Driving Performance Under Violations of Traffic Rules: Novice Vs. Experienced Drivers

Xu, Jiawei, Guo, Kun and Guo, Poly Z.H. (2022) Driving Performance Under Violations of Traffic Rules: Novice Vs. Experienced Drivers. IEEE Transactions on Intelligent Vehicles . pp. 1-10. ISSN 2379-8858

Full content URL: https://doi.org/10.1109/TIV.2022.3200592

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Driving Performance Under Violations of Traffic Rules: Novice Vs. Experienced Drivers
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Abstract

It is of great significance for safe driving to study drivers' eye movement and driving operation behavior when they encounter other road users violating traffic rules. The underlying reason is that most drivers are unable to process the unexpected visual stimulation, which is more likely to lead to driving accidents, especially in a hybrid situation. In this study, a driving simulator is used to design driving scenarios and study the driving performance of drivers with different driving experiences when other road users violate traffic rules. The experimental results show that some novice drivers ignore the position of their own vehicle when they encounter traffic violations which will lead to the collision with other road users. Moreover, some novice drivers can only perform one of the operations between steering and braking to avoid collision in these emergent situations. They cannot reasonably combine braking and steering to complete emergency driving operations like experienced drivers. Finally, when the driving difficulty increases, experienced drivers spend less time looking and more time scanning their surroundings to ensure that they can cope with the more complex driving environment while novice drivers do the opposite. This study reveals the difference between novices and experienced drivers, which paves a useful reference for the future advanced driving assistance system.

Keywords:Vehicles, Human Factors in Driving, Driving Ergonomics, Violation of Traffic Rules, Novice vs. Experienced Drivers
Subjects:C Biological Sciences > C830 Experimental Psychology
Divisions:College of Social Science > School of Psychology
ID Code:50508
Deposited On:09 Sep 2022 14:18

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