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

机译:基于人为因素的跟车行为制动反应时间建模

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This paper develops brake-reaction time (BRT) models for car-following analysis based onhuman factors. The study evaluates the effect of driver characteristics and kinematic conditions on thedriver’s BRT in a car-following task. The traffic kinematic conditions introduce urgency and expectancybased on the lead vehicle’s braking behaviour at different speeds and spacing. The kinematic conditionsare classified as normal, surprised, and stationary. Data are collected on a driving simulator integratedinto a real car and include the BRT as a dependent variable and driver’s age, gender, average drivinghours per week, driving experience, vehicle speed, and spacing as independent variables. The resultsshow that there is a significant difference in the BRT at normal, surprised, and stopped scenarios andsupport 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:本文发展了基于的汽车跟踪分析的制动反应时间(BRT)模型 人为因素。该研究评估了驾驶员特征和运动条件的影响 司机的BRT在汽车之后的任务中。交通运动条件引入紧急和期望 基于引线车辆以不同速度和间距的制动行为。运动条件 被归类为正常,惊讶和静止。在驾驶模拟器上收集数据集成的数据 进入一辆真正的汽车,包括BRT作为依赖变量和驾驶员年龄,性别,平均驾驶 每周小时,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,惊讶和停止的场景中存在显着差异和 支持假设,即紧急和寿命对BRT有显着影响。司机的年龄, 在所有场景中发现性别,速度和间距都是显着的变量。

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