Evaluating the effectiveness of rhythmic visual guidance technology for mitigating driving risks in highway tunnel groups: A simulation study

Abstract

Driving in highway tunnel groups necessitates frequent adaptation to drastic changes in the traffic environment, thereby increasing driving difficulty and risk. This study integrates drivers’ preferences for rhythmic information with the inherent rhythmic characteristics of tunnel group structures to propose a new and adaptive method to mitigate driving risks using rhythmic visual guidance (RVG) technology. Unlike traditional visual guidance systems, which often rely on static signals, RVG utilizes dynamic, rhythmically varying cues to capture drivers’ attention and improve situational awareness more effectively. By employing principles of fuzzy mathematics, the study quantifies the applicability of various rhythmic forms in visual guidance technology and establishes priority application principles for undulating and staggered rhythms. After verifying the accuracy of the simulation model, the effectiveness of RVG technology in mitigating driving risks in highway tunnel groups was analyzed using lateral offset, driving speed, and vehicle acceleration as evaluation metrics. The findings reveal that RVG technology significantly reduces vehicle lateral offset and enhances drivers’ perception and control of tunnel sidewalls and driving trajectories. This effect is particularly pronounced under limited lighting conditions or in large tunnel groups with extended driving distances. Regardless of whether the lighting level is set at 0% or 100% of the standard brightness, the implementation of RVG results in reduced vehicle driving speeds. The variation in the 25th to 75th percentile distribution of driving speeds was insignificant, demonstrating that RVG technology effectively regulates driving speed and is not significantly affected by lighting conditions. Furthermore, when the lighting level is set at 100% of the standard brightness, the 25th to 75th percentile distribution interval of driving speeds is [89.576, 102.416], indicating the highest and least stable driving speeds suggests that blindly increasing tunnel lighting levels not only raises operating costs but may also adversely affect driving safety. This study provides novel insights into applying dynamic visual cues for highway tunnel groups’ traffic operation and safety management. It has significant practical engineering value for guiding the low-carbon design of tunnel groups.