Carla Longest6 On Carla

Metrics

Driving Score

Infraction Score

Route Completion

Results

Performance results of various models on this benchmark

				Paper Title
TransFuser++ WP (TF++WP)	73	0.56	97	Hidden Biases of End-to-End Driving Models
DriveAdapter+TCP	71	0.85	88	DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
TransFuser++ (TF++)	69	0.72	94	Hidden Biases of End-to-End Driving Models
ThinkTwice	67	0.84	77	Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
DriveAdapter	59	0.68	82	DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
Perception PlanT	58	0.65	88	PlanT: Explainable Planning Transformers via Object-Level Representations
Coaching a Teachable Student (CaT)	58	0.77	79	Coaching a Teachable Student
Learning from all Vehicle v2 (LAV v2)	58	0.68	83	Learning from All Vehicles
InteractionNet	51	0.60	87	InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers
Trajectory-guided Control Prediction (TCP)	48	0.65	72	Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
TransFuser (TF)	47	0.50	93	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Interfuser	47	0.63	74	Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
Latent TransFuser (LTF)	37	0.38	95	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Learning from all Vehicles v1 (LAV v1)	33	0.51	70	Learning from All Vehicles
Geometric Fusion (GF)	27	0.30	91	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Neural Attention Fields (NEAT)	24	0.71	62	NEAT: Neural Attention Fields for End-to-End Autonomous Driving
Late Fusion (LF)	22	0.27	83	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
World on Rails (WOR)	21	0.56	48	Learning to drive from a world on rails

0 of 18 row(s) selected.

Carla Longest6 On Carla

Metrics

Driving Score

Infraction Score

Route Completion

Results

Performance results of various models on this benchmark

				Paper Title
TransFuser++ WP (TF++WP)	73	0.56	97	Hidden Biases of End-to-End Driving Models
DriveAdapter+TCP	71	0.85	88	DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
TransFuser++ (TF++)	69	0.72	94	Hidden Biases of End-to-End Driving Models
ThinkTwice	67	0.84	77	Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
DriveAdapter	59	0.68	82	DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
Perception PlanT	58	0.65	88	PlanT: Explainable Planning Transformers via Object-Level Representations
Coaching a Teachable Student (CaT)	58	0.77	79	Coaching a Teachable Student
Learning from all Vehicle v2 (LAV v2)	58	0.68	83	Learning from All Vehicles
InteractionNet	51	0.60	87	InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers
Trajectory-guided Control Prediction (TCP)	48	0.65	72	Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
TransFuser (TF)	47	0.50	93	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Interfuser	47	0.63	74	Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
Latent TransFuser (LTF)	37	0.38	95	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Learning from all Vehicles v1 (LAV v1)	33	0.51	70	Learning from All Vehicles
Geometric Fusion (GF)	27	0.30	91	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Neural Attention Fields (NEAT)	24	0.71	62	NEAT: Neural Attention Fields for End-to-End Autonomous Driving
Late Fusion (LF)	22	0.27	83	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
World on Rails (WOR)	21	0.56	48	Learning to drive from a world on rails

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Carla Longest6 On Carla | SOTA | HyperAI