This paper focuses on two aspects, including the drivers’ subjective preference and the randomness of traffic lights, to construct a selection model of reasonable traffic shortest paths for drivers. Through a questionnaire, factors in people’s travel considerations are analyzed. Statistical results of the questionnaire are weighted to obtain the degree of preference for path choice. A virtual matrix is then generated to represent the traffic light color and duration of the random traffic light. Finally, an urban road network is constructed for model application. Using Monte Carlo simulation and Dijkstra algorithm, reasonable traffic shortest paths and corresponding proportions are obtained. Calculation results show that a reasonable traffic shortest path considering subjectivity and randomness is more in line with the actual situation of the driver. Due to turning differences in the intersection, reasonable traffic shortest paths and corresponding proportions for OD pairs in upstream and downstream directions are different.


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    Titel :

    Finding Reasonable Paths Considering Drivers’ Subjective Preference and Randomness of Traffic Lights


    Beteiligte:
    Song, Tiancheng (Autor:in) / Wang, Dongwei (Autor:in) / Yan, Yadan (Autor:in)

    Kongress:

    22nd COTA International Conference of Transportation Professionals ; 2022 ; Changsha, Hunan Province, China


    Erschienen in:

    CICTP 2022 ; 878-886


    Erscheinungsdatum :

    08.09.2022




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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