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Beyond the Road

A Regional Perspective on Traffic Congestion in Metro Atlanta

Bibliographic Data

ID22033287
AuthorsJeong Chang Seong (0000-0001-9969-8063, University of West Georgia, corresponding author), SeungYeon Lee (0000-0002-6406-0470, Kyung Hee University), Yoonjae Cho (Kyung Hee University), Yoon‐Jae Cho (0000-0003-2710-9631, Kyung Hee University), Chul Sue Hwang (0000-0001-9933-2432, Kyung Hee University)
Year2025
Volume14
Issue2
Pages61
Publication date2025-02-03
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi14020061
OpenAlexW4407100896
LanguageEN
Citations received1
References cited21

Traffic congestion not only affects traffic flow but also influences public perception of congested regions. While analyzing congestion at the road section level can help identify engineering solutions, it often fails to reveal broader spatial patterns and trends at the regional or macro scale unless summarized effectively. This study aims to address these challenges by focusing on regional-scale traffic congestion amounts measured by distanceTime metrics. A 12–month dataset, sampled every 10 min, was analyzed to identify spatial patterns, temporal trends, regional variations, and predictive models in the Metro Atlanta area. The results show that congestion is the most severe and increasing at key urban corridors like Brookhaven–Sandy Springs, the downtown connector, Druid Hills–Decatur, and Johns Creek–Cumming, aligning with recent urban developments. Cities such as Alpharetta, Dunwoody, Brookhaven, Austell, Stone Mountain, East Point, Lake City, Morrow, Fairburn, and Jonesboro show high increasing trends in congestion. Predictive modeling with the long short-term memory (LSTM) method shows promising results for short-term forecasts, though variability in data requires further optimization for certain cities. This research is significant because it demonstrates that congestion amounts measured by distanceTime metrics can be used for assessing regional characteristics broadly at a metropolitan city scale. The findings and methodologies identified in this research might support urban and transportation planning efforts in metropolitan planning organizations, such as the Atlanta Regional Commission, by identifying congestion amounts and trends at both the regional and road scales

Archaeology · Atlanta · Business · Geography · Metropolitan area · Regional science · Traffic congestion · Transport engineering · Computer Science · Engineering · Traffic control and management · Transportation Planning and Optimization · Urban Transport and Accessibility

  • Quantifying Percent Traffic Congestion (pTC) and Mobility Bottleneck Dynamics at Atlanta’s Spaghetti Junction

    Open Access•Jeong Chang Seong, Jiwon Yang et al.•ISPRS International Journal of…•2025

  • The Fundamental Law of Road Congestion

    Gilles Duranton, Matthew A Turner•American Economic Review•2011

  • Optuna

    Open Access•Takuya Akiba, Shotaro Sano et al.•Proceedings of the 25th ACM…•2019

  • Estimating O–D travel time matrix by Google Maps API

    Open Access•Fahui Wang, Yanqing Xu•Annals of GIS•2011

  • Long Short-Term Memory

    Sepp Hochreiter, Jurgen Schmidhuber•Neural Computation•1997

  • Measuring Traffic Congestion with Novel Metrics

    Open Access•Jeong Chang Seong, Yunsik Kim et al.•ISPRS International Journal of…•2023

  • Exploring the spatiotemporal pattern of traffic congestion performance of large cities in China

    Open Access•Xiaoxuan Wei, Yitian Ren et al.•Environmental Impact Assessment…•2022

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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