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Advances in Travel Time Uncertainty for Transportation Network Optimization

Yiyan Niu

Abstract


Travel time uncertainty poses a critical challenge for optimizing transportation networks, especially in time-sensitive scenarios
like commuting and logistics. Key advancements involve developing reliability indicators such as Reliability Premium, Mean Excess Travel
Time, scheduling-based utility functions, and entropy-based metrics. Optimization strategies have evolved from mean-variance models to
stochastic user equilibrium formulations, bi-level programming, and reinforcement learning. Behavioral modeling now incorporates risk attitudes, multi-criteria preferences, and strategic user interactions. Future research should focus on multimodal coordination, real-time adaptive
control, and personalized routing under uncertainty.

Keywords


Travel Time Uncertainty; Transportation Network Optimization; Robust Optimization; Stochastic Traffic Assignment; Risk-Aware Behavioral Modeling

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References


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DOI: https://doi.org/10.18686/utc.v11i2.272

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