Driving visual information in highway tunnel entrances: A computational method based on optical flow and color quantification

The environmental landscape of highway tunnel entrance zones is closely related to driving performance. To investigate the impact mechanism of environmental information volume on drivers’ visual workload in tunnel entrance zones, this study proposes a novel computational method for quantifying visual information. The aim is to provide a theoretical basis for improving tunnel entrance environments and enhancing driving safety. Field experiments on highways collected environmental images, vehicle dynamics, and drivers’ speed and psychological data from eight tunnel entrances. Visual field images were divided into five regions based on attention range: upper portal, central portal, left/right roadside, and pavement. HSV values were extracted to describe color and texture features. A model combining optical flow, sight distance, lane width, and speed quantified visual information volume, including traffic signs, and analyzed its relationship with visual workload. The subjective questionnaire results were consistent with the objective computational findings, verifying the reliability of the proposed method. Tunnel entrances with complex landscapes and diverse traffic signs exhibited higher levels of visual information, with drivers’ gaze distributed across four areas: both sides of the road, the tunnel entrance center, and the roadway. In contrast, entrances with simpler landscapes and fewer signs had lower visual information levels, and drivers’ gaze was mainly concentrated on the roadway and the tunnel entrance center. The proposed visual information quantification method effectively evaluates the impact of tunnel entrance environmental characteristics on driving visual workload. Appropriately controlling the proportion of traffic sign information (15%–25.55%) helps balance visual workload and comfort, while excessive or insufficient information may lead to discomfort due to underload or overload. These findings provide theoretical guidance and practical recommendations for optimizing tunnel entrance landscape design, traffic sign arrangement, and traffic safety enhancement.