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Traffic prediction using time-space diagram: a convolutional neural network approach
M Khajeh Hosseini… - Transportation Research …, 2019 - journals.sagepub.com
Traffic prediction is a major component of any traffic management system. With the increase
in data sources and advancement in connectivity, data analysis and machine learning …
in data sources and advancement in connectivity, data analysis and machine learning …
[HTML][HTML] Methodology for the identification of shock wave type and speed in a traffic stream using connected vehicle data
The concept of traffic shock waves was first theorized by Lighthill and Whitham in 1955. The
identification of shock wave type and speed in a traffic stream provides critical information …
identification of shock wave type and speed in a traffic stream provides critical information …
Predictive speed harmonization using machine learning in traffic flow with connected and automated vehicles
Speed harmonization is an active traffic management strategy used to delay traffic flow
breakdown and mitigate congestion by changing speed limits throughout a road segment …
breakdown and mitigate congestion by changing speed limits throughout a road segment …
A data-driven traffic shockwave speed detection approach based on vehicle trajectories data
Traffic shockwaves demonstrate the formation and spreading of traffic fluctuation on roads.
Existing methods mainly detect the shockwaves and their propagation by estimating traffic …
Existing methods mainly detect the shockwaves and their propagation by estimating traffic …
Automatic traffic queue-end identification using location-based waze user reports
Traffic queues, especially queues caused by non-recurrent events such as incidents, are
unexpected to high-speed drivers approaching the end of queue (EOQ) and become safety …
unexpected to high-speed drivers approaching the end of queue (EOQ) and become safety …
Estimation of traffic flow rate with data from connected-automated vehicles using Bayesian inference and deep learning
Y Han, S Ahn - Frontiers in Future Transportation, 2021 - frontiersin.org
Connected automated vehicles (CAVs) hold promise to replace current traffic detection
systems in the near future. However, traffic state estimation, particularly flow rate, poses a …
systems in the near future. However, traffic state estimation, particularly flow rate, poses a …
Evaluating safety benefits of vehicle-to-everything sensor sharing on rural highways using the microscopic simulation model
Safety is a critical aspect of transportation design and operations. Practitioners utilize
various references to ensure that roadways meet safety, operational, and sustainability …
various references to ensure that roadways meet safety, operational, and sustainability …
A hybrid framework combining vehicle system knowledge with machine learning methods for improved highway trajectory prediction
Vehicle-to-vehicle communication is a solution to improve the quality of on-road traveling in
terms of throughput, safety, efficiency and comfort. However, road users that do not …
terms of throughput, safety, efficiency and comfort. However, road users that do not …
Close Look into the Spatial-Temporal Distribution of Speed, Lane Changes, and Heavy Vehicles in a Congested Freeway Weaving Section
Traffic behavior around major freeway weaving sections exhibits complex dynamics
associated with multi-directional maneuvers such as lane changes (LCs) accompanied by …
associated with multi-directional maneuvers such as lane changes (LCs) accompanied by …
[BUKU][B] Using Cooperative Automated Transportation Data for Freeway Operational Strategies
M Vasudevan, J O'Hara, M Samach, C Silverstein… - 2024 - researchgate.net
1.1 Background Cooperative automated transportation (CAT) envisions all stakeholders and
elements of the transportation system working together to improve safety, mobility, equity …
elements of the transportation system working together to improve safety, mobility, equity …