Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations

被引:56
作者
Sharma, Anshuman [1 ]
Zheng, Zuduo [1 ]
Kim, Jiwon [1 ]
Bhaskar, Ashish [2 ]
Haque, Md Mazharul [2 ]
机构
[1] Univ Queensland, Sch Civil Engn, Brisbane, Qld 4072, Australia
[2] Queensland Univ Technol QUT, Sci & Engn Fac, Sch Civil Engn & Built Environm, 2 George St, Brisbane, Qld 4001, Australia
基金
澳大利亚研究理事会;
关键词
Connected vehicle; Connected environment; Safety; Grouped random parameters; Decision tree; Decision making; Task performance; LANE-CHANGING BEHAVIOR; CAR-FOLLOWING BEHAVIOR; MOBILE PHONE USE; TIME-HEADWAY; COLLISION-AVOIDANCE; ACCELERATION NOISE; INJURY-SEVERITIES; DURATION MODEL; CONTROL-SYSTEM; STABILITY;
D O I
10.1016/j.amar.2020.100127
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
The motive of sharing the information in a connected environment is to assist a driver in operational, tactical, and strategic decision making and improving driving task performance. The influence of such information assistance on driver decision making and task performance during safety-critical events is not well understood. Thus, this study focusses on understanding the impact of connected environment on the acceleration noise and the response time as indicators of task performance and the decision making involved in safety-critical events. To overcome the paucity of connected environment data, an advanced driving simulator experiment is designed and conducted. Three categories of uninterrupted information are available to drivers in connected environment scenario, namely continuous information, on-time event-triggered information, and advanced event-triggered information. The safety-critical event designed in the simulator experiment is the leader's hard braking behaviour in car-following regime. In connected environment scenario, drivers receive an advanced message for this safety-critical event. To model drivers' decision in safety-critical situations, random parameters modelling approaches are adopted to account for the unobserved heterogeneities in drivers' decision. Consequently, a grouped random parameters hazard-based duration model and a grouped random parameters linear regression model-both with heterogeneity in parameter means-are estimated for the response time and the acceleration noise, respectively. Results show that the acceleration noise reduces in connected environment while the response time can either increase or decrease in connected environment compared to those in the traditional environment. To better understand this mixed effect on response time, a decision tree analysis is conducted. For human factors, the results demonstrate that young drivers take more advantage of connected environment relative to the middle-aged or old drivers. Overall, drivers exhibit stable driving behaviour because they have more time to react and thus, are at low risk in safety-critical situations in connected environment. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:24
相关论文
共 2 条
  • [1] Modelling lane-changing execution behaviour in a connected environment: A grouped random parameters with heterogeneity-in-means approach
    Ali, Yasir
    Zheng, Zuduo
    Haque, Md Mazharul
    COMMUNICATIONS IN TRANSPORTATION RESEARCH, 2021, 1
  • [2] A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment
    Ali, Yasir
    Haque, Md. Mazharul
    Zheng, Zuduo
    Afghari, Amir Pooyan
    ANALYTIC METHODS IN ACCIDENT RESEARCH, 2022, 35