Latest Articles for Traffic Management

A look into the OpenLane Topology Challenge and its innovative methods.

Study reveals key findings on mean-field games under various boundary conditions.

A comprehensive dataset for improving traffic understanding at urban intersections.

Improving traffic flow with modern control methods for urban intersections.

An overview of Mean Field Games and their impact on strategic decision-making.

A study of Chicago's taxi rides reveals neighborhood connectivity and travel trends.

Examining how cars and motorcycles interact in traffic flow.

AutoGraph uses traffic data for lane estimation, reducing reliance on manual input.

Assessing the role of communication protocols in road safety for connected vehicles.

Examining the integration of O-RAN and V2X for improved vehicle communication.

A detailed look at driver gaze estimation methods and their impact on safety.

A new model enhances decision-making under delayed information for multiple agents.

Introducing CongestEXP, an algorithm improving player decisions in shared resource scenarios.

This study focuses on traffic elements and lane connections for self-driving cars.

New algorithm improves vehicle safety and detects cyberattacks effectively.

AGC-net improves traffic predictions through context and adaptability.

Examining driver behavior and the impact of V2V technology on road safety.

A new approach improves fairness in reinforcement learning using human feedback.

New machine learning methods enhance traffic model accuracy and efficiency.

A new framework enhances safety and efficiency in urban air transport.

A new method improves how large language models are updated and used.

This article discusses the role of controlled invariants in maintaining system safety.

This study investigates vehicle interactions using a two-class traffic model.

A look at transport equations and their significance across various fields.

New methods enhance accuracy in license plate recognition systems.

A look at how bilevel optimization improves traffic management and planning.

A new algorithm for grouping similar movement paths in large datasets.

Examining how technology can reduce traffic accidents and enhance road safety.

A new method for controlling PWA systems with constraints using ADP techniques.

A new method reveals how different drivers behave on the road.

A look into the complexities of deploying large swarms of unmanned vehicles.

PeRP offers tailored guidance to improve driving efficiency and reduce urban traffic.

Autonomous vehicles enhance parking space estimation for better congestion management.

Learn how rules guide self-driving cars in traffic situations.

A machine learning method to estimate traffic signal timings using data from vehicles.

Analyzing data routing strategies to minimize packet loss in shared networks.

This study reveals how drivers handle merging situations on the road.

A look into LPVMPC and NMPC for safe driving.

Exploring how scalar conservation laws apply to traffic flow analysis.

Research reveals congestion dynamics using Seoul's traffic data.