4.6 Article

A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment

Journal

ANALYTIC METHODS IN ACCIDENT RESEARCH
Volume 35, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.amar.2022.100221

Keywords

Connected environment; Braking; Driving behaviour; Hierarchical; Random parameters; Decision tree

Funding

  1. Australian Research Council Discovery Grants [DP210102970]

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This study examines the braking behavior of drivers in response to a pedestrian at a zebra crossing in a connected environment. The results show that in the connected environment, drivers take longer to reduce their speed, and the braking time is influenced by factors such as the distance to the pedestrian and the gender of the driver.
Driver's response to a pedestrian crossing requires braking, whereby both excess and inadequate braking is directly associated with crash risk. The highly anticipated connected environment aims to increase drivers' situational awareness by providing advanced information and assisting them during critical driving tasks such as braking. Focussing on this crucial behaviour and combined with the promise of a connected environment, the objective of this study is to examine the braking behaviour of drivers in response to a pedestrian at a zebra crossing in a connected environment. Seventy-eight participants from diverse backgrounds performed this driving task in the CARRS-Q Advanced Driving Simulator in two randomised driving scenarios: a baseline scenario (without driving aids) and a connected environment (with driving aids) scenario. A Weibull accelerated failure time duration modelling approach is adopted to model the braking behaviour of drivers. In particular, this duration model is specified to capture the panel nature of the data and unobserved heterogeneity through correlated grouped random parameters with heterogeneity-in-the-means in the Bayesian framework. Results indicate that, for most drivers in the connected environment, it takes longer to reduce their speed with less speed variation and a larger safety margin. In addition, a decision tree analysis for the braking time suggests that for older drivers, when the distance to the zebra crossing is larger in the connected environment than that in the baseline scenario, braking time is likely to increase. The model also reveals that the braking time of female drivers is longer in the connected environment compared to that of male drivers. Overall, the connected environment is associated with increased braking time by providing advanced information, giving drivers additional time to smoothly reduce their speed in response to a pedestrian at a zebra crossing, and ultimately making the vehicle-pedestrian interaction safer.(c) 2022 Elsevier Ltd. All rights reserved.

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