Control of connected and automated vehicles: State of the art and future challenges
Autonomous driving technology pledges safety, convenience, and energy efficiency. Its
challenges include the unknown intentions of other road users: communication between …
challenges include the unknown intentions of other road users: communication between …
A review of reinforcement learning applications in adaptive traffic signal control
In urban areas, the problem of recurring daily congestion is constantly increasing. A possible
solution is seen in the application of adaptive traffic signal control (ATSC) systems for the …
solution is seen in the application of adaptive traffic signal control (ATSC) systems for the …
Platoons of connected vehicles can double throughput in urban roads
Intersections are the bottlenecks of the urban road system because an intersection's
capacity is only a fraction of the maximum flows that the roads connecting to the intersection …
capacity is only a fraction of the maximum flows that the roads connecting to the intersection …
Max-pressure traffic controller based on travel times: An experimental analysis
The traffic control of an arbitrary network of signalized intersections is considered. This work
presents a new version of the recently proposed max-pressure controller, also known as …
presents a new version of the recently proposed max-pressure controller, also known as …
Deriving operational traffic signal performance measures from vehicle trajectory data
Operations-oriented traffic signal performance measures are important for identifying the
need for retiming to improve traffic signal operations. Currently, most traffic signal …
need for retiming to improve traffic signal operations. Currently, most traffic signal …
Prediction of vehicle occupants injury at signalized intersections using real-time traffic and signal data
Intersections are among the most dangerous roadway facilities due to the existence of
complex movements of traffic. Most of the previous intersection safety studies are conducted …
complex movements of traffic. Most of the previous intersection safety studies are conducted …
Real-time pedestrian conflict prediction model at the signal cycle level using machine learning models
Compared with traditional traffic studies, real-time safety analyses can be better
incorporated into proactive traffic management strategies to improve traffic safety. However …
incorporated into proactive traffic management strategies to improve traffic safety. However …
A proactive approach to evaluating intersection safety using hard-braking data
Typical safety improvements at signalized intersections are identified and prioritized using
crash data over 3–5 years. Enhanced probe data that provides date, time, heading, and …
crash data over 3–5 years. Enhanced probe data that provides date, time, heading, and …
[HTML][HTML] Recent advances in traffic signal performance evaluation
D Leitner, P Meleby, L Miao - Journal of traffic and transportation …, 2022 - Elsevier
Signal retiming is a prominent way that transportation agencies use to fight congestion and
change of traffic pattern. Performance evaluations of traffic conditions at signalized …
change of traffic pattern. Performance evaluations of traffic conditions at signalized …
The Crossroads of LLM and Traffic Control: A Study on Large Language Models in Adaptive Traffic Signal Control
Recent advancements in Large Language Models (LLMs) have ushered in opportunities to
craft agents that exhibit human-like cognitive abilities, notably reasoning and planning …
craft agents that exhibit human-like cognitive abilities, notably reasoning and planning …