Travel time stochasticity in transportation networks is a key factor driving route choice behavior. Conventional models fail to account for heterogeneous risk preferences and travel time reliability, showing significant practical limitations. Stochastic Dominance (SD) theory offers a unified, utility-free framework for uncertain route choice via partial order characterization of random travel times, and has gained extensive attention in traffic optimization. This paper systematically reviews SD-based route choice models and algorithms, sorts out model construction under different network environments, summarizes core algorithm design and optimization strategies, and clarifies their applicability. Finally, it summarizes research limitations and prospects future directions, providing reference for relevant theoretical research and engineering applications.
Niu Yiyan (Thu,) studied this question.