This paper presents the development of visual programming languages and summarizes the recent research in traffic simulation and autonomous driving experiments in VIPLE (Visual IoT/Robotics Programming Language Environment). The traffic simulator is developed in the Unity programming engine. The traffic simulator allows generation of different traffic patterns, either randomly or guided through a recorded real-world traffic dataset. Traffic experiments can be programmed in VIPLE or in Unity simulator, allowing developers to create such experiments without a deep understanding and lengthy support programming around the environment. Instead, the user can focus on implementing optimal routing algorithms that navigate a vehicle through the city traffic. The autonomous driving environment is based on TORCS simulation environment. A variety of difficulty levels of autonomous driving experiments can be created. Both traffic simulation and autonomous driving experiments can be written in visual programming language VIPLE, as well as in C# and Python within VIPLE environment. VIPLE has been widely used in different courses worldwide. This new advancement in VIPLE can particularly help students to perform traffic control and autonomous driving related programming, machine learning, and artificial intelligence research and experiments.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic Simulation and Autonomous Driving Experiment in VIPLE


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Zeng, Xiaoqing (Herausgeber:in) / Xie, Xiongyao (Herausgeber:in) / Sun, Jian (Herausgeber:in) / Ma, Limin (Herausgeber:in) / Chen, Yinong (Herausgeber:in) / Chen, Yinong (Autor:in) / De Luca, Gennaro (Autor:in)

    Kongress:

    International Symposium for Intelligent Transportation and Smart City ; 2022 May 20, 2022 - May 21, 2022



    Erscheinungsdatum :

    28.04.2023


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Traffic-Aware Autonomous Driving with Differentiable Traffic Simulation

    Zheng, Laura / Son, Sanghyun / Lin, Ming C. | ArXiv | 2022

    Freier Zugriff

    Traffic Flow Simulation for Autonomous Driving

    Li, Junfeng / Yan, Changqing | ArXiv | 2023

    Freier Zugriff

    Coupling traffic and driving simulation: new possibilities of testing autonomous driving

    Hafner, A. / Barthauer, M. / Henze, R. et al. | TIBKAT | 2019


    Autonomous Automated Driving in Real Traffic

    Ulmer, B. | British Library Conference Proceedings | 1994


    COOPERATIVE AUTONOMOUS DRIVING FOR TRAFFIC CONGESTION AVOIDANCE

    WANG NANNAN / WANG XI / ZHANG QIONG et al. | Europäisches Patentamt | 2019

    Freier Zugriff