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MODELING BRAKE-REACTION TIME IN CAR-FOLLOWING BEHAVIOUR BASED ON HUMAN FACTORS

机译:基于人类因素的汽车跟踪行为中建模制动反应时间

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This paper develops brake-reaction time (BRT) models for car-following analysis based on human factors. The study evaluates the effect of driver characteristics and kinematic conditions on the driver’s BRT in a car-following task. The traffic kinematic conditions introduce urgency and expectancy based on the lead vehicle’s braking behaviour at different speeds and spacing. The kinematic conditions are classified as normal, surprised, and stationary. Data are collected on a driving simulator integrated into a real car and include the BRT as a dependent variable and driver’s age, gender, average driving hours per week, driving experience, vehicle speed, and spacing as independent variables. The results show that there is a significant difference in the BRT at normal, surprised, and stopped scenarios and support the hypothesis that both urgency and expectancy have significant effects on BRT. Driver’s age, gender, speed, and spacing are found to be significant variables in all scenarios.
机译:本文介绍了基于人为因素的汽车跟踪分析的制动反应时间(BRT)模型。该研究评估了驾驶员特征和运动条件在驾驶员BRT上的效果。交通运动条件介绍基于不同速度和间距的引线的制动行为的紧迫性和期望。运动条件被归类为正常,惊讶和静止的。在集成到真实汽车的驾驶模拟器上收集数据,并将BRT作为依赖变量和驾驶员年龄,性别,平均驾驶时间每周,驾驶经验,车辆速度和间距作为独立变量。结果表明,BRT在正常,惊讶和停止的情景中存在显着差异,并支持真正的假设,即紧急性和寿命对BRT有显着影响。司机的年龄,性别,速度和间距被发现在所有场景中都是显着的变量。

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