Discrete traffic network design model considering risk attitude of decision maker and users

Abstract

Traffic network design is one of the core contents of traffic planning. The traditional transportation planning is based on deterministic assumptions and decision-making rules, resulting in unreasonable factors in the planning scheme. This study aims to build uncertain transport network design method with uncertainty theory. This paper assumes that the traffic supply and demand are random variables. Using the expected utility theory to consider the risk attitude of users and the deviation degree to considering the risk attitude of decision maker, a bi-level programming model is established. This paper presents a method with genetic algorithm to solve the problem, and then gives an example. The results of the Nguyen Dupuis network show that the risk attitudes of decision makers and users have an important impact on the decision-making of network design. The proposed method can effectively improve the robustness of network design.