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

Xinxin Yu; Jie Shao; Xiaoxia Yao; Guoyi Tang; Ying Liu; Xiongjun Han; Changzhi Bian; Heling Liu

doi:10.1117/12.2652564

21 November 2022 Discrete traffic network design model considering risk attitude of decision maker and users

Xinxin Yu, Jie Shao, Xiaoxia Yao, Guoyi Tang, Ying Liu, Xiongjun Han, Changzhi Bian, Heling Liu

Author Affiliations +

Proceedings Volume 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022); 123400J (2022) https://doi.org/10.1117/12.2652564
Event: International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 2022, Lanzhou, China

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.

Citation Download Citation

Xinxin Yu, Jie Shao, Xiaoxia Yao, Guoyi Tang, Ying Liu, Xiongjun Han, Changzhi Bian, and Heling Liu "Discrete traffic network design model considering risk attitude of decision maker and users", Proc. SPIE 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 123400J (21 November 2022); https://doi.org/10.1117/12.2652564

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