August 1, 2025Open Access

A Literature Review on Extreme Traffic Congestion: Defining, Modeling, and Managing Extreme Conditions in the Autonomous Vehicle Era

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KQKun QianKunming University of Science and Technology

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Implication

Literature review defines and models extreme congestion in urban areas, highlighting the role of autonomous vehicles and advanced traffic management systems.

Key Points

Extreme congestion represents a critical breakdown in network efficiency, requiring innovative solutions.
The report explores various traffic modeling approaches, including microscopic, macroscopic, and mesoscopic models.
Machine Learning and Deep Learning are emphasized for real-time traffic operations and autonomous vehicle integration.
Holistic management strategies, including smart city infrastructure and policy interventions, are crucial for sustainable transportation.

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Kun Qian (2025) studied this question.

synapsesocial.com/papers/689a0c65e6551bb0af8cfba0 https://doi.org/10.20944/preprints202507.2579.v1

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Implication

Literature review defines and models extreme congestion in urban areas, highlighting the role of autonomous vehicles and advanced traffic management systems.

A Literature Review on Extreme Traffic Congestion: Defining, Modeling, and Managing Extreme Conditions in the Autonomous Vehicle Era

Discussion

Member takes

Implication

Key Points

Cite This Study

A Literature Review on Extreme Traffic Congestion: Defining, Modeling, and Managing Extreme Conditions in the Autonomous Vehicle Era

Discussion

Member takes

Implication

Key Points

Cite This Study

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