This paper presents the design and validation of our autonomous driving system developed for one-on-one high-speed racing at the Indy Autonomous Challenge (IAC) 2024. In this event, each team is required to pass the opponent car on an oval racetrack at very high speeds reaching more than 250 km/h. In order to meet the critical challenges of high-speed autonomous racing, we developed reliable perception, behavior planning for passing, and control algorithms stable in the high speed range. For perception, we constructed a multi-modal pipeline using cameras, LiDARs, and radars to achieve accurate and reliable real-time object detection. We also designed a new state machine-based algorithm for effective planning of overtaking maneuvers. As for the control, we improved the vehicle controller at higher speed ranges by building a more accurate engine torque map and fine-tuning the controller during the actual runs. Our newly designed racing system was proven effective, enabling our car to cruise stably at 250.1 km/h in solo lap and executing multiple successful overtaking maneuvers during the one-on-one races at the Las Vegas Motor Speedway (LVMS) for the Consumer Electronics Show (CES) 2024.


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    Titel :

    Design and Validation of Autonomous Driving System for High Speed One-on-One Racing


    Beteiligte:
    Nah, Sungwon (Autor:in) / Moon, Seongwoo (Autor:in) / Nam, Hyunwoo (Autor:in) / Ryu, Chanhoe (Autor:in) / Kim, Dokyeong (Autor:in) / Kim, Jihyeok (Autor:in) / Shim, David Hyunchul (Autor:in)


    Erscheinungsdatum :

    22.06.2025


    Format / Umfang :

    3374447 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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