Temporal TransFuser++
About
This repo contains the model weights for adapted temporal versions of the TransFuser++ model by Jaeger et. al. 2023.
These models were trained as part of a master's thesis titeled "Temporal Fusion in Imitation-Based End-to-End Autonomous Driving" at the Norwegian University of Science and Technology (NTNU). The thesis will be linked when it becomes available.
All model weights and checkpoint states can be found under "Files and versions".
Results on Bench2Drive
Experiment | Overall | Multi-ability metrics | ||||||
---|---|---|---|---|---|---|---|---|
DS | SR | Merge | Overtake | Emergency Brake | Give Way | Traffic Sign | Mean | |
static-8x1 | 81.68 | 62.27 | 57.92 | 44.44 | 76.67 | 46.67 | 78.42 | 60.82 |
static-8x2 | 83.22 | 64.24 | 59.68 | 45.19 | 81.11 | 50.00 | 79.65 | 63.13 |
lidar-4x1 | 63.58 | 36.52 | 33.07 | 20.00 | 35.00 | 46.67 | 67.54 | 40.46 |
full-4x1 | 79.78 | 56.06 | 47.08 | 41.48 | 71.67 | 50.00 | 76.84 | 57.41 |
static-4x1 | 81.25 | 60.45 | 50.63 | 46.67 | 80.00 | 50.00 | 77.19 | 60.90 |
notraj-4x1 | 81.14 | 60.45 | 54.62 | 45.19 | 77.22 | 50.00 | 74.56 | 60.32 |
noprune-4x1 | 82.80 | 63.79 | 54.20 | 49.63 | 83.79 | 50.00 | 80.00 | 63.52 |
large-4x1 | 82.22 | 63.03 | 58.33 | 40.74 | 80.00 | 50.00 | 81.75 | 62.17 |
Default TF++ | 80.87 | 62.58 | 58.33 | 42.22 | 74.44 | 46.67 | 80.88 | 60.51 |
DS = driving score
SR = success rate
Multi-ability metrics are defined by Bench2Drive [ArXiv].
Credits
- CARLA Garage repository by Jaeger et. al.
- Hidden Biases of End-to-End Driving Models by Jeager et. al. 2023
- Hidden Biases of End-to-End Driving Datasets by Zimmerlin et. al. 2024
- Bench2Drive by Jia et. al. 2024
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