Modeling and predicting vehicle accident occurrence in Chattanooga, Tennessee
Modeling and predicting vehicle accident occurrence in Chattanooga, Tennessee
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建模和预测田纳西州查塔努加的车辆事故发生
DOI：
10.1016/j.aap.2020.105860
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发表时间：
2021
影响因子：
5.9
通讯作者：
Sartipi, Mina
中科院分区：
文献类型：
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作者：
Roland, Jeremiah;Way, Peter D.;Firat, Connor;Doan, Thanh-Nam;Sartipi, Mina
鉴于车祸发生危及大多数人生命的威胁一直存在，需要采取预防措施来遏制车祸的发生。从危险的天气到危险的道路条件，在研究事故发生时有大量的因素需要考虑。为了解决这个问题，我们提出了一种使用多层感知器模型来预测田纳西州查塔努加市任何一天的事故热点位置的方法。该模型分析事故及其相关的天气和道路几何形状，以了解事故发生的原因。该模型作为现场服务提供给当地执法部门和应急服务机构，以更好地分配资源，减少事故发生的响应时间。建立了多个模型，每个模型都有不同的变量，每个模型都产生了不同的结果。
Given the ever present threat of vehicular accident occurrence endangering the lives of most people, preventative measures need to be taken to combat vehicle accident occurrence. From dangerous weather to hazardous roadway conditions, there are a high number of factors to consider when studying accident occurrence. To combat this issue, we propose a method using a multilayer perceptron model to predict where accident hotspots are for any given day in the city of Chattanooga, TN. This model analyzes accidents and their associated weather and roadway geometrics to understand the causes of accident occurrence. The model is offered as a live service to local law enforcement and emergency response services to better allocate resources and reduce response times for accident occurrence. Multiple models were made, each having different variables present, and each yielding varying results.