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Modelling the response times of mobile phone distracted young drivers: A hybrid approach of decision tree and random parameters duration model

journal contribution
posted on 2023-07-05, 14:30 authored by Yasir AliYasir Ali, Md Mazharul Haque
Research has shown the detrimental effects of using mobile phones whilst driving, which are more prominent and concerning for young drivers, who are often less experienced and riskier. As such, this study investigates young drivers’ response times when they encounter a safety–critical event on a suburban road whilst using a mobile phone. To collect high-quality trajectory data, the CARRS-Q advanced driving simulator was used. Thirty-two licenced young drivers were exposed to the sudden braking of the lead vehicle in their lane in three driving conditions: baseline (no phone conversation), handheld, and hands-free. Unlike extant studies, this paper proposes a hybrid modelling framework for the response times of distracted drivers. This framework combines a decision tree model and a correlated grouped random parameters duration model with heterogeneity-in-means. While the decision tree model identifies a priori relationship among main effects, the random parameter model captures unobserved heterogeneity and correlation between random parameters. The modelling results reveal that mobile phone distraction impairs response time behaviour for the majority of drivers. However, some drivers tend to respond earlier whilst being distracted, suggesting that the perceived risk of mobile use might have led to an early response, indicating their risk compensation behaviour. Female drivers tend to respond earlier compared to male drivers, indicating their safer and risk-averse behaviour. Overall, mobile phone distraction appears to deteriorate response time behaviour and poses a significant safety concern to drivers and the overall traffic stream unless mitigated.

History

School

  • Architecture, Building and Civil Engineering

Published in

Analytic Methods in Accident Research

Volume

39

Issue

2023

Publisher

Elsevier

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in Analytic Methods in Accident Research published by Elsevier. The final publication is available at https://doi.org/10.1016/j.amar.2023.100279. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2023-04-20

Publication date

2023-04-26

Copyright date

2023

eISSN

2213-6657

Language

  • en

Depositor

Dr Yasir Ali. Deposit date: 3 July 2023

Article number

100279

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