Since vehicles are not restricted by lane lines when driving inside intersections, they travel freely and their paths have many possibilities, which are related to the traffic order of other road users. It is necessary to understand and describe vehicle paths through intersections. Previous studies on modeling vehicle paths through intersections have predominantly been limited to vehicles turning in one single direction or specific intersections, ignoring the application universality. This study set out to establish a unified model to describe non-conflict paths of vehicles through intersections. An entrance lane-based coordinate system with geometric parameters was established to describe the position relationships of entrance and exit lanes. Three-order Bezier curves with control parameters were used to describe vehicle paths. By extracting the parameter values from driving simulator-based experiments, the entrance and exit lane-based vehicle path model was proposed to represent the relationship between geometric and control parameters. Actual path data captured by an unmanned aerial vehicle were used for model validation, and results show the validity of the proposed model with a mean Root Mean Square Error of 0.4613 m between observed and fitted paths. More validation considering position distributions of path origins and destinations and angle deviations when entering and leaving intersections was performed. Cases from HighD open dataset also demonstrated the model’s potential for lane-changing scenarios. This study provides an exciting opportunity to commonly describe vehicle paths without conflicts at geometrically regular and irregular intersections and is hoped to have the possibility of planning local paths for autonomous vehicles.


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    Title :

    Modeling Vehicle Paths at Intersections: A Unified Approach Based on Entrance and Exit Lanes


    Contributors:
    Lu, Guangquan (author) / Hua, Jun (author) / Zhao, Haoyi (author) / Liu, Miaomiao (author) / Xu, Jin (author) / Zong, Fang (author)

    Published in:

    Publication date :

    2023-12-01


    Size :

    3879012 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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