Liu Zhuofan, Ahlström Christer, Forsman Åsa, Kircher Katja
Xi'an University of Posts & Telecommunications, China.
The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
Hum Factors. 2020 Nov;62(7):1171-1189. doi: 10.1177/0018720819869099. Epub 2019 Aug 19.
To assess the attentional demand of different contextual factors in driving.
The attentional demand on the driver varies with the situation. One approach for estimating the attentional demand, via spare capacity, is to use visual occlusion.
Using a 3 × 5 within-subjects design, 33 participants drove in a fixed-base simulator in three scenarios (i.e., urban, rural, and motorway), combined with five fixed occlusion durations (1.0, 1.4, 1.8, 2.2, and 2.6 s). By pressing a microswitch on a finger, the driver initiated each occlusion, which lasted for the same predetermined duration within each trial. Drivers were instructed to occlude their vision as often as possible while still driving safely.
Stepwise logistic regression per scenario indicated that the occlusion predictors varied with scenario. In the urban environment, infrastructure-related variables had the biggest influence, whereas the distance to oncoming traffic played a major role on the rural road. On the motorway, occlusion duration and time since the last occlusion were the main determinants.
Spare capacity is dependent on the scenario, selected speed, and individual factors. This is important for developing workload managers, infrastructural design, and aspects related to transfer of control in automated driving.
Better knowledge of the determinants of spare capacity in the road environment can help improve workload managers, thereby contributing to more efficient and safer interaction with additional tasks.
评估驾驶中不同情境因素的注意力需求。
驾驶员的注意力需求因情况而异。一种通过剩余能力来估计注意力需求的方法是使用视觉遮挡。
采用3×5的被试内设计,33名参与者在固定基座模拟器中于三种场景(即城市、农村和高速公路)下驾驶,并结合五种固定的遮挡持续时间(1.0、1.4、1.8、2.2和2.6秒)。驾驶员通过按下手指上的微动开关启动每次遮挡,每次试验中遮挡持续相同的预定持续时间。驾驶员被要求在安全驾驶的同时尽可能频繁地遮挡视线。
每个场景的逐步逻辑回归表明,遮挡预测因素因场景而异。在城市环境中,与基础设施相关的变量影响最大,而在农村道路上,与对向车辆的距离起主要作用。在高速公路上,遮挡持续时间和自上次遮挡以来的时间是主要决定因素。
剩余能力取决于场景、所选速度和个体因素。这对于开发工作量管理系统、基础设施设计以及与自动驾驶中的控制权转移相关的方面很重要。
更好地了解道路环境中剩余能力的决定因素有助于改进工作量管理系统,从而有助于与额外任务进行更高效、更安全的交互。