Zobrazeno 1 - 10
of 216 803
pro vyhledávání: '"Driver P"'
Success in racing requires a unique combination of vehicle setup, understanding of the racetrack, and human expertise. Since building and testing many different vehicle configurations in the real world is prohibitively expensive, high-fidelity simula
Externí odkaz:
http://arxiv.org/abs/2412.03803
In the domain of autonomous vehicles, the human-vehicle co-pilot system has garnered significant research attention. To address the subjective uncertainties in driver state and interaction behaviors, which are pivotal to the safety of Human-in-the-lo
Externí odkaz:
http://arxiv.org/abs/2412.04888
The classification of distracted drivers is pivotal for ensuring safe driving. Previous studies demonstrated the effectiveness of neural networks in automatically predicting driver distraction, fatigue, and potential hazards. However, recent research
Externí odkaz:
http://arxiv.org/abs/2411.13181
Autor:
Xu, Hanxiang, Ma, Wei, Zhou, Ting, Zhao, Yanjie, Chen, Kai, Hu, Qiang, Liu, Yang, Wang, Haoyu
The rapid development of large language models (LLMs) with advanced programming capabilities has paved the way for innovative approaches in software testing. Fuzz testing, a cornerstone for improving software reliability and detecting vulnerabilities
Externí odkaz:
http://arxiv.org/abs/2411.11532
The driver warning system that alerts the human driver about potential risks during driving is a key feature of an advanced driver assistance system. Existing driver warning technologies, mainly the forward collision warning and unsafe lane change wa
Externí odkaz:
http://arxiv.org/abs/2411.06306
Red light violation is a major cause of traffic collisions and resulting injuries and fatalities. Despite extensive prior work to reduce red light violations, they continue to be a major problem in practice, partly because existing systems suffer fro
Externí odkaz:
http://arxiv.org/abs/2411.03271
Road safety remains a critical challenge worldwide, with approximately 1.35 million fatalities annually attributed to traffic accidents, often due to human errors. As we advance towards higher levels of vehicle automation, challenges still exist, as
Externí odkaz:
http://arxiv.org/abs/2410.21086
Autor:
Fang, Zihan, Lin, Zheng, Hu, Senkang, Cao, Hangcheng, Deng, Yiqin, Chen, Xianhao, Fang, Yuguang
Recently, in-car monitoring has emerged as a promising technology for detecting early-stage abnormal status of the driver and providing timely alerts to prevent traffic accidents. Although training models with multimodal data enhances the reliability
Externí odkaz:
http://arxiv.org/abs/2410.02592
This paper addresses the problem of human-based driver support. Nowadays, driver support systems help users to operate safely in many driving situations. Nevertheless, these systems do not fully use the rich information that is available from sensing
Externí odkaz:
http://arxiv.org/abs/2410.03774