Bayesian Optimization for High-dimensional Urban Mobility Problems
Seongjin Choi · Sergio Rodriguez · Carolina Osorio
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.
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