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Modeling on-demand public transit: A Markovian continuous approximation approach

Dr. Alexander Vinel
Auburn University
Friday, February 10, 2023
2:15-3:15pm Tickle 410
Abstract

With recent advances in mobile technology, public transit agencies around the world have been actively experimenting with new transportation modes, many of which can be characterized as on-demand public transit. Design and efficient operation of such systems can be particularly challenging because they often need to carefully balance demand volume with resource availability. The talk will discuss a family of models for on-demand public transit that combine a continuous approximation methodology with a Markov process. Our goal is to develop a tractable method to evaluate and predict system performance, specifically focusing on obtaining the probability distribution of performance metrics. This information can then be used in capital planning, such as fleet sizing, contracting, and driver scheduling, among other tasks. We will discuss the analytical solution for a stylized single-vehicle model of first-mile operation, and then describe several extensions to the base model. We will also review some computational experiments and a case study, based on a real-world pilot on-demand public transit project in a major U.S. metropolitan area. We will then outline connections between the developed modeling approach and more general methodologies, such as semi-Markov models, and how continuous approximation idea can improve applicability of such techniques in future research.

Bio

Alexander Vinel is an associate professor in the Department of Industrial and Systems Engineering at Auburn University. He joined the ISE department in 2015 after completing a Ph.D. in industrial engineering from the University of Iowa. Dr. Vinel also holds M.S. and B.S. degrees in applied mathematics and physics from Moscow Institute of Physics and Technology. His research and teaching interests focus on stochastic operations research, including optimization methods, decision making under uncertainty and data analytics, such as methodologies for measuring and optimizing risk and approaches to data-driven optimization. Specific application areas of interest include portfolio optimization to reduce intermittency in renewable energy, data analytics in additive manufacturing, optimization for occupational safety and stochastic models in transportation systems. His research has been funded by National Science Foundation (NSF), Air Force Office of Scientific Research (AFOSR), Federal Aviation Administration (FAA), and Air Force Materiel Command (AFMC). Dr. Vinel serves as an Area Editor for peer-reviewed academic journal Computers and Operations Research. He was selected as the Outstanding Faculty Member in the Industrial and Systems Engineering Department at Auburn in 2016, and is a co-author on the publication selected for the Best Paper Award for the journal Ergonomics in 2021.

https://tennessee.zoom.us/j/95898278848