Driving data for simulated sleepiness, real sleep deprivation and normal controls.

The data set is an output of the Track and Know project to be shared with the scientific community. The data set contains the output of a monitoring app recorded during a series of journeys organised in two sub sets. The first subset of data was recorded from journeys made on different days around a circular route by a single driver. On different iterations of the journey the driver determined to drive either; as carefully as possible, normally or poorly. The intention of the poor driving was to imitate sleepy driving with harsh breaking, cornering and acceleration and deliberate lane drifting. The data set is designed to allow the development of algorithms to detect different driving behaviours The second data set was generated by 3 volunteers who were engaged in shift work. The journeys consist of trips to work and home at different times of day and other journeys not related to work. The intention of the data set is to allow comparisons to be made between journeys undertaken by the drivers when sleep replete and sleep deprived (after working a night shift). The data are enriched with weather information pertaining to the date, time and location of each journey.本数据集为Track and Know项目的产出成果，将向科研界公开共享。本数据集包含一款监控应用在被划分为两个子集的系列行程中记录的输出数据。 第一子集数据由一名驾驶员在多日沿环形路线行驶的行程中采集得到。在该行程的不同轮次中，驾驶员分别以尽可能谨慎、常规以及拙劣三种驾驶风格进行操作：其中拙劣驾驶的设计意图为模拟疲劳驾驶，包含急刹车、急转弯、急加速以及故意车道偏离等行为。本数据集旨在支持用于检测不同驾驶行为的算法研发。 第二子集数据由3名从事倒班工作的志愿者采集生成。其行程涵盖每日不同时段的上下班通勤，以及其他非工作相关出行。该数据集的设计目标为支持对比驾驶员在睡眠充足与睡眠剥夺（完成夜班工作后）两种状态下的驾驶行为。 数据集还补充了与每次行程的日期、时间及位置对应的气象信息。