In light of the challenges and costs of real-world testing, autonomous vehicle developers
often rely on testing in simulation for the creation of reliable systems. A key element of …

Virtualized traffic via various simulation models and real‐world traffic data are promising
approaches to reconstruct detailed traffic flows. A variety of applications can benefit from the …

In this work, we propose a new approach to road modeling and 3D traffic simulation. Based
on the raw geographic information system (GIS) data laid out as sparse polylines with …

In recent years, exploring autonomous vehicles has become an emerging research topic
due to the massive opportuni-ties to deploy deep learning models in real-world …

The development and testing of automated driving systems currently pose a challenge for
the automotive industry. Since real world tests of automated driving systems are time …

Microscopic traffic simulators have become efficient tools to conduct different analytic studies
on roads, vehicles, behavior of drivers, and critical intersections, which lead towards a well …

Computer simulations of traffic and driving provide essential solutions to reduce risk and
cost in traffic-related studies and research. Through nearly 90 years of simulation …

Autonomous vehicles hold great promise in improving the future of transportation. The
driving models used in these vehicles are based on neural networks, which can be difficult …

Autonomous vehicles are expected to navigate in complex traffic scenarios with multiple
surrounding vehicles. The correlations between road users vary over time, the degree of …

Most of existing traffic simulation methods have been focused on simulating vehicles on
freeways or city-scale urban networks. However, relatively little research has been done to …