智能化交通事故责任认定模型研究

Study on Intelligent Liability Judgment Model for Traffic Accident

将概念学习和统计模式识别方法引入交通事故责任认定的研究领域 ,提出用于分析交通事故当事人的过错行为与交通事故责任之间关系的智能化责任认定模型 (ILJM)的理论框架。将某城市 1997年已处理结案的典型交通事故案例作为学习样本 ,构建了智能化的交通事故责任认定模型。

Concept learning and statistical pattern recognition applied in the field of traffic accident liability judgment, this paper introduces the Intellectualized Liability Judgment Model (ILJM) in analyzing the relationships between the accident parties' fault action and the liability grade. By using a number of closed cases in certain Cities in 1997 as learning object, the intellectualized traffic accident liability judgment model is proposed. As a new decision support approach, ILJM has the following characteristics:It borrows semantic models as a way of analysis of the learning objects, so it is a flexible and simple method.It is effective to help with acquiring knowledge. The production rules of liability judgment that is generated by this method can be renovated and improved through constant learning. Based on the research of ILJM, this paper is to propose a theoretical framework of the Intelligent Support System of traffic accident liability judgment, which is fit for the work of traffic accident handlers.