The 2005 DARPA Grand Challenge, a 212-kilometer race through the Mojave Desert, showcased the state of the art in high-speed, autonomous navigation of trails and roads. To win the challenge, a team's robot had to complete the course faster than any other robot, and it had to do so within 10 hours. Carnegie Mellon University's Red Team developed two robots, which used a combination of autonomous and human preplanning to become two of only four robots to complete the Grand Challenge. The robots used onboard sensors to adjust a preplanned route to avoid obstacles and correct for position-estimation errors. To be successful, teams had to develop innovative algorithms and systems - and rigorously test them to verify performance. The Red Team used the tests regressively to evaluate how unit changes in hardware and software affected the robots' overall driving ability.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Testing driver skill for high-speed autonomous vehicles


    Contributors:
    Urmson, C. (author) / Whittaker, W. (author) / Harbaugh, S. (author) / Clark, M. (author) / Koon, P. (author)

    Published in:

    Computer, Long Beach ; 39 , 12 ; 48-51


    Publication date :

    2006


    Size :

    4 Seiten, 3 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Autonomous Vehicles and Advanced Driver Assistance

    KRISHNAN ASHOK | European Patent Office | 2024

    Free access

    Driver footrest device for autonomous vehicles

    European Patent Office | 2022

    Free access

    Driver footrest device for autonomous vehicles

    KIM BYUNG HYUCK | European Patent Office | 2022

    Free access

    Measuring Driver Discomfort in Autonomous Vehicles

    Niermann, Dario / Lüdtke, Andreas | Springer Verlag | 2020


    REMOTE DRIVER STATE CONSIDERATION FOR AUTONOMOUS VEHICLES

    TANRIOVER CAGRI CAGATAY | European Patent Office | 2019

    Free access