Highway network design model with value-at-risk

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

doi:10.1117/12.2652300

21 November 2022 Highway network design model with value-at-risk

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

Proceedings Volume 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022); 1234007 (2022) https://doi.org/10.1117/12.2652300
Event: International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 2022, Lanzhou, China

Abstract

In order to improve the traditional planning method, this paper establishes traffic network design model under uncertainty theory, so as to improve the rationality of the traffic network planning scheme. This paper assumes that the traffic demand is a random variable, and then establishes a bi-level model. The upper model takes the sum of the total travel time and VaR as the objective function, and the lower model uses the user equilibrium allocation model. The genetic algorithm with Monte Carlo simulation is used to solve the stochastic network optimization problem. The example analysis shows that: (1) The uncertainty of demand has a significant impact on the network construction scheme. (2) Network planning scheme will be affected by the risk attitude of the decision maker.

Citation Download Citation

Xinxin Yu, Changzhi Bian, Heling Liu, Jie Shao, Xiaoxia Yao, Guoyi Tang, Xiongjun Han, and Ying Liu "Highway network design model with value-at-risk", Proc. SPIE 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 1234007 (21 November 2022); https://doi.org/10.1117/12.2652300

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