Tarko Andrew P
Purdue University, Lyles School of Civil Engineering, Center for Road Safety, West Lafayette, IN 47907, USA.
Accid Anal Prev. 2023 Jan;179:106875. doi: 10.1016/j.aap.2022.106875. Epub 2022 Nov 4.
The fundamental matters of how traffic conflicts are connected to crashes and how to estimate this connection with traffic conflict data is an active subject of research and refinements. There are still open questions about traffic events that can be analytically extrapolated to related crashes, and how to efficiently estimate the probability of crash associated with such events to enable conversion of observed events to the corresponding expected number of crashes. There are two important uses of a working estimation method: (1) rapid assessment of safety at specific roads locations and evaluation of countermeasures by safety engineers, (2) modeling of safety effects by analysts based on relatively short observations at multiple locations or at limited number of locations but during extended periods. This paper focuses on the application of traffic conflicts by safety engineers where the method practicality is important. The paper first recalls the OLS method of estimating the shape parameter of the underlying Lomax distribution proposed in (Tarko, 2018). Then, the ML method is introduced and the Lomax-based crash estimates obtained with the two methods are compared. Both the methods assume the scale parameter to estimate the shape parameter. The effect of assuming the scale parameter on estimates of the expected number of crashes is evaluated. To bring the scale parameter's effect into a meaningful perspective, it is compared to two other effects: (1) type of driver, and (2) limited number of observations. Finally, re-parametrized Lomax distribution is pointed out as a potential way to address the difficulties with estimating the two distribution parameters simultaneously. The summary of the results closes the paper.
交通冲突如何与碰撞事故相关联以及如何利用交通冲突数据估算这种关联，这些基本问题是当前研究和完善的热点。对于哪些交通事件可以通过分析推断出相关碰撞事故，以及如何有效估算与此类事件相关的碰撞概率，从而将观测到的事件转化为相应的预期碰撞事故数量，仍然存在一些未解决的问题。一种有效的估算方法有两个重要用途：（1）安全工程师对特定道路位置的安全进行快速评估并评估对策；（2）分析师根据在多个位置或有限数量位置的相对短期但长时间的观测结果对安全效果进行建模。本文关注安全工程师对交通冲突的应用，其中方法的实用性很重要。本文首先回顾了（塔尔科，2018年）提出的用于估计潜在洛马克斯分布形状参数的OLS方法。然后，介绍了ML方法，并比较了用这两种方法获得的基于洛马克斯分布的碰撞事故估计值。这两种方法都假设尺度参数来估计形状参数。评估了假设尺度参数对预期碰撞事故数量估计的影响。为了从有意义的角度看待尺度参数的影响，将其与另外两种影响进行了比较：（1）驾驶员类型；（2）观测数量有限。最后，指出重新参数化的洛马克斯分布是解决同时估计两个分布参数困难的一种潜在方法。结果总结结束了本文。
