An Automated Process for Identification of Bottlenecks in the Traffic System Using Large Data Sets-Reference-Cited by-同舟云学术

An Automated Process for Identification of Bottlenecks in the Traffic System Using Large Data Sets

Published:2023-03 Issue:3 Volume:149 Page:
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Grumert Ellen F.¹^ORCID,Olstam Johan²^ORCID

Affiliation:

1. Research Director, Traffic Safety and Traffic Systems, Swedish National Road and Transport Research Institute, Linköping 581 95, Sweden (corresponding author). ORCID: .

2. Senior Research Leader and Associate Professor, Dept. of Science and Technology, Swedish National Road and Transport Research Institute, Linköping Univ., Norrköping 601 74, Sweden. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JTEPBS.TEENG-7199

Reference33 articles.

1. Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network

2. Application of time-series analysis techniques to freeway incident detection;Ahmed S. A.;Transp. Res. Rec.,1982

3. Brilon W. J. Geistefeldt and M. Regler. 2005. “Reliability of freeway traffic flow: A stochastic concept of capacity.” In Proc. 16th Int. Symp. on Transportation and Traffic Theory. Bingley UK: Emerald Publishing.

4. Bivariate relations in nearly stationary highway traffic

5. Some traffic features at freeway bottlenecks

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