works on traffic management and resource allocation of UAV- based parcel delivery in low-altitude urban airspace, and multimodal strategies for mitigating delay from urban parcel delivery. She also had research experience in regional air traffic management in Multiple Airport Regions. Regarding teaching interest, Ang has co-developed the curriculum of the course ‘Aviation Data Science’ taught at UC Berkeley, and served as graduate student instructor for core transportation courses.
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