Distraction pattern classification and comparisons under different conditions in the full-touch HMI mode

Abstract

Understanding driver distraction patterns is an important part of human–machine interaction (HMI), which is beneficial for the development of control strategies in human–machine co-driving systems. However, comparatively few studies have focused on driver distraction patterns. To address this issue, this study proposes a framework to characterize distraction patterns using glance behavior and manual behavior, and classifies distraction patterns into: aggressive, moderate, and conservative patterns based on real road experiments. Subsequently, differences in distraction behavior and effects on lateral vehicle control ability across distraction pattern groups, as well as distraction behavior differences exhibited by drivers in the same distraction pattern group under different conditions, are analyzed. Firstly, the results show that the aggressive distraction patterns have a smaller number of eyes-off-road (NoEOR) incidences but longer mean single eyes-off-road time (MSEORT), maximum single eyes-off-road time (MaxEORT) and a higher percentage of long eyes-off-road (PoLEOR) incidences than the other patterns. There are slight differences in the single eyes-off-road times (EORTs) between the conservative and moderate patterns and in the manual behavior for the aggressive and moderate distraction patterns. Secondly, the same distraction pattern exhibited by drivers for different road and secondary task conditions has differences in terms of the behavioral performance. Finally, there is few differences in the lateral motion of a vehicle with different distraction patterns. Surprisingly, the standard deviation of the steering wheel angle (SDSWA) is the smallest in the aggressive distraction pattern.