TopoDiffuser: A Diffusion-Based Multimodal Trajectory Prediction Model with Topometric Maps

-- This paper introduces T opoDiffuser, a diffusion-based framework for multimodal trajectory prediction that incorporates topometric maps to generate accurate, diverse, and road-compliant future motion forecasts. By embedding structural cues from topometric maps into the denoising process of a conditional diffusion model, the proposed approach enables trajectory generation that naturally adheres to road geometry without relying on explicit constraints. Extensive experiments on the KITTI benchmark demonstrate that T opoDiffuser outperforms state-of-the-art methods, while maintaining strong geometric consistency. T o support future research, we publicly release our code at https://github.com/EI-Nav/T Trajectory prediction is an important task in autonomous driving and robotic navigation.