Road accidents and safe driving are one of the main concerns of transportation systems and the companies that explore different solutions to reduce the accident rate. The most interesting option to achieve this goal is through an on-board training of professional drivers to apply safe driving techniques during their work activity. The purpose of this study is to analyze a monitoring system that is not limited to the real-time vehicle tracking but is also capable of monitoring and providing real-time feedback and in-vehicle training. We analyze the influence of different sociodemographic factors on driving behavior. The analyzed data correspond to an urban public transport company, obtained from a study performed on 246 drivers. The drivers received training based on a blended learning system with an on-board feedback device, accompanied by both theoretical and practical sessions. The driving behavior of each driver is obtained from the data gathered from the vehicles that allow us to characterize their driving patterns. The information related to safe driving is completed with a list of the records of road accidents. The results of the sociodemographic influence on driving behavior provide significant information, giving an elaborated classification of safety driving patterns in order to apply intelligent transportation systems.

中文翻译：

---

驾驶模式分析和基于车载反馈的主动式道路安全监测培训

道路事故和安全驾驶是交通系统和探索不同解决方案以降低事故率的公司的主要关注点之一。实现这一目标的最有趣的选择是通过对专业驾驶员的车载培训，在他们的工作活动中应用安全驾驶技术。本研究的目的是分析一个监控系统，该系统不仅限于实时车辆跟踪，而且还能够监控并提供实时反馈和车载培训。我们分析了不同社会人口因素对驾驶行为的影响。分析的数据对应于从对 246 名司机进行的研究中获得的城市公共交通公司。驾驶员接受基于混合学习系统和车载反馈设备的培训，伴随着理论和实践课程。每个驾驶员的驾驶行为是从车辆收集的数据中获得的，这些数据使我们能够表征他们的驾驶模式。与安全驾驶相关的信息以道路事故记录清单完成。社会人口学对驾驶行为的影响结果提供了重要信息，给出了安全驾驶模式的详细分类，以便应用智能交通系统。