< Back to Article

Local causal dynamic integrated global mode guidance transformer network for pedestrian trajectory prediction

Fig 2

Overview of the proposed LGCMT framework.

The target trajectory X_i and neighbor trajectories are embedded and processed by a local–global collaborative encoder, consisting of a Causal Temporal Encoder (CTE) with SCT-MSA for local dynamics and a Global Context Encoder (GCE) for global motion trends. A motion-pattern library is scored by the CLS head to select top-K modes, and a socially-aware non-autoregressive decoder (REG head) generates K future trajectory hypotheses in parallel.

doi: https://doi.org/10.1371/journal.pone.0347049.g002