Thirty-Four Truck

A Drowsy Driver Warning System (DDWS) detects physiological and/or performance indications of driver drowsiness and provides feedback to drivers regarding their state. The primary function of a DDWS is to provide information that will alert drivers to their drowsy state and motivate them to seek rest or take other corrective steps to increase alertness. The system tested in this study was the Driver Fatigue Monitor (DFM) developed by Attention Technologies, Inc., which estimates PERCLOS (percent eye closure). The primary goal of this field operational test (FOT) was to determine the safety benefits and operational capabilities, limitations, and characteristics of the DFM. The FOT was conducted in a naturalistic driving environment and data were collected from actual truck drivers driving commercial trucks. During the course of the study, 46 trucks were instrumented with a Data Acquisition System (DAS). Over 100 data variables such as the PERCLOS output from the DFM and driving performance data (e.g., lane position, speed, and longitudinal acceleration) were collected. Other collected measures included video, actigraphy, and questionnaires. The FOT had 103 drivers participate. Drivers were randomly assigned to either control (24 drivers) or experimental groups (79 drivers). The data collected include the following: approximately 46,000 driving-data hours; 397 load history files from 103 drivers; approximately 195,000 hours of activity/sleep data; questionnaires from all drivers; fleet management surveys from each company; and focus group results collected from 14 drivers during two post-study focus group sessions.驾驶员疲劳预警系统（Drowsy Driver Warning System, DDWS）可检测驾驶员疲劳相关的生理及行为表现指标，或二者兼具，并向驾驶员反馈其当前状态。该系统的核心功能是向驾驶员预警自身疲劳状况，促使其及时休息或采取其他提升警觉性的纠正措施。本研究测试的系统为注意力技术有限公司（Attention Technologies, Inc.）开发的驾驶员疲劳监测仪（Driver Fatigue Monitor, DFM），该设备可估算眼闭合百分比（percent eye closure, PERCLOS）。本次实地运行测试（field operational test, FOT）的核心目标是评估该DFM的安全效益、运行性能、局限性与特性。FOT在自然驾驶环境中开展，数据采集对象为驾驶商用卡车的在职卡车驾驶员。研究期间，共有46辆卡车搭载了数据采集系统（Data Acquisition System, DAS）。本次研究共采集超100项数据变量，涵盖DFM输出的PERCLOS数据、驾驶表现数据（如车道位置、行驶车速与纵向加速度）等。此外，采集的数据还包括视频影像、体动记录数据与调查问卷。本次FOT共有103名驾驶员参与，通过随机分组分为对照组（24人）与实验组（79人）。所采集的数据包括：约46000小时的驾驶数据时长、103名驾驶员的397份加载历史文件、约195000小时的活动与睡眠数据、所有驾驶员的调查问卷、各参与企业的车队管理调研结果，以及研究结束后开展的两场焦点小组座谈会中，由14名驾驶员提供的焦点小组访谈结果。

搜集汇总

背景与挑战

背景概述

该数据集是'Thirty-Four Truck'，专注于驾驶员疲劳监测系统（DDWS）的现场操作测试，特别是测试Driver Fatigue Monitor（DFM）系统，该系统使用PERCLOS（眼闭合百分比）来评估驾驶员疲劳状态。数据收集自自然驾驶环境，涉及46辆卡车和103名卡车司机，涵盖超过100个变量，包括驾驶性能数据、视频、活动记录和问卷，总计约46,000小时驾驶数据，用于分析安全效益和系统特性。