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Entropy-Based Effect Evaluation of Delineators in Tunnels on Drivers' Gaze Behavior
Xueyan Han1, Yang Shao1, Shaowei Yang1
1Transportation Technology Building, Chang'an University, Xi'an 710064, China.
Entropy (Basel, Switzerland)
|December 8, 2020
Summary
Tunnel delineators improve driver safety by enhancing cognition and reducing visual fatigue. This study found that delineators, particularly wall and pavement types, decrease visual complexity and driver attention switching in tunnels.
Area of Science:
- Traffic Safety
- Human Factors Engineering
- Cognitive Psychology
Background:
- Driving safety in tunnels is a significant concern.
- Delineators can improve drivers' immediate environmental awareness and safety.
Purpose of the Study:
- To investigate the impact of tunnel delineators on driver gaze behavior.
- To quantify the complexity of driver visual scanning patterns using Markov chains and entropy analysis.
Main Methods:
- A simulation study involving 25 participants.
- Analysis of fixation position, fixation duration, and scanpath patterns.
- Modeling driver AOI switching as Markov chains and calculating transition (Ht) and stationary (Hs) entropy.
Main Results:
- Delineators attract driver attention, focusing it on the pavement.
- Tunnels with both wall and pavement delineators resulted in lower transition and stationary entropy (Ht and Hs).
- Straight tunnel sections showed higher entropy values (Ht and Hs) compared to curves.
Conclusions:
- Tunnel delineators enhance driver focus and reduce visual complexity, potentially decreasing visual fatigue.
- The findings suggest optimal delineator configurations can improve tunnel driving safety and comfort.
