Crash Prediction Model for Freeway Segment Considering Time Correlation
编号:1950 访问权限:仅限参会人 更新:2021-12-03 14:43:21 浏览:112次 张贴报告

报告开始:2021年12月17日 08:56(Asia/Shanghai)

报告时间:1min

所在会场:[P2] Poster2021 [P2T4] Track 4 Transportation Behavior, Safety and Security

暂无文件

摘要
Freeways play an important role in transportation system. But crashes occur frequently on freeways. Crash prediction models for freeway can evaluate road safety status and analyze safety influencing factors. Based on 9987 crashes occurred on Ningbo-Taizhou-Wenzhou Freeway from 2016 to 2019, this paper develops a Random Effect Negative Binomial (RENB) model, which introduces a random effect term into a Negative Binomial (NB) model to explain time correlation of the crash data among different years. In this paper, the NB model and the RENB model are compared in terms of goodness of fit and prediction accuracy. Results show that factors influencing crashes are annual average daily traffic volume, length of research unit, number of lanes and road alignment; the goodness of fit of the NB model and the RENB model is consistent, while the NB model has better prediction accuracy.
关键词
CICTP
报告人
Jia Li
Beijing University of Technology

稿件作者
Jia Li Beijing University of Technology
发表评论
验证码 看不清楚,更换一张
全部评论
重要日期
  • 会议日期

    12月17日

    2021

    12月20日

    2021

  • 12月16日 2021

    报告提交截止日期

  • 12月24日 2021

    注册截止日期

主办单位
Chinese Overseas Transportation Association
Chang'an University
联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询