World wide transport authorities are imposing complex Hours of Service regulations to drivers, which constraint the amount of working, driving and resting time when delivering a service. As a consequence, transport companies are responsible not only of scheduling driving plans aligned with laws that define the legal behaviour of a driver, but also of monitoring and identifying as soon as possible problematic patterns that can incur in costs due to sanctions. Transport experts are frequently in charge of many drivers and lack time to analyse the vast amount of data recorded by the onboard sensors, and companies have grown accustomed to pay sanctions rather than predict and forestall wrongdoings. This paper exposes an application for summarising raw driver activity logs according to these regulations and for explaining driver behaviour in a human readable format. The system employs planning, constraint, and clustering techniques to extract and describe what the driver has been doing while identifying infractions and the activities that originate them. Furthermore, it groups drivers based on similar driving patterns. An experimentation in real world data indicates that recurring driving patterns can be clustered from short basic driving sequences to whole drivers working days.
翻译:世界范围内的运输当局正在对司机实行复杂的服务时数规定,这限制了提供服务时的工作、驾驶和休息时间,因此,运输公司不仅负责按照界定司机法律行为的法律安排驾驶计划,而且监测和尽快查明可能因制裁而造成费用问题的模式,运输专家经常负责许多司机,没有时间分析机载传感器记录的大量数据,公司已经习惯于支付制裁,而不是预测和预防错失行为。本文披露了根据这些条例对生司机活动记录进行汇总的应用程序,以及用人可读的格式解释司机行为。该系统采用规划、限制和集群技术,提取和描述司机的行为,同时查明违规行为和由他们引起的活动。此外,它根据类似的驾驶模式将司机分组。在现实世界数据中进行的一项实验表明,经常性驾驶模式可以从短的基本驾驶顺序到整个司机工作日。