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Driving visual information in highway tunnel entrances: A computational method based on optical flow and color
Yunwei Meng1, Lei Wang1, Yin Zhang2
1Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation System, Chongqing Jiaotong University, Chongqing, China.
Traffic Injury Prevention
|June 9, 2025
Summary
Optimizing highway tunnel entrances by quantifying visual information is key for driver safety. Controlling traffic sign information between 15%-25.55% balances visual workload and comfort, enhancing the driving experience.
Area of Science:
- Human-Computer Interaction
- Transportation Engineering
- Environmental Psychology
Background:
- Highway tunnel entrance zones significantly influence driver performance and safety.
- Understanding the relationship between environmental information and driver visual workload is crucial for optimizing these areas.
Purpose of the Study:
- To develop a novel computational method for quantifying visual information volume in tunnel entrance zones.
- To investigate the impact of this quantified visual information on drivers' visual workload.
- To provide a theoretical basis for improving tunnel entrance environments and enhancing driving safety.
Main Methods:
- Conducted field experiments at eight highway tunnel entrances, collecting environmental images, vehicle dynamics, and driver data.
- Divided visual fields into five regions and extracted HSV values for color and texture analysis.
- Developed a model integrating optical flow, sight distance, lane width, and speed to quantify visual information volume, including traffic signs.
Main Results:
- A novel computational method was validated against subjective driver feedback.
- Complex tunnel entrances with more traffic signs showed higher visual information levels, with drivers' gaze distributed widely.
- Simpler entrances had lower visual information, concentrating driver attention on the roadway and tunnel center.
Conclusions:
- The proposed method effectively quantifies visual information and its impact on driving visual workload.
- Optimal traffic sign information (15%-25.55%) balances workload and comfort; extremes cause discomfort.
- Findings offer guidance for optimizing tunnel entrance design, sign placement, and traffic safety.
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