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Traffic accident modelling via self-exciting point processes

机译:通过自激励点过程进行交通事故建模

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摘要

Traffic accidents may pose a high risk with respect to human travel safety. In order to improve the safety of travelling, an insight into the traffic accidents is needed. This requires a practical and specifically approach when it comes to modelling for traffic accidents. This paper presents a traffic accident model based on self-exciting processes, which describes the specific phenomena and problems in traffic accidents. The research focuses on the stationary condition, reliability and safety analysis of the traffic network in a certain city or the traffic situation in a certain area. First, a traffic accident model based on self-exciting processes is developed, and secondly, the stationary condition of the model is studied, which is used to analyze the reliability and safety of the traffic network in a certain city or the traffic situation in a certain area. In addition, the probability and related characteristics for traffic process are evaluated by simulation methods. The traffic accident model is developed with the use of self-exciting processes. Maximum Likelihood Estimate (MLE) is used for the parameter estimations of the traffic accident model. Finally, a numerical example is presented, in which the traffic accident model developed is applied to the simulation data.
机译:交通事故可能会对人员出行安全构成高风险。为了提高出行的安全性,需要深入了解交通事故。在交通事故建模方面,这需要一种实用且专门的方法。本文提出了一种基于自激过程的交通事故模型,描述了交通事故中的具体现象和问题。研究重点是某城市或某区域交通状况的交通网络的稳态,可靠性和安全性分析。首先,建立了基于自激过程的交通事故模型,其次,研究了模型的平稳状态,用于分析某城市交通网络或某城市交通状况的可靠性和安全性。某些区域。此外,通过模拟方法评估交通过程的概率和相关特征。交通事故模型是使用自激过程开发的。最大似然估计(MLE)用于交通事故模型的参数估计。最后,给出了一个数值示例,其中将开发的交通事故模型应用于仿真数据。

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