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This project aims at visualizing observed and predicted trajectories with animation

Python 100.00%

trajectory-visualization's Introduction

Trajectory-Visualization

This project aims at visualizing observed and predicted trajectories with animation

Observed Trajectories and Predicted Trajectories

In shared spaces, pedestrian, cyclist, and car trajectories are observed for 6 timesteps. Each timestep lasts 0.5s and in total the observation lasts 3s. The observation is used to predict trajectories in the next 6 timesteps in 3s. To vividly illustrate the prediction process, including monitoring potential collisions and deviations and modeling interactions between different transportation modes, animation is used to compare and visualize predicted trajectories with true trajectories.

sequence41

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trajectory-visualization's People

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