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.

在互联环境中共享信息的动机是协助驾驶员进行操作，战术和战略决策，并改善驾驶任务的绩效。在安全关键事件期间，此类信息辅助对驾驶员决策和任务执行的影响尚不十分清楚。因此，本研究着重于了解互联环境对加速度噪声和响应时间的影响，以此作为任务绩效和安全关键事件决策的指标。为了克服连接的环境数据的不足，设计并进行了高级驾驶模拟器实验。在连接的环境中，驾驶员可以使用三类不间断的信息，即连续信息，按时事件触发的信息，以及高级事件触发信息。模拟器实验中设计的关键安全事件是领导者在跟车情况下的紧急制动行为。在连接环境中，驱动程序会收到有关此安全关键事件的高级消息。为了在安全关键的情况下对驾驶员的决策建模，采用了随机参数建模方法来解决驾驶员决策中未观察到的异质性。因此，分别针对响应时间和加速度噪声估算了基于分组的随机参数危害持续时间模型和分组的随机参数线性回归模型（均在参数均值方面具有异质性）。结果表明，与传统环境相比，在互联环境中加速度噪声降低，而在互联环境中响应时间可以增加或减少。为了更好地理解这种对响应时间的混合影响，进行了决策树分析。对于人为因素，结果表明，与中年或中年驾驶员相比，年轻驾驶员更多地利用了互联环境。总体而言，驾驶员表现出稳定的驾驶行为，因为他们有更多的时间做出反应，因此在连接环境中对安全至关重要的情况下处于低风险中。结果表明，与中年或中年驾驶员相比，年轻驾驶员更多地利用了互联环境。总体而言，驾驶员表现出稳定的驾驶行为，因为他们有更多的时间做出反应，因此在连接环境中对安全至关重要的情况下处于低风险中。结果表明，与中年或中年驾驶员相比，年轻驾驶员更多地利用了互联环境。总体而言，驾驶员表现出稳定的驾驶行为，因为他们有更多的时间做出反应，因此在互联环境中对安全至关重要的情况下处于较低的风险中。