The development of tourism brings economic benefits as well as additional pressure on the urban traffic system. For example, the travel time of tourists coincides with the rush hour of urban residents’ daily commuting. Limited urban traffic resources cannot meet the travel needs of tourists and urban residents at the same time, resulting in traffic congestion and low travel efficiency. Now, with the development of intelligent technology, tourists can obtain real-time information about transportation systems through various channels and adjust their travel behavior accordingly. This study shows tourists’ travel behavior based on a survey conducted to the tourists in Yangzhou city. 1500-interview data are analyzed, and a Multinomial Logit Model (MNL) was employed to establish the probability prediction model of tourists’ departure time choice. The results presented that sync traffic information and some other tourism-related factors determine the choice of tourists’ departure time. These factors distinguish the travel behavior of tourists from the daily travel behavior of urban residents. This study can provide suggestions for the urban tourism management department to formulate more targeted and efficient policies while creating a more comfortable tourism environment for tourists.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Modeling Tourists’ Departure Time considering the Influence of Multisource Traffic Information


    Beteiligte:
    Shijun Yu (Autor:in) / Siyuan Zhang (Autor:in) / Shejun Deng (Autor:in) / Tao Ji (Autor:in) / Peng Zhou (Autor:in) / Lang Peng (Autor:in)


    Erscheinungsdatum :

    2021




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Multisource traffic information fusion method for expressways

    YU DEXIN / LIN CIYUN / ZHANG WEI et al. | Europäisches Patentamt | 2015

    Freier Zugriff

    Optimising Electric Bus Departure Interval Considering Stochastic Traffic Conditions

    Zhenyang Qiu / Xiaowei Hu / Shuai Song et al. | DOAJ | 2023

    Freier Zugriff

    Joint Arrival-Departure Taxiway Scheduling Considering Departure Uncertainty

    Zhang, Yi / Zhang, Yicheng / Zhang, Sheng et al. | IEEE | 2023