College of Traffic Engineering, Hunan University of Technology, Zhuzhou 412007, China.
School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China.
Accid Anal Prev. 2021 May;154:106091. doi: 10.1016/j.aap.2021.106091. Epub 2021 Mar 16.
This study proposed a method for transportation agencies to efficiently and accurately formulate or revise rules for the movement of railway transport while ensuring safety under adverse conditions. Determining such a method in general requires trial-and-error experimentation, which consumes large amounts of time and money. We used the uniform experiment (UE) and generalized linear autoregression (GLAR) to establish our method. Based on it, a series of numerical models were proposed to examine the association between the operational indices of safety (derailment coefficient and rate of wheel unloading) and such factors as the type of wagon, cargo weight, partial loading (covering longitudinal and lateral offset), line condition, and operating speed. The models were used to determine the worst transportation conditions. The results of analysis showed the following: 1) the effect of the speed of operation on the safety indices followed a parabolic law, those of cargo weight and part loading followed a linear law, the type of wagon and line condition exhibited no clear regularity, and some of these factors have an interactive influence. 2) A combination of the UE and GLAR helped deal with the complex multivariate process using the fewest multilevel experiments to accurately determine the most adverse conditions for railway freight transportation. The proposed method provided reference schemes for governmental agencies to study and revise freight management regulations.
本研究提出了一种方法，供运输机构在确保不利条件下安全的前提下，有效地、准确地制定或修订铁路运输规则。一般来说，确定这样的方法需要反复试验，这会消耗大量的时间和金钱。我们使用统一试验（UE）和广义线性自回归（GLAR）来建立我们的方法。在此基础上，提出了一系列数值模型，以检验安全运行指标（脱轨系数和车轮卸载率）与货车类型、货物重量、部分装载（包括纵向和横向偏移）、线路条件和运行速度等因素之间的关系。这些模型用于确定最坏的运输条件。分析结果表明：1）运行速度对安全指标的影响呈抛物线规律，货物重量和部分装载的影响呈线性规律，货车类型和线路条件没有明显的规律，其中一些因素具有交互影响。2）UE 和 GLAR 的结合有助于利用最少的多层次实验来处理复杂的多变量过程，从而准确确定铁路货运最不利的条件。所提出的方法为政府机构研究和修订货运管理法规提供了参考方案。
