A stochastic-robust MPC framework with Nested Benders Decomposition for EAMoD reduces median waiting times by up to 36% and electricity costs by over 35% versus baselines in city simulations.
Understanding charging dynamics of fully-electrified taxi services using large-scale trajectory data.Transportation Research Part C: Emerging Technologies, 143:103822, 2022
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Combined Stochastic and Robust Optimization for Electric Autonomous Mobility-on-Demand with Nested Benders Decomposition
A stochastic-robust MPC framework with Nested Benders Decomposition for EAMoD reduces median waiting times by up to 36% and electricity costs by over 35% versus baselines in city simulations.