Research on Spiral Tunnel Exit Speed Prediction Model Based on Driver Characteristics
Abstract
:1. Introduction
2. Real Car Driving Experiment
2.1. Experimental Conditions
2.2. Experimental Procedure
3. Speed Prediction Modeling and Analysis
3.1. Selection of Data Indicators
3.1.1. Speed Distribution
3.1.2. Illumination Change
3.1.3. Driver Pupil Changes
3.2. Speed Prediction Model
3.2.1. NARX Model
3.2.2. Model Process and Results
4. Traffic Safety Risk Evaluation
4.1. Driving Sight Distance Calculation
4.2. Driving Load
4.3. Follow Time Distance
4.4. K-Means-Based Clustering Analysis of Driving Behavior
4.4.1. Clustering Analysis of Driving Behavior
4.4.2. Driving Behavior Expectations
4.5. Tunnel Exit Phase Predicted Speed Analysis
4.6. Tunnel Exit Phase Speed Control Measures
5. Conclusions
- (1)
- The driver is influenced by the exit environment. Under extreme concentration, the driving load fluctuates noticeably. According to an analysis of the tunnel exit section’s driver characteristics and environmental features, the vehicle’s speed decreased continuously during both the uphill and downhill spiral phases in the tunnel exit section. Due to the effect of road alignment, the uphill spiral speed decreased more gradually than the downhill spiral speed. As the illumination of the tunnel’s exit section fluctuated drastically, causing the drivers’ pupils to contract rapidly, the drivers’ field of vision constantly decreased. The drivers slowed down during vehicle braking, and load fluctuations caused changes in the environment. The substantial influence of ecological illumination on the drivers during the tunnel exit phase has a negative effect on traffic safety [25].
- (2)
- During the tunnel’s exit phase, the drivers’ driving behavior and driving expectations changed significantly. During the tunnel exit phase, the reduced visual range and fluctuating driving load significantly altered the drivers’ behavior. The closer a driver was to the exit, the more aggressive their driving behavior became. Taking into account behavioral factors in driving expectations revealed a downward trend in driving expectations. 75 m before tunnel exit, the expected speed was as low as 18.98 km/h. This demonstrates that effective control of the drivers’ speed during the tunnel’s exit phase had a significant impact on traffic safety during the tunnel’s exit phase.
- (3)
- Setting dynamic safety and comfort speeds to keep drivers comfortable during the tunnel exit phase can effectively reduce tunnel exit traffic risk. Taking into account significant differences in the environmental impact and substantial changes in driver characteristics during the tunnel exit phase, setting variable speed limits within the safe driving speed tolerance range and decreasing speed dispersion is advantageous to the safe operation of tunnel exit phase traffic.
6. Discussions and Perspectives
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Vehicle Speed (km/h) | Critical Safety Distance (m) | Early Warning Safety Distance (m) |
---|---|---|
100.2157 | 63.713 | 163.929 |
80 | 41.086 | 121.086 |
73 | 34.404 | 107.404 |
68 | 29.996 | 97.996 |
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Xu, X.; Kang, X.; Wang, X.; Zhao, S.; Si, C. Research on Spiral Tunnel Exit Speed Prediction Model Based on Driver Characteristics. Sustainability 2022, 14, 15736. https://doi.org/10.3390/su142315736
Xu X, Kang X, Wang X, Zhao S, Si C. Research on Spiral Tunnel Exit Speed Prediction Model Based on Driver Characteristics. Sustainability. 2022; 14(23):15736. https://doi.org/10.3390/su142315736
Chicago/Turabian StyleXu, Xiaoling, Xuejian Kang, Xiaoping Wang, Shuai Zhao, and Chundi Si. 2022. "Research on Spiral Tunnel Exit Speed Prediction Model Based on Driver Characteristics" Sustainability 14, no. 23: 15736. https://doi.org/10.3390/su142315736