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.

翻译：在美国，高风险驾驶员占致命交通事故的70%。随着传感器与智能车载系统的进步，基于驾驶员行为评估以提升驾驶体验与道路安全的研究取得了显著进展。本文综述了利用视觉与车载数据分析驾驶员行为的多种技术，概述了该领域的最新研究进展。同时，讨论了当前面临的技术挑战与未解决问题，并为未来研究提出了潜在建议。本综述结论表明，视觉信息与车载信息的融合能够显著提升驾驶员行为分析的准确性与有效性，从而增强安全措施并减少交通事故。