• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 28 Issue 5
Oct.  2015
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Article Contents
LIU Lan, LUO Chen, YIN Junsong, MA Yafeng. Route Decision Model under the Environment of Multi-source Information[J]. Journal of Southwest Jiaotong University, 2015, 28(5): 891-897. doi: 10.3969/j.issn.0258-2724.2015.05.019
Citation: LIU Lan, LUO Chen, YIN Junsong, MA Yafeng. Route Decision Model under the Environment of Multi-source Information[J]. Journal of Southwest Jiaotong University, 2015, 28(5): 891-897. doi: 10.3969/j.issn.0258-2724.2015.05.019

Route Decision Model under the Environment of Multi-source Information

doi: 10.3969/j.issn.0258-2724.2015.05.019
  • Received Date: 06 Jan 2015
  • Publish Date: 25 Oct 2015
  • Aimed at the route choice process integrated with the subjective perception and objective analysis that cannot be quantified, the intuitionistic fuzzy set theory is applied to quantify the selection results of route decision, in which the subjective and objective intuitionistic fuzzy numbers are constructed by the establishment of the dual membership function, and decision-making functions are set up with the membership degree and hesitating membership degree of intuitionistic fuzzy numbers. Drawing lessons from evidence conflicting ideas of evidence theory, a function projection method is proposed to solve the distribution problem of hesitating degree function. Then, a logarithmic growth model is applied to determine dynamic weights and quantify temporal characteristics of multi-source information, and a route decision model is established to analyze the driving decision-making behavior. Finally, an example derived from traffic practices demonstrates that the approximate membership degrees of go and change decision are calculated as 0.767 and 0.233, respectively, with the decision-making functions under a multivariate information environment including experiences, traffic management and control, roads, and congestion.

     

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