Moral-García Serafín, Castellano Javier G, Mantas Carlos J, Montella Alfonso, Abellán Joaquín
Department of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain.
Department of Civil, Architectural, and Environmental Engineering, University of Naples Federico II, 80125 Naples, Italy.
Entropy (Basel). 2019 Apr 3;21(4):360. doi: 10.3390/e21040360.
Presently, there is a critical need to analyze traffic accidents in order to mitigate their terrible economic and human impact. Most accidents occur in urban areas. Furthermore, driving experience has an important effect on accident analysis, since inexperienced drivers are more likely to suffer fatal injuries. This work studies the injury severity produced by accidents that involve inexperienced drivers in urban areas. The analysis was based on data provided by the Spanish General Traffic Directorate. The information root node variation (IRNV) method (based on decision trees) was used to get a rule set that provides useful information about the most probable causes of fatalities in accidents involving inexperienced drivers in urban areas. This may prove useful knowledge in preventing this kind of accidents and/or mitigating their consequences.
目前，迫切需要对交通事故进行分析，以减轻其可怕的经济和人员影响。大多数事故发生在城市地区。此外，驾驶经验对事故分析有重要影响，因为缺乏经验的驾驶员更容易遭受致命伤害。这项工作研究了城市地区涉及缺乏经验驾驶员的事故所造成的伤害严重程度。分析基于西班牙交通总局提供的数据。使用信息根节点变异（IRNV）方法（基于决策树）来获得一组规则，这些规则提供了有关城市地区涉及缺乏经验驾驶员的事故中最可能的死亡原因的有用信息。这可能是预防此类事故和/或减轻其后果的有用知识。
