Stochastic User Equilibrium for Route Choice Model Based on Random Regret Minimization

2012 ◽  
Vol 2284 (1) ◽  
pp. 100-108 ◽  
Author(s):  
Shlomo Bekhor ◽  
Caspar Chorus ◽  
Tomer Toledo
Keyword(s):  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Regret Minimization ◽  
Model Based ◽  
Random Regret Minimization

scholarly journals A regret-based route choice model with asymmetric preference in a stochastic network

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879323
Author(s):  
Lei Zhao ◽  
Hongzhi Guan ◽  
Xinjie Zhang ◽  
Xiongbin Wu
Keyword(s):  
Loss Aversion ◽  
Equilibrium Model ◽  
Choice Model ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Regret Minimization ◽  
Route Network ◽  
Travel Decision ◽  
Gains And Losses ◽  
Random Regret Minimization

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.

Solving the Overlapping Problem in Route Choice with Paired Combinatorial Logit Model

2003 ◽  
Vol 1857 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Anthony Chen ◽  
Panatda Kasikitwiwat ◽  
Zhaowang Ji
Keyword(s):  
Mathematical Programming ◽  
Logit Model ◽  
Choice Model ◽  
Route Choice ◽  
Similarity Index ◽  
User Equilibrium ◽  
Transportation Systems ◽  
Programming Formulation ◽  
Stochastic User Equilibrium ◽  
Mathematical Programming Formulation

Recently, there has been renewed interest in improving the logit-based route choice model because of the importance of the route choice model in intelligent transportation systems applications, particularly the applications of advanced traveler information systems. The paired combinatorial logit (PCL) model and its equivalent mathematical programming formulation for the route choice problem have been studied. An algorithm based on the partial linearization method is presented for solving the PCL stochastic user equilibrium problem. Detailed examples are provided to explain how this hierarchical logit model resolves the overlapping problem through the similarity index while still accounting for both congestion and stochastic effects in the mathematical programming formulation.

Stochastic Traffic Assignment Model Based on Travel Time Reliability

2011 ◽  
Vol 130-134 ◽  
pp. 3716-3720
Author(s):  
Yi Ran Cheng ◽  
Yin Han ◽  
Xin Kai Jiang ◽  
Jia Lei Gu
Keyword(s):  
Travel Time ◽  
Equilibrium Model ◽  
Choice Behavior ◽  
Transportation Networks ◽  
Route Choice ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Stochastic User Equilibrium ◽  
Model Based ◽  
Route Choice Behavior

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.

Is it Necessary to Relax the IID Assumptions in the Logsum-Based Accessibility Analysis?

2019 ◽  
Vol 2673 (4) ◽  
pp. 84-96
Author(s):  
Yongnan Yan ◽  
Xiangdong Xu ◽  
Anthony Chen
Keyword(s):  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Independence Assumption ◽  
Accessibility Analysis ◽  
Project Appraisal ◽  
Transit Accessibility ◽  
Accessibility Evaluation ◽  
The Difference

Accessibility is an important link between transportation and land use. As a typical measure of accessibility, logsum or a utility-based measure has been widely used in project appraisal, urban transit accessibility evaluation, destination choice, and network vulnerability analysis. Since the logsum term is the log of the denominator of the choice probability expression, it inherits the independently and identically distributed (IID) assumptions of the classical multinomial logit (MNL) route choice model. This paper aims to explore whether the IID assumptions have a significant effect on the logsum-based accessibility analysis, given that accessibility analysis focuses at the origin-destination (O-D) level and zonal level (aggregate analysis) rather than at the route level (disaggregate analysis). We derive two new logsum terms for two representative extended logit stochastic user equilibrium (SUE) models, that is, the C-logit model for relaxing the independence assumption and the MNL model with scaling effect (MNLs) for relaxing the identically distributed assumption. The case analysis of a real network in Winnipeg, Canada shows that: (1) there does exist a difference in accessibility evaluation among the three logsum terms using the three route choice models; (2) relaxing the identically distributed assumption is more important than the independence assumption since the difference in accessibility evaluation between MNLs-logsum and MNL-logsum is larger than that between C-logit-logsum and MNL-logsum; (3) the difference in accessibility evaluation at the zonal level is smaller than that at the O-D level; and (4) the difference increases with the dispersion parameter.

scholarly journals A Simulation-Based Dynamic Stochastic Route Choice Model for Evacuation

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Xing Zhao ◽  
Gang Ren ◽  
Chao Fan ◽  
Chen-Zi Ding
Keyword(s):  
Traffic Flow ◽  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Transmission Model ◽  
Time Interval ◽  
Signal Design ◽  
Stochastic User Equilibrium ◽  
Cell Transmission Model ◽  
Dynamic Stochastic

This paper establishes a dynamic stochastic route choice model for evacuation to simulate the propagation process of traffic flow and estimate the stochastic route choice under evacuation situations. The model contains a lane-group-based cell transmission model (CTM) which sets different traffic capacities for links with different turning movements to flow out in an evacuation situation, an actual impedance model which is to obtain the impedance of each route in time units at each time interval and a stochastic route choice model according to the probit-based stochastic user equilibrium. In this model, vehicles loading at each origin at each time interval are assumed to choose an evacuation route under determinate road network, signal design, and OD demand. As a case study, the proposed model is validated on the network nearby Nanjing Olympic Center after the opening ceremony of the 10th National Games of the People's Republic of China. The traffic volumes and clearing time at five exit points of the evacuation zone are calculated by the model to compare with survey data. The results show that this model can appropriately simulate the dynamic route choice and evolution process of the traffic flow on the network in an evacuation situation.

scholarly journals A Day-to-Day Route Choice Model Based on Reinforcement Learning

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Fangfang Wei ◽  
Shoufeng Ma ◽  
Ning Jia
Keyword(s):  
Reinforcement Learning ◽  
Network Flow ◽  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Learning Rate ◽  
Traffic Dynamics ◽  
Link Capacity ◽  
Model Based ◽  
Capacity Degradation

Day-to-day traffic dynamics are generated by individual traveler’s route choice and route adjustment behaviors, which are appropriate to be researched by using agent-based model and learning theory. In this paper, we propose a day-to-day route choice model based on reinforcement learning and multiagent simulation. Travelers’ memory, learning rate, and experience cognition are taken into account. Then the model is verified and analyzed. Results show that the network flow can converge to user equilibrium (UE) if travelers can remember all the travel time they have experienced, but which is not necessarily the case under limited memory; learning rate can strengthen the flow fluctuation, but memory leads to the contrary side; moreover, high learning rate results in the cyclical oscillation during the process of flow evolution. Finally, both the scenarios of link capacity degradation and random link capacity are used to illustrate the model’s applications. Analyses and applications of our model demonstrate the model is reasonable and useful for studying the day-to-day traffic dynamics.

Location-Based Route Choice Model under Random Regret Minimization

CICTP 2014 ◽  
2014 ◽  
Author(s):  
Xiangfeng Ji ◽  
Jian Zhang ◽  
Yongkai Hu ◽  
Bin Ran
Keyword(s):  
Choice Model ◽  
Route Choice ◽  
Regret Minimization ◽  
Random Regret Minimization
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