Using Visual and Vehicular Sensors for Driver Behavior Analysis: A Survey

TL;DR

This survey reviews recent techniques using visual and vehicular sensors for analyzing driver behavior, highlighting their potential to improve road safety through integrated data analysis.

Contribution

It provides a comprehensive overview of current methods, discusses challenges, and suggests future directions for sensor-based driver behavior analysis.

Findings

Integration of vision and vehicular data improves analysis accuracy

Sensor-based methods can enhance safety measures

Open problems include data privacy and sensor reliability

Abstract

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.