基于车载记录仪数据的车辆风险模型实证

随着计算机技术的发展,越来越多的车载记录仪(in-vehicle data recorders,简称IVDR)因为商业目的被安装到了车辆上.在获取更多实时车辆行驶数据的前提下,也为车辆事故原因的分析提供了更加丰富的数据基础.本文通过对车载记录仪的数据进行分析并结合不同车辆的驾驶条件与环境因素开展车辆风险因素研究具有一定的理论价值与实践创新.研究运用大量的行驶数据、地理位置等数据信息,建立多元线性回归模型对车辆风险与事故关系进行研究并对所得结果进行了实证检验.过研究发现车辆风险因素与事故之间的影响关系:行驶里程与发生事故的概率存在非线性关系等.望通过本研究能对车辆风险量化、交通出行规划、车险个性化定价提供一定的借鉴作用.

Empirical Study of Vehicle Risk Model Based on IVDR Data

As the development of computer science, the commercial applications of In-Vehicle Data Recorders (IVDR) are growing rapidly. With the real-time vehicle travelling data, the implications of IVDR facilitate the rich data base of traffic accident causal analysis. Combining IVDR data analysis with driving conditions and environmental factors of different vehicles, this paper carries out the study on vehicle risk factors. On the basis of a large amount of driving and geographic location information, this study builds multiple linear regression models to analyze the relationship between vehicle risk and traffic accident, and applies empirical test to the research results. This research indicates the interact relationship between vehicle risk factors and traffic accidents, for instance, that the nonlinear relationship between travelling distance and accident probability and etc. It is expected that this study would provide useful preference for vehicle risk quantification, transport planning, and vehicle personalized pricing.