A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters

Understand

Generating multi-vehicle trajectories from existing limited data can provide rich resources for autonomous vehicle development and testing.

• This paper introduces a multi-vehicle trajectory generator (MTG) that can encode multi-vehicle interaction scenarios (called driving encounters) into an interpretable representation from which new driving encounter scenarios are generated by sampling.
• The MTG consists of a bi-directional encoder and a multi-branch decoder.
• A new disentanglement metric is then developed for model analyses and comparisons in terms of model robustness and the independence of the latent codes.