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test_eval_data rename traj Jun 10, 2019 rename traj Jun 10, 2019 Update Jun 27, 2019

The Trajectory Prediction Challenge of Apolloscapes Dataset

For detail and download


This repository contains the evaluation scripts for the trajectory prediction challenge of the ApolloScapes dataset. Our trajectory dataset consists of camera-based images, LiDAR scanned point clouds, and manually annotated trajectories. It is collected under various lighting conditions and traffic densities in Beijing, China. More specifically, it contains highly complicated traffic flows mixed with vehicles, riders, and pedestrians.

Dataset download

Evaluation is the evaluation code. Run the code for a sample evaluation:

python --object_file=./test_eval_data/considered_objects.txt --gt_dir=./test_eval_data/prediction_gt.txt --res_file=./test_eval_data/prediction_result.txt
./test_eval_data/considered_objects.txt contains objects we consider when counting the error.
./test_eval_data/prediction_gt.txt is just for testing the code which is not the real ground truth. Please submit your result to the leaderboard to get true error.
./test_eval_data/prediction_result.txt is one example for submitted result.

Submission of data format

Submit your result for online evaluation here: Submit

Leaderboard: Leaderboard


TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents. PDF BibTex

Yuexin Ma, Xinge Zhu, Sibo Zhang, Ruigang Yang, Wenping Wang, and Dinesh Manocha.

AAAI(oral), 2019

  title={TrafficPredict: Trajectory prediction for heterogeneous traffic-agents},
  author={Ma, Yuexin and Zhu, Xinge and Zhang, Sibo and Yang, Ruigang and Wang, Wenping and Manocha, Dinesh},
  journal={arXiv preprint arXiv:1811.02146},


Please feel free to contact us, or raise an issue with any questions, suggestions or comments:

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