Strategic User Equilibrium Model Incorporating Both Demand and Capacity Uncertainty

摘要

In this paper, we present an extension of a novel equilibrium based assignment model originally proposed by Dixit et al (2013), which addresses day-to-day volatility in travel conditions resulting from short-term demand uncertainty, by incorporating the impact of capacity uncertainty. Specifically, the demand and capacity variability are represented independently using assumed known distributions. The proposed model is based on the premise that users gain knowledge of the demand and capacity distributions through their past travel experience. Using this knowledge, users seek to minimize their expected travel time and choose a strategy (i.e., travel route) accordingly. They then follow this strategy day10to-day, independent of the realized traffic demand and capacity. The network may therefore result in non-equilibrium assignment patterns, which is consistent with the lack of observed equilibrium in field networks. The model is mathematically formulated, expressions for the analytical link travel times and corresponding variability are derived and the uniqueness of the assignment solution regarding link flows is proven. Numerical analysis is conducted to demonstrate the performance and reliability of the model by comparing the analytical results with simulation based assignment.