Modeling and simulations on automated vehicles to alleviate traffic congestion

Aligning social welfare and agent preferences to alleviate traffic congestion

Multiagent coordination algorithms provide unique insights into the challenging problem of alleviating traffic congestion. What is particularly interesting in this class of problem is that no individual action (e.g., leave at a given time) is intrinsically “bad” but that combinations of actions among agents lead to undesirable outcomes. As a consequence, agents need to learn how to coordinate t...

What do autonomous vehicles mean to traffic congestion and crash? Network traffic flow modeling and simulation for autonomous vehicles

Traffic Congestion Detection System through Connected Vehicles and Big Data

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ ...

Real-Time Traffic Management to Maximize Throughput of Automated Vehicles

Given an arbitrary number of automated vehicles, the researchers designed an algorithm to maximize the number of possible lane changes on an arbitrary segment of a highway at any given time. The proposed algorithm utilizes information such as vehicles’ positions, speeds, and time slacks to make judicious lane change decisions without requiring prior knowledge of traffic patterns or unnecessary ...

Modeling Truck Traffic Volume Growth Congestion