Analysis of the Impact of the Francis Scott Key Bridge Collapse on Traffic Flows and the Traffic Network in Baltimore City

2025-99-0034

10/17/2025

Authors Abstract
Content
This study focuses on analyzing the impact of the Francis Scott Key Bridge collapse on traffic flow and the traffic network in Baltimore City. By employing the processing of publicly available datasets, the construction of a traffic network model and a comprehensive scoring method and an improved K-means clustering algorithm based on the idea of the rotational method, the following conclusions have been drawn in this study. First, the bridge collapse significantly changed the distribution of traffic flow. According to the AADT data of 17 key traffic nodes, after the bridge collapse, the AADT of all nodes generally increased except for the nodes closest to the tunnel and bridge. For example, traffic nodes around the city center (e.g., nodes with OSMID numbers 37831627 and 602433660) experienced an increase in AADT, suggesting that traffic flows we Second, the 17 key nodes selected represent the major nodes of the Baltimore City traffic system and provide accurate data to support subsequent traffic optimization. Finally, the redistribution of traffic flows after the bridge collapses exacerbated the traffic bottlenecks on the inner and outer ring highways and tunnels and other roads, especially around the collapsed nodes, where the traffic burden increased significantly, reflecting the tendency of shifting traffic flows to the peripheral areas. The results of the study provide a theoretical basis and data support for the optimization of the traffic system in Baltimore City and emergency response to similar events in the future.
Meta TagsDetails
Pages
7
Citation
Hao, Z., Hu, J., Ran, J., Zheng, Y. et al., "Analysis of the Impact of the Francis Scott Key Bridge Collapse on Traffic Flows and the Traffic Network in Baltimore City," SAE Technical Paper 2025-99-0034, 2025, .
Additional Details
Publisher
Published
Oct 17
Product Code
2025-99-0034
Content Type
Technical Paper
Language
English