In this paper, we introduce cooperative autonomous driving algorithms for vehicular networks with nonlinear mobile robot dynamics in urban environments that take human safety into account and are capable of performing vehicle-to-vehicle (V2V) and vehicle-to-pedestrian (V2P) collision avoidance. We argue that “flocks” are multi-agent models of vehicular traffic on roads and propose novel autonomous driving architectures and algorithms for cyber-physical vehicles capable of performing autonomous driving tasks such as lane-driving, lane-changing, braking, passing, and making turns. Our proposed autonomous driving algorithms are inspired by Olfati-Saber's flocking theory. Though, there are notable differences between autonomous driving on urban roads and flocking behavior — flocks have a single desired destination whereas most drivers on road do not share the same destination. We refer to this collective behavior (driving) as “multi-objective flocking.” The self-driving vehicles in our framework turn out to be hybrid systems with a finite number of discrete states that are related to the driving modes of vehicles. Complex driving maneuvers can be performed using a sequence of mode switchings. We use near-identity nonlinear transformations to extend the application of particle-based autonomous driving algorithms to multi-robot networks with nonlinear dynamics. The derivation of the mode switching conditions that preserve safety is non-trivial and an important part of the design of autonomous driving algorithms. We present several examples of driving tasks that can be effectively performed using our proposed driving algorithms.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Autonomous driving for vehicular networks with nonlinear dynamics


    Beteiligte:


    Erscheinungsdatum :

    01.06.2012


    Format / Umfang :

    1119263 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Autonomous Driving for Vehicular Networks with Nonlinear Dynamics

    Iftekhar, L. / Olfati-Saber, R. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2012


    Vehicular Networks and Autonomous Driving Cars

    Seon Hong, Choong / Khan, Latif U. / Chen, Mingzhe et al. | Springer Verlag | 2021


    Deep Learning Based Autonomous Driving in Vehicular Networks

    Su, Zhou / Hui, Yilong / Luan, Tom H. et al. | Springer Verlag | 2020


    Reliable and Efficient Autonomous Driving: the Need for Heterogeneous Vehicular Networks

    Zheng, Kan / Zheng, Qiang / Yang, Haojun et al. | ArXiv | 2015

    Freier Zugriff

    Design of V2X-Based Vehicular Contents Centric Networks for Autonomous Driving

    Lee, Sanghoon / Jung, Younghwa / Park, Young-Hoon et al. | IEEE | 2022