• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Promet-traffic & transportation >COMPARISON OF DIFFRENT ROAD SEGMENTATION METHODS
【24h】

COMPARISON OF DIFFRENT ROAD SEGMENTATION METHODS

机译：不同道路分割方法的比较

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In road safety, the process of organizing road infrastructure network data into homogenous entities is called segmentation. Segmenting a road network is considered the first and most important step in developing a safety performance function (SPF). This article aims to study the benefit of a newly developed network segmentation method which is based on the generation of accident groups applying K-means clustering approach. K-means algorithm has been used to identify the structure of homogeneous accident groups. According to the main assumption of the proposed clustering method, the risk of accidents is strongly influenced by the spatial interdependence and traffic attributes of the accidents. The performance of K-means clustering was compared with four other segmentation methods applying constant average annual daily traffic segments, constant length segments, related curvature characteristics and a multivariable method suggested by the Highway Safety Manual (HSM). The SPF was used to evaluate the performance of the five segmentation methods in predicting accident frequency. K-means clustering-based segmentation method has been proved to be more flexible and accurate than other models in identifying homogeneous infrastructure segments with similar safety characteristics.
机译：在道路安全方面，将道路基础设施网络数据组织成同种异体实体的过程称为分段。分割道路网络被认为是开发安全性能功能（SPF）的第一个也是最重要的一步。本文旨在研究一种新开发的网络分割方法的好处，该方法是基于应用K-Means聚类方法的事故组的产生。 K-Means算法已被用于识别均匀事故组的结构。根据拟议的聚类方法的主要假设，事故的风险受到事故的空间相互依存和交通属性的强烈影响。将K-Means聚类的性能与用于高速公路安全手册（HSM）建议的恒定年平均每日交通区段，恒定长度段，相关曲率特征和多变量方法进行比较。 SPF用于评估五个分段方法预测事故频率的性能。基于K-Means基于聚类的分割方法已经被证明比识别具有相似安全特性的均匀基础设施段的其他模型更加灵活和准确。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号