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重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2021, Vol. 40 ›› Issue (10): 161-170.DOI: 10.3969/j.issn.1674-0696.2021.10.19

• 交通+大数据人工智能 • 上一篇    下一篇

基于游客体验的城市近郊旅游路线规划

陆百川1,2，杨杰毅1，王鑫1   

  1. (1. 重庆交通大学 交通运输学院，重庆 400074； 2. 重庆交通大学 重庆山地城市交通系统与安全实验室，重庆 400074)
  • 收稿日期:2020-11-23 修回日期:2021-04-02 发布日期:2021-10-29
  • 作者简介:陆百川（1961—），男，江苏南通人，教授，博士，博士生导师，主要从事智能交通及交通信息方面的研究。E-mail：656542576@qq.com 通信作者：杨杰毅（1998—），女，河北邢台人，硕士研究生，主要从事交通信息工程及控制方面的研究。E-mail：1535776056@qq.com
  • 基金资助:
    重庆市研究生导师团队建设项目(JDDSTD2018007);重庆市教委科技研究计划重点项目(KJZD-K202000704)

Tourism Route Planning of Urban Suburb Based on Tourist Experience

LU Baichuan1,2, YANG Jieyi1, WANG Xin1   

  1. (1. School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China; 2. Key Lab of Traffic System & Safety in Mountain Cities, Chongqing Jiaotong University, Chongqing 400074, China)
  • Received:2020-11-23 Revised:2021-04-02 Published:2021-10-29

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摘要： 根据城市近郊自驾游灵活性和个性化的特点，综合考虑道路交通和旅游景点因素对游客出行体验的影响，提出了一种基于游客体验的城市近郊旅游路线规划方法。首先在综合分析道路交通因素及旅游景点属性对自驾游客体验感影响基础上，建立了基于综合路阻的景点间最优路径选择模型，并采用Floyd算法进行了求解；然后根据旅游出行成本和景点游览效用构建了基于游客体验的景点顺序规划模型，并利用遗传算法对最优旅游路线进行了求解；最后通过实例验证表明，相比传统基于出行距离最短的旅游路线规划方法，基于游客体验的城市近郊旅游路线规划方法更符合自驾游客出游实际情况，能有效减少游客的行程时间和景点等待时间。

关键词: 交通工程；旅游路线；游客体验；自驾游客；城市近郊

Abstract: According to the characteristics of flexibility and individuality of self-driving tour in suburban areas, and comprehensively considering the influence of road traffic and tourist attractions on the travel experience of tourists, a method for planning tourism routes in suburban cities based on tourist experience was proposed. First of all, based on the comprehensive analysis of the influence of road traffic factors and tourist attractions attributes on the experience of self-driving tourists, an optimal path selection model between attractions based on the comprehensive road resistance was established, and Floyd algorithm was used to solve the model. Then, on the basis of the travel cost and the utility of scenic spots, the sequence planning model of scenic spots based on tourist experience was built, and the optimal tourist route was solved by genetic algorithm. Finally, an example was used to verify. It shows that compared with the traditional route planning method based on the shortest distance, the tourism route planning method of suburban areas based on the tourist experience is more in line with the actual travel situation of self-driving tourists, which effectively reduces the travel time of tourists and the waiting time of attractions.

Key words: traffic engineering; tourist routes; tourist experience; self-driving tourists; suburban city

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