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Evaluation of BridgeDrive on Fail2Drive #7

@ShuLiu-ETHZ

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@ShuLiu-ETHZ

Dear Simon Gerstenecker,

First of all, thank you very much for creating such a challenging benchmark. I believe it will have a significant impact on the autonomous driving community.

To investigate the robustness of our BridgeDrive, we conducted a thorough evaluation on your benchmark. Here are the results:

Method Bench2Drive Fail2Drive In-Distribution Fail2Drive Generalization
DS ↑ DS ↑ SR(%) ↑ HM ↑ DS ↑ SR(%) ↑ HM ↑
TCP 59.9 24.7 39.1 30.3 24.5 (-0.8%) 31.4 (-19.7%) 27.5 (-9.1%)
UniAD 45.8 47.5 36.3 41.2 44.0 (-7.4%) 27.6 (-24.0%) 33.9 (-17.6%)
Orion 77.8 53.0 52.0 52.5 51.2 (-3.4%) 46.0 (-11.5%) 48.5 (-7.7%)
HiP-AD 86.8 74.1 70.7 72.4 67.1 (-9.4%) 56.7 (-19.8%) 61.5 (-15.1%)
SimLingo 85.1 82.6 79.3 80.9 71.7 (-13.2%) 55.0 (-30.6%) 62.2 (-23.1%)
TFv5 84.2 83.3 78.5 80.8 75.4 (-9.5%) 61.1 (-22.2%) 67.5 (-16.5%)
TFv6 95.2 90.2 93.3 91.7 79.5 (-11.9%) 70.7 (-24.2%) 74.8 (-18.4%)
BridgeDrive (Ours) 96.3 91.6 95.0 93.3 81.9 (-10.5%) 75.0 (-21.1%) 78.3 (-16.0%)

For completeness, I could also send you the evaluation JSON files via email.

I believe including these results in your paper would greatly enhance the comprehensiveness of your work, especially since none of the compared methods are diffusion-based—BridgeDrive would help fill that gap.

I hope you find this message helpful, and I look forward to a fruitful discussion. Cheers!

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