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注意力中断对驾驶行为模式的影响:急动度成本函数和车辆控制数据的分析。

The effects of disruption in attention on driving performance patterns: analysis of jerk-cost function and vehicle control data.

机构信息

Department of Biomedical Engineering, Research Institute of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, 322 Danwol-dong, Chungju-si, Chungcheongbuk-do, South Korea.

出版信息

Appl Ergon. 2013 Jul;44(4):538-43. doi: 10.1016/j.apergo.2012.11.004. Epub 2012 Dec 2.

Abstract

This study analyzes the effects of attention disruption factors, such as sending text messages (STM) and performing searching navigation (SN) on driving performance patterns while actively driving, centering on motion signals. To this end, it analyzes not only data on control of the vehicle including the Anterior-Posterior Coefficient of Variation (APCV), Medial-Lateral Coefficient of Variation (MLCV), and Deviation of Vehicle Speed but also motion data such as the Jerk-Cost function (JC). A total of 55 drivers including 28 males (age: 24.1 ± 1.5, driving experience: 1.8 years ± 1.7 years) and 27 females (age: 23.8 ± 2.6, driving experience: 1.5 ± 1.0) participated in this study. All subjects were instructed to drive at a constant speed (90 km/h) for 2 min while keeping a distance of 30 m from the front car also running at a speed of 90 km/h. They were requested to drive for the first 1 min and then drive only (Driving Only) or conduct tasks while driving for the subsequent 1 min (Driving + STM or Driving + SN). The information on APCV, MLCV, and deviation of speed were delivered by a driving simulator. Furthermore, the motion signal was measured using 4 high-speed infrared cameras and based on the measurement results, JCs in a total of 6 parts including left shoulder (L.shoulder), left elbow (L.elbow), left hand (L.hand), right knee (R.knee), right ankle (R.ankle), and right toe (R.toe) were calculated. Differences among the results of 3 conditions of experiment, Driving Only, Driving + STM, and Driving + SN, were compared and analyzed in terms of APCV, MLCV, Deviation of Vehicle Speed, and JC. APCV and Deviation of Vehicle Speed increased in Driving + SN, rather than in Driving Only. MLCV increased in Driving + STM and Driving + SN, rather than in Driving Only. In the case of most JCs except that of L.hand, the values increased in Driving + SN, compared to Driving Only. This study indicated that JC could be a reliable parameter for the evaluation of driving performance patterns. In addition, it was discovered that additional tasks under driving, such as STM and SN, impaired smoothness or proficiency in driving motion, thereby increasing anterior-posterior and medio-lateral variability and deviation of speed.

摘要

本研究以运动信号为中心,分析了驾驶过程中发短信(STM)和执行搜索导航(SN)等注意力分散因素对驾驶性能模式的影响。为此,它不仅分析了包括前后变化系数(APCV)、左右变化系数(MLCV)和车速偏差在内的车辆控制数据,还分析了诸如急动成本函数(JC)等运动数据。共有 55 名驾驶员参与了这项研究,其中 28 名男性(年龄:24.1±1.5 岁,驾龄:1.8 年±1.7 年)和 27 名女性(年龄:23.8±2.6 岁,驾龄:1.5 年±1.0 年)。所有受试者都被要求以 90 公里/小时的恒定速度行驶 2 分钟,同时与以同样速度行驶的前车保持 30 米的距离。他们被要求在前 1 分钟内只开车(仅驾驶),然后在随后的 1 分钟内仅开车(驾驶+STM 或驾驶+SN)或在驾驶时执行任务。APCV、MLCV 和速度偏差信息由驾驶模拟器提供。此外,运动信号通过 4 台高速红外摄像机进行测量,并根据测量结果,计算了总共 6 个部分(左肩部(L.shoulder)、左肘部(L.elbow)、左手(L.hand)、右膝(R.knee)、右踝(R.ankle)和右脚脚趾(R.toe))的 JC。在仅驾驶、驾驶+STM 和驾驶+SN 这 3 种实验条件下,对 APCV、MLCV、车速偏差和 JC 的结果进行了比较和分析。结果发现,与仅驾驶相比,在驾驶+SN 中 APCV 和车速偏差增加,而在仅驾驶中则没有。在驾驶+STM 和驾驶+SN 中,MLCV 增加,而在仅驾驶中则没有。除了 L.hand 的 JC 之外,在大多数情况下,与仅驾驶相比,驾驶+SN 时 JC 值增加。本研究表明,JC 可能是评估驾驶性能模式的可靠参数。此外,研究还发现,驾驶过程中执行的诸如 STM 和 SN 等附加任务会降低驾驶动作的平稳性或熟练度,从而增加前后和左右的可变性以及车速偏差。

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