陈艳艳, 张野, 孙浩冬. 基于手机信令数据的旅游客流特征分析[J]. 北京工业大学学报, 2022, 48(8): 842-850. DOI: 10.11936/bjutxb2021060001
    引用本文: 陈艳艳, 张野, 孙浩冬. 基于手机信令数据的旅游客流特征分析[J]. 北京工业大学学报, 2022, 48(8): 842-850. DOI: 10.11936/bjutxb2021060001
    CHEN Yanyan, ZHANG Ye, SUN Haodong. Analysis of Tourist Flow Characteristics Based on Mobile Phone Signaling Data[J]. Journal of Beijing University of Technology, 2022, 48(8): 842-850. DOI: 10.11936/bjutxb2021060001
    Citation: CHEN Yanyan, ZHANG Ye, SUN Haodong. Analysis of Tourist Flow Characteristics Based on Mobile Phone Signaling Data[J]. Journal of Beijing University of Technology, 2022, 48(8): 842-850. DOI: 10.11936/bjutxb2021060001

    基于手机信令数据的旅游客流特征分析

    Analysis of Tourist Flow Characteristics Based on Mobile Phone Signaling Data

    • 摘要: 为解决旅游人口增加导致的城市客流激增与滞留及交通拥堵等问题, 提出一种基于手机信令数据精准提取游客特征的方法,精准识别游客的出行轨迹,分析挖掘旅游客流的特征及其变化规律. 基于上述方法,以北京八达岭长城景区为案例进行计算、识别与分析,得到其景区内游客的时空特征. 结果表明,该方法具有普适性和可移植性,可在数据支撑充足的情况下完成长时段、多范围的景区客流识别及出行规律挖掘,为景区客流量预测及应急保障提供科学数据支撑,并为旅游、交通管理部门和旅游者提供决策支持,提高旅游交通的服务水平.

       

      Abstract: To solve the problems of the surge and detention in urban passenger flow and traffic congestion caused by the increase in tourist population, this paper proposed a method for extracting tourist characteristics based on mobile signaling data, accurately identifying the travel trajectory of tourists, analyzing and mining the characteristics and changing laws of tourist flow. Based on the above method, the Badaling Great Wall was used as a case for calculation, identification and analysis to obtain the temporal and spatial characteristics of tourists in the tourist attractions. It can complete long-term, multi-range tourist flow identification and travel law mining with sufficient data support, and provide scientific data support for prediction and emergency protection. Finally, it also can provide decision-making support for the tourism, traffic management departments and tourists, and improve the service level of tourism traffic.

       

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