Traffic light timing optimization is still an active line of research despite the wealth of
scientific literature on the topic, and the problem remains unsolved for any non-toy scenario …

Due to decelerating gains in single-core CPU performance, computationally expensive
simulations are increasingly executed on highly parallel hardware platforms. Agent-based …

We propose a distributed algorithm for controlling traffic signals. Our algorithm is adapted
from backpressure routing, which has been mainly applied to communication and power …

With rapid population growth, there is an urgent need for intelligent traffic control techniques
in urban transportation networks to improve network performance. In an urban transportation …

This paper proposes a real-time signal timing prediction based on deep learning algorithms
that takes various traffic flow parameters as input and predicts signal timing parameters …

The movement and transport of people and goods is spatial by its very nature. Thus,
geospatial fundamentals of transport systems need to be adequately considered in transport …

Agent-based approach is a popular tool for modelling and developing large-scale
distributed systems such as urban traffic control system with dynamic traffic flows. This study …

In order to accelerate large-scale agent-based mobility scenarios, and to provide advanced
traffic simulation and forecasting tools for planners and decision makers, a GPU-accelerated …

As computing technologies develop, there is a trend in traffic simulation research in which
the focus is moving from macro-and meso-simulation to micro-simulation since micro …

Autonomous vehicles have seen great advancements in recent years, and such vehicles are
now closer than ever to being commercially available. The advent of driverless cars provides …