Vehicles, Advanced Features, Driver Behavior, and Safety: A Systematic Review of the Literature

Abstract

Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lane departure warning (LDW), blind spot warning (BSW), over speed warning (OSW), forward collision warning (FCW), lane keep assist (LKA), adaptive cruise control (ACC), cooperative ACC (CACC), and automated emergency braking (AEB) are designed to assist with, or in some cases take over, certain driving maneuvers. They can be broadly categorized into advanced driver assistance system (ADAS) and automated features. Each of these advanced features focuses on addressing a particular task of driving, thereby, aiding the driver, influencing their behavior, and enhancing safety. Many vehicles with these advanced features are penetrating into the market, yet the total reported number of crashes has increased in recent years. This paper presents a systematic review of these advanced features on driver behavior and safety. The review is categorized into 1) survey and mathematical methods to assess driver behavior, 2) field test methods to assess driver behavior, 3) microsimulation methods to assess driver behavior, 4) driving simulator methods to assess driver behavior, and 5) driver understanding and the effectiveness of advanced features. It is followed by conclusions, knowledge gaps, and need for further research.

Assessment of Reasons for Driver Speeding and Estimation of Penalty Probability

“…His driving behavior is unaffected by feelings and moods [23,24]. Around the world, there are many traffic fatalities; they are the main cause of death for those under the age of 54 [25,26]. Every year brings more and newer to the road, worsening the traffic and safety issues [27,28].…”

“…Driver error is the primary cause of traffic accidents. Automakers and researchers are constantly working to produce vehicles with cutting-edge properties, minimize human intervention in driving, influence driver behavior, improve safety, and have the best goal of full automation in the future [25]. Although many studies analyzing driving behavior have been carried out in recent years, some concerns remain to be addressed.…”