Behavioral Cloning Models Reality Check for Autonomous Driving
<|reference_start|>Behavioral Cloning Models Reality Check for Autonomous Driving: How effective are recent advancements in autonomous vehicle perception systems when applied to real-world autonomous vehicle control? While numerous vision-based autonomous vehicle systems have been trained and evaluated in simulated environments, there is a notable lack of real-world validation for these systems. This paper addresses this gap by presenting the real-world validation of state-of-the-art perception systems that utilize Behavior Cloning (BC) for lateral control, processing raw image data to predict steering commands. The dataset was collected using a scaled research vehicle and tested on various track setups. Experimental results demonstrate that these methods predict steering angles with low error margins in real-time, indicating promising potential for real-world applications.<|reference_end|>
@article{yildirim2024behavioral,
    title={Behavioral Cloning Models Reality Check for Autonomous Driving},
    author={Mustafa Yildirim, Barkin Dagda, Vinal Asodia and Saber Fallah},
    journal={arXiv preprint arXiv:2409.07218},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.07218},
    primaryClass={cs.RO cs.AI cs.CV}
}