Open AccessResearch on Liability Identification System of Road Traffic Accident
Author(s) -
Sai Liu Sai Liu,
Zhen-Jiang Zhang Sai Liu,
Zi-Hang Yu Zhen-Jiang Zhang
Publication year - 2022
Publication title -
diànnǎo xuékān/diannao xuekan
Language(s) - English
Resource type - Journals
eISSN - 2312-993X
pISSN - 1991-1599
DOI - 10.53106/199115992022023301020
Subject(s) - liability , accident (philosophy) , identification (biology) , enforcement , business , law enforcement , strict liability , crash , actuarial science , computer security , law , transport engineering , computer science , engineering , political science , finance , philosophy , botany , epistemology , biology , programming language
With the rapid development of social economy and the increasing improvement of people’s living standards, car ownership is increasing exponentially, and road traffic accidents occur frequently. The identification of liability of traffic accident is an important problem in accident handling, which relates to the life and property interests of the litigants concerned. At present, the identification of liability of traffic accident basically depends on the manual judgment of law enforcement department, which is influenced by the experience and human feelings of law enforcement personnel, and has certain randomness and uncertainty. This paper proposes a traffic accident intelligent responsibility identification system based on Case-based Reasoning and D-S Evidence Theory. In the process of liability identification, Case-based Reasoning and D-S Evidence Theory are combined to analyze cases in case database. According to the case similarity, the basic probability of the litigants bearing the main liability is fused to obtain the probability interval of each litigant bearing the main liability, so as to determine the main liability person of the accident. By testing in real cases, the method proposed in this paper has achieved outstanding effect in identifying the main liability of traffic accidents.