1–10 von 10 Ergebnissen
|

    Methods and Models for Simulating Autonomous Vehicle Sensors

    Elmquist, Asher / Negrut, Dan | IEEE | 2020

    IRIS: High-fidelity Perception Sensor Modeling for Closed-Loop Planetary Simulations

    Aiazzi, Carolina / Jain, Abhinandan / Gaut, Aaron et al. | AIAA | 2022

    IRIS: High-fidelity Perception Sensor Modeling for Closed-Loop Planetary Simulations

    Young, Aaron / Elmquist, Asher / Jain, Abhinandan et al. | NTRS | 2022

    IRIS: High-fidelity Perception Sensor Modeling for Closed-Loop Planetary Simulations

    Elmquist, Asher / Young, Aaron / Jain, Abhinandan et al. | NTRS | 2022

    IRIS: High-fidelity Perception Sensor Modeling for Closed-Loop Planetary Simulations

    Aiazzi, Carolina / Jain, Abhinandan / Gaut, Aaron et al. | TIBKAT | 2022

    IRIS: High-Fidelity Perception Sensor Modeling for Closed-Loop Planetary Simulations

    Aiazzi, Carolina / Jain, Abhinandan / Gaut, Aaron et al. | TIBKAT | 2022

    Autonomous Vehicles in the Cyberspace: Accelerating Testing via Computer Simulation

    Elmquist, Asher / Negrut, Dan / Hatch, Dylan et al. | SAE Technical Papers | 2018

    A Geographically Distributed Simulation Framework for the Analysis of Mixed Traffic Scenarios Involving Conventional and Autonomous Vehicles

    Benatti, Simone / Schwarz, Chris / Young, Aaron et al. | British Library Conference Proceedings | 2022

    A Geographically Distributed Simulation Framework for the Analysis of Mixed Traffic Scenarios Involving Conventional and Autonomous Vehicles

    Benatti, Simone / Schwarz, Chris / Young, Aaron et al. | British Library Conference Proceedings | 2022