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

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

Ali, Yasir (Queensland University of Technology)
Haque, Md Mazharul (Queensland University of Technology)
Zheng, Zuduo (University of Queensland)
Afghari, A.P. (TU Delft Safety and Security Science)

2022

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.

Braking
Connected environment
Decision tree
Driving behaviour
Hierarchical
Random parameters

http://resolver.tudelft.nl/uuid:50b717ac-dd32-40b7-9110-8155a90a05e7

https://doi.org/10.1016/j.amar.2022.100221

2023-07-01

2213-6657

Analytic Methods in Accident Research, 35

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2022 Yasir Ali, Md Mazharul Haque, Zuduo Zheng, A.P. Afghari