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DTSTART;TZID=America/New_York:20220708T150000
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UID:77366-1657292400-1657296000@c2smart.engineering.nyu.edu
SUMMARY:Individual Path Recommendation Under Public Transit Service Disruptions Considering Behavior Uncertainty and Equity
DESCRIPTION:During a public transit service disruption\, passengers usually need path recommendations to find alternative routes. In this webinar\, MIT PhD Candidate Baichuan Mo will discuss his proposal for a mixed-integer programming (MIP) formulation to model the individual-based path (IPR) recommendation problem during PT service disruptions with the objective of minimizing system travel time and respecting passengers’ path choice preferences. Passengers’ behavior uncertainty in path choices given recommendations and their travel time equity are also considered. He models the behavior uncertainty based on passenger’s prior preferences and posterior path choice probability distribution with two new concepts: epsilon-feasibility and gamma-concentration\, which control the mean and variance of path flows in the optimization problem. The IPR problem with behavior uncertainty is solved efficiently with Benders decomposition. A post-adjustment heuristic is used to address the equity requirement. The proposed approach is implemented in the Chicago Transit Authority (CTA) system with a real-world urban rail disruption as the case study. Results show that the proposed IPR model significantly reduces the average travel times compared to the status quo and outperforms the capacity-based benchmark path recommendation strategy. \n \nBaichuan Mo is a Ph.D. student in the transportation program at MIT. He completed his dual Master’s degree in Transportation and Computer Science at MIT in 2020. Prior to joining MIT\, he got a B.E. degree from the Department of Civil Engineering\, Tsinghua University\, awarded with the Tsinghua Presidential Scholarship. \nBaichuan’s main research interest is data-driven transportation modeling\, demand modeling\, and machine learning. His master thesis was on the network performance model for urban rail system monitoring. His current research focuses on unplanned incident analysis and management in urban rail systems\, sponsored by Chicago Transit Authority (CTA).
URL:https://c2smart.engineering.nyu.edu/event/individual-path-recommendation-under-public-transit-service-disruptions-considering-behavior-uncertainty-and-equity/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Big Data & Planning for Smart Cities
ATTACH;FMTTYPE=image/png:https://c2smart.engineering.nyu.edu/wp-content/uploads/2022/06/C2SMART-Seminar-Individual-Path-Recommendation-Under-Public-Transit-Service-Disruptions-Considering-Behavior-Uncertainty-and-Equity.png
ORGANIZER;CN="C2SMART":MAILTO:c2smart@nyu.edu
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