Evaluating and Predicting Road Network Resilience Using Traffic Speed and Log Data

被引：0
|
作者：
Yu, Xiaofei [1 ]
Tan, Erlang [1 ]
Ma, Xiaolei [1 ]
Zhang, Zhao [2 ]
机构：
[1] Beihang Univ, Beijing Key Lab Cooperat Vehicle Infrastruct Syst, Sch Transportat Sci & Engn, Beijing, Peoples R China
[2] Beihang Univ, Sch Transportat Sci & Engn, Beijing, Peoples R China
来源：
CICTP 2022: INTELLIGENT, GREEN, AND CONNECTED TRANSPORTATION | 2022年
基金：
国家重点研发计划;
关键词：
D O I：
暂无
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
Resilience plays a crucial role in management of large-scale road networks. This research studies the relationship between resilience and road changes under the influence of incidents and explores the resilient changing of road sections. The road incident is matched through the incident log data based on vehicle speeds on the road segments provided by the Amap data platform. The remaining resilience (RR) of the road is calculated according to the definition of resilience of road sections. Besides, the topological model of incident influence spread is proposed to analyze the spread influence of incidents occurring on roads. A case study with the accident data on roads near Beijing Olympic Park from October to December 2019 is analyzed to determine the relationship of resilience between different road sections. The results show a certain linear relationship in the remaining resilience between the affected road sections after an incident.
引用
收藏
页码：2112 / 2122
页数：11
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