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Modeling the service-route-based crash frequency by a spatiotemporal-random-effect zero-inflated negative binomial model: An empirical analysis for bus-involved crashes

机译:通过时空 - 随机效应零膨胀的负二进制模型建模基于服务路线的碰撞频率:涉及总线崩溃的实证分析

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摘要

Previous studies related to bus crash frequencies modeling are limited and the statistical models are usually developed at the road segment or zonal level. This study focuses on modeling crash frequencies specifically at the bus-service-route level, which is useful and important to policymakers and bus operation companies toward the improvement of the safety level of bus networks, especially for developing countries where buses are still a major mode of urban travels. Using the observed data adopted from one of the bus operating companies in Beijing, China, we proposed a spatiotemporal-random-effect zero-inflated negative binomial (spatiotemporal ZINB) model to investigate bus crash occurrence and identity key influential factors at the bus-service-route level. The model was motivated to accommodate the special statistical characteristics of the excessive zeros and, more importantly, the potential spatiotemporal correlations of the data. Three degenerated versions of this model were also developed for comparison purposes. Results indicate that the proposed spatiotemporal ZINB model is statistically superior to the others according to a comprehensive judgment based on the EAIC, EBIC, and RMSE criteria. The estimated coefficients reveal the impacts of related factors on the likelihood of bus-involved crashes from bus operation factors including total passengers, number of drivers, and proportion of male drivers as well as planning factors including route length and stop density. On the other hand, the standard deviations of the introduced structured and unstructured spatiotemporal random-effects are statistically significant indicating that the observations are correlated within each route, between neighbor routes and across years. Corresponding policy and practical implications are provided for bus operating companies and planning departments toward the improvement of bus safety.
机译:与总线碰撞频率建模相关的先前研究是有限的,统计模型通常在路段或地区级别开发。本研究侧重于专门在公交服务 - 服务路线级别建模碰撞频率,这对政策制定者和巴士经营公司对公共汽车网络的安全水平有用而且重要,特别是对于公共汽车仍然是主要模式的发展中国家城市旅行。使用来自公交营运公司在北京,中国的一个采用的观测数据,提出了一种时空随机效应零膨胀负二项分布(时空ZINB)模型来研究车祸发生和身份的关键影响因素在公交服务-Route级别。该模型有动力适应过量零的特殊统计特征,更重要的是,数据的潜在时空相关性。还开发了这种模型的三个退行版本以进行比较目的。结果表明,根据基于EAC,EBIC和RMSE标准的综合判断,所提出的时空Zinb模型与其他统计学上优于其他。估计系数显示的相关因素从总线操作因素总线参与的崩溃,包括总的乘客,司机的数量,以及男性司机的比例以及规划因素,包括路线长度和密度停止的可能性的影响。在另一方面,所引入的结构化和非结构化的时空随机效应的标准差是统计学上显著表明观测每条路线中的相关性,邻居,和跨地区年。公共汽车运营公司和规划部门提供了相应的政策和实际影响,以提高公交安全。

著录项

  • 来源
    《Accident Analysis & Prevention》 |2020年第9期|105674.1-105674.9|共9页
  • 作者单位

    Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techn Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techn Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techn Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techn Beijing 100044 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Bus-involved crashes; Crash frequency; Spatiotemporal-random-effect; Bus service route; Zero-inflated data;

    机译:公交车涉及的崩溃;崩溃频率;时空随机效应;总线服务路线;零充气数据;

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