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An Ambulance Location Problem for Covering Inherently Rare and Random Road Crashes
Computers & Industrial Engineering ( IF 6.7 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.cie.2020.106937
Seyed Sina Mohri , Hossein Haghshenas

Abstract Ambulance Location Problem (ALP) is studied in the field of covering road crashes, which are often rare and random in nature. On the account of rareness, crashes should be attributed to the network edges rather than nodes. Therefore, a covering problem with edge demand is the most compatible location problem. Accordingly, this paper proposes an edge maximal covering location problem with partial coverage of the facilities on the edges. Randomness is a feature associated with the frequency and severity of crashes. An Empirical Bayes (EB) method is applied to the observed frequency of crashes to reduce errors caused by the random feature of the crashes. The randomness associated with crash severity is investigated by adding the data derived from Property Damage Only (PDO) crashes to the network demand. As a result, an equivalent PDO measure is proposed to satisfy the demand of the network edges. The proposed method is applied to a real case study and some insights are presented.

中文翻译:

用于覆盖固有罕见和随机道路碰撞的救护车定位问题

摘要 救护车定位问题(ALP)是在覆盖道路事故的领域中进行研究的,这些事故通常是罕见的和随机的。考虑到罕见性,崩溃应该归因于网络边缘而不是节点。因此,具有边缘需求的覆盖问题是最兼容的位置问题。因此,本文提出了边缘最大覆盖位置问题,边缘设施部分覆盖。随机性是与崩溃的频率和严重程度相关的特征。将经验贝叶斯 (EB) 方法应用于观察到的崩溃频率,以减少由崩溃的随机特征引起的错误。通过将来自仅财产损失 (PDO) 崩溃的数据添加到网络需求中来研究与崩溃严重性相关的随机性。因此,提出了一种等效的 PDO 措施来满足网络边缘的需求。将所提出的方法应用于实际案例研究,并提出了一些见解。
更新日期:2021-01-01
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