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
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
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 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
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