Empirical Validation of Continuum Traffic Flow Model of Capacity Drop at Sag and Tunnel Bottlenecks

Abstract This study validates the continuum traffic flow model of capacity drop at sag and tunnel bottlenecks, as proposed by Jin (Transp. Res. B Methodol. 107 , 41–56, 2018) and Wada et al. (Transp. Res. C Emerg. Technol. 113 , 260–276, 2020), through empirical analysis. Specifically, after addressing the limitations in the existing studies, we calibrate the model using data from multiple congestion events at several expressway bottlenecks. We then demonstrate that the model can reproduce the observed speed recovery near the head of the queue, and assess whether both estimated bottleneck capacities and locations are consistent with observed traffic conditions. Finally, as an application of the calibration results, we examine the relationship between the spatial changes in the estimated traffic capacity and longitudinal gradients.

Authors

Institutions

Publication Details

Journal
International Journal of Intelligent Transportation Systems Research
Published
2026-01-26
DOI
https://doi.org/10.1007/s13177-026-00626-9
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empirical Validation of Continuum Traffic Flow Model of Capacity Drop at Sag and Tunnel Bottlenecks

Kai Su, Kentaro Wada, Ryota Horiguchi, Jian Xing
International Journal of Intelligent Transportation Systems Research
Traffic control and management
article

Empirical Validation of Continuum Traffic Flow Model of Capacity Drop at Sag and Tunnel Bottlenecks

Kai Su, Kentaro Wada, Ryota Horiguchi, Jian Xing
article en

Abstract

Abstract This study validates the continuum traffic flow model of capacity drop at sag and tunnel bottlenecks, as proposed by Jin (Transp. Res. B Methodol. 107 , 41–56, 2018) and Wada et al. (Transp. Res. C Emerg. Technol. 113 , 260–276, 2020), through empirical analysis. Specifically, after addressing the limitations in the existing studies, we calibrate the model using data from multiple congestion events at several expressway bottlenecks. We then demonstrate that the model can reproduce the observed speed recovery near the head of the queue, and assess whether both estimated bottleneck capacities and locations are consistent with observed traffic conditions. Finally, as an application of the calibration results, we examine the relationship between the spatial changes in the estimated traffic capacity and longitudinal gradients.

International Journal of Intelligent Transportation Systems Research
University of Tsukuba (JP), Nippon Institute for Biological Science (JP), Japan Transport Research Institute (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 100%
Traffic control and management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.