Route Choice Strategy in Traffic Network and Routing Strategy in Communication Network

2015 ◽  
Vol 4 (3) ◽  
Author(s):  
Bo Kui Chen ◽  
Ya Chun Gao
2007 ◽  
Vol 18 (11) ◽  
pp. 1775-1782 ◽  
Author(s):  
H. J. SUN ◽  
J. J. WU ◽  
Z. Y. GAO

In this paper, we propose a simple betweenness-driven model to capture the dynamics of traffic routing choice behaviors. By comparing with two other models (degree-driven and cost-driven), it is shown that the cost-driven routing strategy is more complex and sensitive to traffic congestion. Another result indicates that the load distributions are determined by the connectivity distribution and route choice behaviors of the traffic network. The model thus provides useful insight for the design of traffic networks.


2021 ◽  
Author(s):  
Chao Fan ◽  
Yanyan Wang ◽  
Zhongping Wu ◽  
Mingxi Zhang ◽  
Menglan Zhou

1997 ◽  
Vol 123 (4) ◽  
pp. 276-282 ◽  
Author(s):  
David E. Boyce ◽  
Der-Horng Lee ◽  
Bruce N. Janson ◽  
Stanislaw Berka

2021 ◽  
Vol 13 (17) ◽  
pp. 9992
Author(s):  
Xinming Zang ◽  
Zhenqi Guo ◽  
Jingai Ma ◽  
Yongguang Zhong ◽  
Xiangfeng Ji

In this paper, we employ a target-oriented approach to analyze the multi-attribute route choice decision of travelers in the stochastic tolled traffic network, considering the influence of three attributes, which are (stochastic) travel time, (stochastic) late arrival penalty, and (deterministic) travel cost. We introduce a target-oriented multi-attribute travel utility model for this analysis, where each attribute is assigned a target by travelers, and travelers’ objective is to maximize their travel utility that is determined by the achieved targets. Moreover, the interaction between targets is interpreted as complementarity relationship between them, which can further affect their travel utility. In addition, based on this travel utility model, a target-oriented multi-attribute user equilibrium model is proposed, which is formulated as a variational inequality problem and solved with the method of successive average. Target for travel time is determined via travelers’ on-time arrival probability, while targets for late arrival penalty and travel cost are given exogenously. Lastly, we apply the proposed model on the Braess and Nguyen–Dupuis traffic networks, and conduct sensitivity analysis of the parameters, including these three targets and the target interaction between them. The study in this paper can provide a new perspective for travelers’ multi-attribute route choice decision, which can further show some implications for the policy design.


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