Bayesian Optimization for High-dimensional Urban Mobility Problems
Keywords: Urban Mobility, Bayesian Optimization, Demand Estimation, Benchmark
TL;DR: Benchmark high-dimensional urban mobility problem for Bayesian Optimization
Abstract: This workshop talk presents a class of important optimization problems that arise in the design of urban mobility digital twins. It presents the open questions in the field and identifies key research opportunities for the communities of Bayesian optimization, uncertainty quantification, and inverse optimization. It shares the code to tackle a travel demand estimation problem for two road networks: an illustrative toy network and the San Francisco metropolitan network.
Submission Number: 73
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