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Author:

Jiang, M. (Jiang, M..) | Chen, Y. (Chen, Y..) | Zhou, R. (Zhou, R..)

Indexed by:

Scopus

Abstract:

This paper aims to establish and optimize the quantization algorithm of the tourist guide signs designing for the complex road network. The rating of tourist attractions, the amount of tourists, tourism scenic area, the travel time from the expressway exit to the tourism were taken as the influence factors of node demanding level for tourist attractions. Based on grey variable weight cluster theory, a division measure of guide demand for tourist regions was established, which could provide the theoretical basis for choosing which tourist attractions should be guided by directional signs. Compared with current research that only considered the level of tourism scenic spots to classify the guide necessity, the established method considered the traffic attraction of the scenic spots, which is more aligned with the drivers' demand. Considering the total amount restriction of guide signs, the path constraint that driver should not make a turn from the exit to the tourist attraction, and the condition that all tourist regions should be guided at least once. The mathematical model was established and solved by using the genetic algorithm to obtain the optimal inducing effect and the layout of tourist guide signs. The established method can provide the optimal layout of tourist guide signs. © 2019 American Society of Civil Engineers.

Keyword:

expressway; genetic algorithm; gray theory; tourist guide signs

Author Community:

  • [ 1 ] [Jiang, M.]Beijing Key Laboratory of Traffic Engineering, School of Civil, Construction Engineering Institute, Beijing Univ. of Technology, Beijing, 100124, China
  • [ 2 ] [Chen, Y.]Beijing Key Laboratory of Traffic Engineering, School of Civil, Construction Engineering Institute, Beijing Univ. of Technology, Beijing, 100124, China
  • [ 3 ] [Zhou, R.]School of Chinese Materia Medica, Beijing Univ. of Chinese Medicine, Beijing, 102488, China

Reprint Author's Address:

  • [Chen, Y.]Beijing Key Laboratory of Traffic Engineering, School of Civil, Construction Engineering Institute, Beijing Univ. of TechnologyChina

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Source :

Transportation Research Congress 2017: Sustainable, Smart, and Resilient Transportation - Selected Papers from the Proceedings of the Transportation Research Congress 2017

Year: 2019

Page: 117-127

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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