基于人工神经网络的四车道分隔国道碰撞类型影响参数研究

J. Sowjanya, Naveen Kumar Chikkakrishna, Teja Tallam
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引用次数: 1

摘要

由于印度等发展中国家的混合交通状况,十年来道路事故呈指数级增长,导致道路安全恶化。因此,道路安全已成为研究人员和工程师关注的主要问题。了解影响变量对崩溃计数的影响是非常重要的。虽然收集有关崩溃影响变量的数据是一项具有挑战性的任务,但了解其影响是非常重要的。在本研究中,考虑了一条四车道分隔的国道,并对2013-2018年的五年撞车记录进行了分析。从高速公路的平面和剖面图中提取不同的几何特征。从实地研究中收集交通特征。建立了随机模型来了解所选变量对碰撞类型的影响。利用软计算工具开发了人工神经网络,了解了影响变量对碰撞类型的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANN based Study to Investigate the Parameters Influencing Collision Type on a Four Lane Divided National Highway
Due to the mixed traffic conditions in developing countries like India, there is an exponential growth of road accidents over the decade which leads to the deterioration of road safety. Therefore, road safety has become a major concern for researchers and engineers. It is very important to know the effect of influencing variables on the crash count. Although the data to collect about the influencing variables for the crashes is a challenging task it is very important to know the effect. In this study, a four-lane divided national highway is considered and the analysis is done for the crash records for five years which is from 2013–2018. From the plan and profile drawings of the highway, different geometrical characteristics are extracted. Traffic characteristics are collected from the field studies. Stochastic models were developed to know the effect of selected variables on collision type. Using soft computing tool Artificial Neural Network is developed and the significance of the influencing variables on collision type is known.
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