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Impact of distraction on decision making at the onset of yellow signal
Transportation Research Part C: Emerging Technologies ( IF 7.6 ) Pub Date : 2020-08-04 , DOI: 10.1016/j.trc.2020.102741
Pushpa Choudhary , Nagendra R. Velaga

The current study shows the impact of distraction in designing the intelligent in-vehicle systems for assisting the drivers to make stop/cross decision at the onset of yellow signal. In total, 83 participants drove through a simulated urban scenario with six signalised intersections. Firstly, the time taken to execute the stop/cross decision was statistically modelled by using Weibull AFT (Accelerated Failure Time) models. The results showed that compared to the baseline, eating and drinking tasks reduced the stopping time by 6% and 7% respectively. For the crossing encounters, the eating task caused 12% increment in crossing time compared to the baseline. This analysis was followed by modelling the success rates of the executed decisions with binary logistic models. The success rates of the stopping decision showed that reduction in the time lapsed in executing the decision led to failure in stopping the vehicle before the stop line. Similarly, an increment in the time taken to execute the crossing decision led to reduced probability of successfully crossing the stop line within the yellow duration. Hence, the results suggest that the design of the smart assistance system for decision making at the onset of yellow signal should be based on the success rate of the decision which is dependent on the time lapsed in executing the decision. Moreover, the presence of distracting activities should be considered as an input parameter while designing the assistance system.



中文翻译:

黄色信号出现时分心对决策的影响

当前的研究显示了分心在设计智能车载系统中的影响,该系统可帮助驾驶员在黄色信号开始时做出停车/交叉决策。共有83位参与者开车经过带有六个信号交叉口的模拟城市场景。首先,通过使用Weibull AFT(加速故障时间)模型对执行停止/交叉决策所需的时间进行统计建模。结果表明,与基线相比,饮食任务减少了6%的停止时间和7%的停止时间。对于相交,相较于基线,进食任务导致相交时间增加了12%。在进行此分析之后,使用二进制逻辑模型对执行的决策的成功率进行建模。停止决策的成功率表明,执行决策所花费的时间减少导致在停止线之前停止车辆失败。同样,执行穿越决策所需的时间增加导致黄色持续时间内成功穿越停车线的可能性降低。因此,结果表明,在黄色信号开始时进行决策的智能辅助系统的设计应基于决策的成功率,该成功率取决于执行决策所花费的时间。此外,在设计援助系统时,应将分散注意力的活动的存在作为输入参数。执行交叉决策所需时间的增加导致黄色持续时间内成功越过停车线的可能性降低。因此,结果表明,在黄色信号开始时进行决策的智能辅助系统的设计应基于决策的成功率,该成功率取决于执行决策所花费的时间。此外,在设计援助系统时,应将分散注意力的活动的存在作为输入参数。执行交叉决策所需时间的增加导致黄色持续时间内成功越过停车线的可能性降低。因此,结果表明,在黄色信号开始时进行决策的智能辅助系统的设计应基于决策的成功率,该成功率取决于执行决策所花费的时间。此外,在设计援助系统时,应将分散注意力的活动的存在作为输入参数。结果表明,在出现黄色信号时用于决策的智能辅助系统的设计应基于决策的成功率,该成功率取决于执行决策所花费的时间。此外,在设计援助系统时,应将分散注意力的活动的存在作为输入参数。结果表明,在出现黄色信号时用于决策的智能辅助系统的设计应基于决策的成功率,该成功率取决于执行决策所花费的时间。此外,在设计援助系统时,应将分散注意力的活动的存在作为输入参数。

更新日期:2020-08-04
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