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Bench2Drive

Bench2Drive is an autonomous driving benchmark based on the CARLA leaderboard 2.0. It consists of 220 short routes featuring safety critical scenarios. The evaluation is performed closed-loop in the CARLA simulator. The performance of an entire driving stack is being evaluated.

Papers

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Showing 26–35 of 35 papers

TitleStatusHype
From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Driving—0
Validity Learning on Failures: Mitigating the Distribution Shift in Autonomous Vehicle Planning—0
ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation—0
Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)—0
Safety2Drive: Safety-Critical Scenario Benchmark for the Evaluation of Autonomous Driving—0
Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning—0
Two Tasks, One Goal: Uniting Motion and Planning for Excellent End To End Autonomous Driving Performance—0
Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model—0
GEMINUS: Dual-aware Global and Scene-Adaptive Mixture-of-Experts for End-to-End Autonomous DrivingCode0
GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous DrivingCode0
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