Risky drivers account for 70% of fatal accidents in the United States. With
recent advances in sensors and intelligent vehicular systems, there has been
significant research on assessing driver behavior to improve driving
experiences and road safety. This paper examines the various techniques used to
analyze driver behavior using visual and vehicular data, providing an overview
of the latest research in this field. The paper also discusses the challenges
and open problems in the field and offers potential recommendations for future
research. The survey concludes that integrating vision and vehicular
information can significantly enhance the accuracy and effectiveness of driver
behavior analysis, leading to improved safety measures and reduced traffic
accidents.

通过使用传感器和智能车载系统，评估驾驶员行为的研究可以提高驾驶体验和道路安全。本文研究了使用视觉和车载数据分析驾驶员行为的各种技术，并提供了该领域最新研究的概述，同时讨论了面临的挑战和未解决的问题，并为未来的研究提出了潜在建议。综述得出结论，整合视觉和车载信息可以显著提高驾驶员行为分析的准确性和有效性，从而提高安全措施并减少交通事故。