Papers › Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet...

Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline

16 Jun 2022arXiv:2206.08129archive 2025-07-28

Penghao Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li, Yu Qiao

Current end-to-end autonomous driving methods either run a controller based on a planned trajectory or perform control prediction directly, which have spanned two separately studied lines of research. Seeing their potential mutual benefits to each other, this paper takes the initiative to explore the combination of these two well-developed worlds. Specifically, our integrated approach has two branches for trajectory planning and direct control, respectively. The trajectory branch predicts the future trajectory, while the control branch involves a novel multi-step prediction scheme such that the relationship between current actions and future states can be reasoned. The two branches are connected so that the control branch receives corresponding guidance from the trajectory branch at each time step. The outputs from two branches are then fused to achieve complementary advantages. Our results are evaluated in the closed-loop urban driving setting with challenging scenarios using the CARLA simulator. Even with a monocular camera input, the proposed approach ranks first on the official CARLA Leaderboard, outperforming other complex candidates with multiple sensors or fusion mechanisms by a large margin. The source code is publicly available at https://github.com/OpenPerceptionX/TCP

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Code

OpenPerceptionX/TCP officialmentioned in papermentioned on GitHub report

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Tasks

Autonomous DrivingBench2DriveCARLA longest6Trajectory Planning

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Autonomous Driving CARLA Leaderboard TCP Driving Score 75.14 #3 of 18 Archive leaderboard report
Autonomous Driving CARLA Leaderboard TCP Infraction penalty 0.87 #3 of 18 Archive leaderboard report
Autonomous Driving CARLA Leaderboard TCP Route Completion 85.63 #3 of 18 Archive leaderboard report
Autonomous Driving CARLA Leaderboard TCP (Reproduced) Driving Score 47.91 #8 of 18 Archive leaderboard report
Autonomous Driving CARLA Leaderboard TCP (Reproduced) Infraction penalty 0.77 #8 of 18 Archive leaderboard report
Autonomous Driving CARLA Leaderboard TCP (Reproduced) Route Completion 65.73 #8 of 18 Archive leaderboard report
Bench2Drive Bench2Drive TCP-traj Driving Score 59.90 #20 of 35 Archive leaderboard report
Bench2Drive Bench2Drive TCP-traj w/o distillation Driving Score 49.30 #23 of 35 Archive leaderboard report
Bench2Drive Bench2Drive TCP Driving Score 40.70 #32 of 35 Archive leaderboard report
Bench2Drive Bench2Drive TCP-ctrl Driving Score 30.47 #34 of 35 Archive leaderboard report
CARLA longest6 CARLA Trajectory-guided Control Prediction (TCP) Driving Score 48 #13 of 21 Archive leaderboard report
CARLA longest6 CARLA Trajectory-guided Control Prediction (TCP) Infraction Score 0.65 #13 of 21 Archive leaderboard report
CARLA longest6 CARLA Trajectory-guided Control Prediction (TCP) Route Completion 72 #13 of 21 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

CARLAEntropy RegularizationPPO

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