Literature DB >> 27450793

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies.

Gustav Markkula1, Johan Engström2, Johan Lodin3, Jonas Bärgman4, Trent Victor5.   

Abstract

Driver braking behavior was analyzed using time-series recordings from naturalistic rear-end conflicts (116 crashes and 241 near-crashes), including events with and without visual distraction among drivers of cars, heavy trucks, and buses. A simple piecewise linear model could be successfully fitted, per event, to the observed driver decelerations, allowing a detailed elucidation of when drivers initiated braking and how they controlled it. Most notably, it was found that, across vehicle types, driver braking behavior was strongly dependent on the urgency of the given rear-end scenario's kinematics, quantified in terms of visual looming of the lead vehicle on the driver's retina. In contrast with previous suggestions of brake reaction times (BRTs) of 1.5s or more after onset of an unexpected hazard (e.g., brake light onset), it was found here that braking could be described as typically starting less than a second after the kinematic urgency reached certain threshold levels, with even faster reactions at higher urgencies. The rate at which drivers then increased their deceleration (towards a maximum) was also highly dependent on urgency. Probability distributions are provided that quantitatively capture these various patterns of kinematics-dependent behavioral response. Possible underlying mechanisms are suggested, including looming response thresholds and neural evidence accumulation. These accounts argue that a naturalistic braking response should not be thought of as a slow reaction to some single, researcher-defined "hazard onset", but instead as a relatively fast response to the visual looming cues that build up later on in the evolving traffic scenario.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Keywords:  Deceleration; Kinematics; Reaction time; Rear-end crashes; Visual looming

Mesh:

Year:  2016        PMID: 27450793     DOI: 10.1016/j.aap.2016.07.007

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  5 in total

1.  Accumulation of continuously time-varying sensory evidence constrains neural and behavioral responses in human collision threat detection.

Authors:  Gustav Markkula; Zeynep Uludağ; Richard McGilchrist Wilkie; Jac Billington
Journal:  PLoS Comput Biol       Date:  2021-07-15       Impact factor: 4.475

2.  The effect of varying levels of vehicle automation on drivers' lane changing behaviour.

Authors:  Ruth Madigan; Tyron Louw; Natasha Merat
Journal:  PLoS One       Date:  2018-02-21       Impact factor: 3.240

3.  A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task.

Authors:  Jami Pekkanen; Otto Lappi; Paavo Rinkkala; Samuel Tuhkanen; Roosa Frantsi; Heikki Summala
Journal:  R Soc Open Sci       Date:  2018-09-05       Impact factor: 2.963

4.  Predicting takeover response to silent automated vehicle failures.

Authors:  Callum Mole; Jami Pekkanen; William Sheppard; Tyron Louw; Richard Romano; Natasha Merat; Gustav Markkula; Richard Wilkie
Journal:  PLoS One       Date:  2020-11-30       Impact factor: 3.240

5.  How to quantitatively evaluate safety of driver behavior upon accident? A biomechanical methodology.

Authors:  Wen Zhang; Jieer Cao; Jun Xu
Journal:  PLoS One       Date:  2017-12-14       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.