A stochastic user equilibrium model solving overlapping path and perfectly rational issues

2021 ◽  
Vol 28 (5) ◽  
pp. 1584-1600
Author(s):  
Dong-mei Yan ◽  
Jian-hua Guo
2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879323
Author(s):  
Lei Zhao ◽  
Hongzhi Guan ◽  
Xinjie Zhang ◽  
Xiongbin Wu

In this study, a stochastic user equilibrium model on the modified random regret minimization is proposed by incorporating the asymmetric preference for gains and losses to describe its effects on the regret degree of travelers. Travelers are considered to be capable of perceiving the gains and losses of attributes separately when comparing between the alternatives. Compared to the stochastic user equilibrium model on the random regret minimization model, the potential difference of emotion experienced induced by the loss and gain in the equal size is jointly caused by the taste parameter and loss aversion of travelers in the proposed model. And travelers always tend to use the routes with the minimum perceived regret in the travel decision processes. In addition, the variational inequality problem of the stochastic user equilibrium model on the modified random regret minimization model is given, and the characteristics of its solution are discussed. A route-based solution algorithm is used to resolve the problem. Numerical results given by a three-route network show that the loss aversion produces a great impact on travelers’ choice decisions and the model can more flexibly capture the choice behavior than the existing models.


2011 ◽  
Vol 130-134 ◽  
pp. 3716-3720
Author(s):  
Yi Ran Cheng ◽  
Yin Han ◽  
Xin Kai Jiang ◽  
Jia Lei Gu

Considering the un-deterministic transportation networks, the paper proposes the change of the route choice decisions under the stochastic transportation networks. The route choice behavior is described as a choice for a time shortest route which is subject to a time-reliability level. The paper also considered this new route choice behavior in the stochastic user equilibrium model, and proposed stochastic user equilibrium model based on the optimized reliability travel time route choice behavior in the stochastic networks. The equivalence and uniqueness of the solution of the model are demonstrated. Numerical results of a small network show that the proposed model can reflect the real traveler’s route choice behavior in stochastic transportation networks.


2020 ◽  
Vol 12 (13) ◽  
pp. 5433
Author(s):  
Xueyan Wei ◽  
Wei Wang ◽  
Weijie Yu ◽  
Xuedong Hua ◽  
Yun Xiang

As a countermeasure to urban exhaust pollution and traffic congestion, traffic restriction based on the last digit of license plate numbers has been widely introduced throughout the world. However, the effect of traffic restriction is weakened as it causes the long-distance detour of restricted travel modes and induces travel demand to shift to unrestricted travel modes. To consider detour and shift of traffic demand caused by traffic restriction, we propose a stochastic user equilibrium model under traffic rationing based on mode shifting rate and the corresponding solution algorithm. A case study is conducted to verify the effectiveness of proposed model and algorithm. Main findings of numerical experiments include: (1) Compared with traditional stochastic user equilibrium model, the temporary traffic demand shift caused by long-distance detour are well considered in proposed model. (2) Sensitivity analysis of the consumption parameters used in the proposed model shows that, the involved cost parameters have different effectiveness on the mode shifting rate. This study provides a reasonable relaxation of the intensively used assumption, that all restricted vehicles outside the restricted district will detour in traffic rationing research, and provides a reasonable approach to evaluate the change of link flow and the beneficial effectiveness on the sustainability of traffic environment after implementation of traffic restriction policy.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 20971-20986 ◽  
Author(s):  
Jianmei Liu ◽  
Zhengbing He ◽  
Shuaiqi Ma

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