These days most of the research related to autonomous vehicle technology focuses on vehicle technology itself and lesser on road infrastructure, including geometric design. This research project aims to lower the deficiency of research works required to make the optimized geometric road design for autonomous vehicle sustainable. In geometric design, significant concerns are designing the road geometrics such as lane width, the radius of horizontal curves, sag vertical curves and crest vertical curves, extra widening, setback distance, and intersection, making the road safer for the vehicles to travel comfortably.Road geometrics is widely designed using the stopping sight distance model, which provides sufficient time to avoid accidents and is efficient. Here in the research work, the stopping sight design model is used for autonomous vehicle technology. At first, the art of autonomous vehicle technology is studied, and a significant difference between autonomous vehicle technology and human-driven vehicle to apply stopping sight distance model is figured out. A literature study is also done for the geometric design of the road for the vehicle with the human driver and autonomous vehicle. The AASHTO model derived for the human-driven vehicle is used and modified for the autonomous vehicle, which gives the optimized geometric design for the autonomous vehicle. The Optimized geometric design parameter is designed individually in AutoCAD Civil 3D. Two road designs follow this in a random rural topography consisting of a normal road design for the vehicle with the human driver and a fully autonomous vehicle. Finally, the sustainability of optimized geometric design compared to road design for the human-driven vehicle is checked in terms of earthwork, pavement surface areas, and pavement materials volume. The result shows that the optimization of a geometric road design for autonomous vehicles is sustainable and extensive research is required.


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    Titel :

    Optimization of geometric road design for autonomous vehicle


    Beteiligte:
    Aryal, Prabin (Autor:in)

    Erscheinungsdatum :

    2020-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    380 / 629



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