Impacts of Combinations of Visual Information on Sidewalls of Urban Long Tunnel on Drivers' Vehicle Control Abilities

To investigate the effects of different combinations of visual information on sidewalls on drivers'vehicle control abilities across various lanes in urban long tunnels, a driving simulation experiment was conducted. Statistical techniques and factor analysis were used to assess the influence of visual information types and lane positions. Results indicated that both combinations of visual information on sidewalls and lane positions significantly affected vehicle control performance, although no interaction effects were observed. Under the same lane condition, Scenario 1 (with horizontal stripes only) resulted in the highest driving speed, exceeding other three combination scenarios by 5.2~9.8 km/h. It also showed the highest longitudinal acceleration, surpassing others by 0.08~0.14 m/s². In terms of lateral behavior, Scenario 1 exhibited greater lateral deviation than that in Scenarios 3 and 4 by 0.17 m and 0.16 m, respectively, and the maximum increase in lateral acceleration reached 0.051 m/s². Under the same visual guidance condition, lane position also had a significant effect: driving speeds in the left and right lanes were 3.2 km/h and 2.1 km/h higher than that in the middle lane, respectively; the lateral acceleration in the left lane exceeded that of the middle and right lanes by 0.454 m/s² and 0.495 m/s², respectively. Overall, driving behavior indicators in the left lane were higher than those in the middle and right lanes, suggesting that the left and right lanes pose relatively higher driving risks. Further, factor analysis revealed that closed-type visual combinations were the most effective in enhancing vehicle control in the left and right lanes, while the wavy rhythmic pattern was better suited to improve control abilities in the middle lane. Therefore, it is recommended that closed-type visual combinations are prioritized in practical engineering applications, while wavy rhythmic patterns may be used in fatigue alert zones to enhance driving safety.