
During March 2026, this developer enhanced trajectory evaluation and planning analytics for autonomous driving by updating the tier4/driving_log_replayer_v2 and autoware_tools repositories. They introduced a ground-truth trajectory source mode for rosbag-based scenario evaluation, expanded open-loop metrics with DLR-style ADE/FDE formats, and added new metrics for heading error, comfort, and lane-keeping. Their work included robust topic propagation and vehicle model configuration improvements in the planning data analyzer. Using C++, Python, and ROS, they emphasized reliability through comprehensive unit testing, pre-commit hygiene, and targeted fixes, resulting in a more flexible, accurate, and maintainable data pipeline for robotics applications.
March 2026 focused on delivering an enhanced evaluation and planning data pipeline across tier4/driving_log_replayer_v2 and autoware_tools. Key items include end-to-end trajectory data capture, replay, and planning analytics enhancements; introduction of a ground-truth (GT) trajectory source mode for rosbag evaluation; expanded open-loop metrics with a DLR-style ADE/FDE format and new, namespace-supported metrics; and improvements to planning_data_analyzer to support GT trajectories with robust topic propagation. Quality and stability improvements were achieved through unit tests, pre-commit hygiene, and targeted fixes.
March 2026 focused on delivering an enhanced evaluation and planning data pipeline across tier4/driving_log_replayer_v2 and autoware_tools. Key items include end-to-end trajectory data capture, replay, and planning analytics enhancements; introduction of a ground-truth (GT) trajectory source mode for rosbag evaluation; expanded open-loop metrics with a DLR-style ADE/FDE format and new, namespace-supported metrics; and improvements to planning_data_analyzer to support GT trajectories with robust topic propagation. Quality and stability improvements were achieved through unit tests, pre-commit hygiene, and targeted fixes.

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