Digital Twin, as an emerging technology related to Cyber-Physical Systems (CPS) and Internet of Things (IoT), has attracted increasing attentions during the past decade. Conceptually, a Digital Twin is a digital replica of a physical entity in the real world, and this technology is leveraged in this study to design a cooperative driving system at non-signalized intersections, allowing connected vehicles to cooperate with each other to cross intersections without any full stops. Within the proposed Digital Twin framework, we developed an enhanced first-in-first-out (FIFO) slot reservation algorithm to schedule the sequence of crossing vehicles, a consensus motion control algorithm to calculate vehicles’ referenced longitudinal motion, and a model-based motion estimation algorithm to tackle communication delay and packet loss. Additionally, an augmented reality (AR) human-machine-interface (HMI) is designed to provide the guidance to drivers to cooperate with other connected vehicles. Agent-based modeling and simulation of the proposed system is conducted in Unity game engine based on a real-world map in San Francisco, and the human-in-the-loop (HITL) simulation results prove the benefits of the proposed algorithms with 20% reduction in travel time and 23.7% reduction in energy consumption, respectively, when compared with traditional signalized intersections.


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    Titel :

    Digital Twin-Assisted Cooperative Driving at Non-Signalized Intersections


    Beteiligte:
    Wang, Ziran (Autor:in) / Han, Kyungtae (Autor:in) / Tiwari, Prashant (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-06-01


    Format / Umfang :

    4222596 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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