Reproducing real-world traffic scenes in the simulator is fundamental to training self-driving
systems. Creating a simulation scenario is a complex task, generally done manually: the ego …

Image synthesis driven by computer graphics achieved recently a remarkable realism, yet
synthetic image data generated this way reveals a significant domain gap with respect to …

High-quality traffic flow generation is the core module in building simulators for autonomous
driving. However, the majority of available simulators are incapable of replicating traffic …

In this paper, a method is presented for 3D traffic Scenes Construction and Simulation based
on scene stages. The construction method is divided into two phases: scene stages analysis …

Simulation systems have become essential to the development and validation of
autonomous driving (AD) technologies. The prevailing state-of-the-art approach for …

Simulation forms the backbone of modern self-driving development. Simulators help
develop, test, and improve driving systems without putting humans, vehicles, or their …

In this paper, we present a novel probabilistic generative model for multi-object traffic scene
understanding from movable platforms which reasons jointly about the 3D scene layout as …

One core challenge in the development of automated vehicles is their capability to deal with
a multitude of complex traffic scenarios with many, hard to predict traffic participants. As part …

We present a novel traffic animation method to promote the sense of immersion of the virtual
traffic flow by inserting virtual vehicles into the real trajectory data. Our intelligent agent …

Connected and automated vehicles (CAVs) are expected to play a vital role in the next-
generation intelligent transportation system. In recent years, researchers have proposed …