Copertina

CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Huang, Peide, Ding, Wenhao, Stoler, Benjamin, Francis, Jonathan, Chen, Bingqing, Zhao, Ding
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Robotics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding
di: Stoler, Benjamin, et al.
Pubblicazione: (2025)

LongComp: Long-Tail Compositional Zero-Shot Generalization for Robust Trajectory Prediction
di: Stoler, Benjamin, et al.
Pubblicazione: (2025)

SafeShift: Safety-Informed Distribution Shifts for Robust Trajectory Prediction in Autonomous Driving
di: Stoler, Benjamin, et al.
Pubblicazione: (2023)

SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario Generation
di: Stoler, Benjamin, et al.
Pubblicazione: (2024)

ReGentS: Real-World Safety-Critical Driving Scenario Generation Made Stable
di: Yin, Yuan, et al.
Pubblicazione: (2024)

Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors
di: Hao, Kunkun, et al.
Pubblicazione: (2024)

Safety2Drive: Safety-Critical Scenario Benchmark for the Evaluation of Autonomous Driving
di: Li, Jingzheng, et al.
Pubblicazione: (2025)

Surprise Potential as a Measure of Interactivity in Driving Scenarios
di: Ding, Wenhao, et al.
Pubblicazione: (2025)

Safety-Critical Control with Uncertainty Quantification using Adaptive Conformal Prediction
di: Zhou, Hao, et al.
Pubblicazione: (2024)

Topology-Driven Trajectory Optimization for Modelling Controllable Interactions Within Multi-Vehicle Scenario
di: Ma, Changjia, et al.
Pubblicazione: (2025)

LD-Scene: LLM-Guided Diffusion for Controllable Generation of Adversarial Safety-Critical Driving Scenarios
di: Peng, Mingxing, et al.
Pubblicazione: (2025)

CrashAgent: Crash Scenario Generation via Multi-modal Reasoning
di: Li, Miao, et al.
Pubblicazione: (2025)

Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving
di: Lin, Haohong, et al.
Pubblicazione: (2023)

AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion
di: Xie, Yuting, et al.
Pubblicazione: (2024)

RealDrive: Retrieval-Augmented Driving with Diffusion Models
di: Ding, Wenhao, et al.
Pubblicazione: (2025)

Risk-Aware Vehicle Trajectory Prediction Under Safety-Critical Scenarios
di: Wang, Qingfan, et al.
Pubblicazione: (2024)

LightTact: A Visual-Tactile Fingertip Sensor for Deformation-Independent Contact Sensing
di: Lin, Changyi, et al.
Pubblicazione: (2025)

Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications
di: Zhang, Xilun, et al.
Pubblicazione: (2024)

Barrier-Enhanced Parallel Homotopic Trajectory Optimization for Safety-Critical Autonomous Driving
di: Zheng, Lei, et al.
Pubblicazione: (2024)

STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
di: Memmel, Marius, et al.
Pubblicazione: (2024)

Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving
di: Lin, Haohong, et al.
Pubblicazione: (2025)

Safety-Critical Scenario Generation Via Reinforcement Learning Based Editing
di: Liu, Haolan, et al.
Pubblicazione: (2023)

From Real-World Traffic Data to Relevant Critical Scenarios
di: Lüttner, Florian, et al.
Pubblicazione: (2025)

From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios
di: Gao, Yuan, et al.
Pubblicazione: (2025)

APEX: Learning Adaptive High-Platform Traversal for Humanoid Robots
di: Wang, Yikai, et al.
Pubblicazione: (2026)

Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models
di: Mei, Yuewen, et al.
Pubblicazione: (2025)

Generating Critical Scenarios for Testing Automated Driving Systems
di: Nguyen, Trung-Hieu, et al.
Pubblicazione: (2024)

Conditional Flow-VAE for Safety-Critical Traffic Scenario Generation
di: Gong, Zimu, et al.
Pubblicazione: (2026)

SaFeR: Safety-Critical Scenario Generation for Autonomous Driving Test via Feasibility-Constrained Token Resampling
di: Cui, Jinlong, et al.
Pubblicazione: (2026)

HAD-Gen: Human-like and Diverse Driving Behavior Modeling for Controllable Scenario Generation
di: Wang, Cheng, et al.
Pubblicazione: (2025)

UniGen: Unified Modeling of Initial Agent States and Trajectories for Generating Autonomous Driving Scenarios
di: Mahjourian, Reza, et al.
Pubblicazione: (2024)

SG-CADVLM: A Context-Aware Decoding Powered Vision Language Model for Safety-Critical Scenario Generation
di: Zhao, Hongyi, et al.
Pubblicazione: (2026)

DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch
di: Sun, Shuo, et al.
Pubblicazione: (2023)

SAH-Drive: A Scenario-Aware Hybrid Planner for Closed-Loop Vehicle Trajectory Generation
di: Fan, Yuqi, et al.
Pubblicazione: (2025)

Fusing Driver Perceived and Physical Risk for Safety Critical Scenario Screening in Autonomous Driving
di: Xiong, Chen, et al.
Pubblicazione: (2026)

Planning by Simulation: Motion Planning with Learning-based Parallel Scenario Prediction for Autonomous Driving
di: Niu, Tian, et al.
Pubblicazione: (2024)

Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization
di: Yang, Fan, et al.
Pubblicazione: (2023)

Beyond ADE and FDE: A Comprehensive Evaluation Framework for Safety-Critical Prediction in Multi-Agent Autonomous Driving Scenarios
di: Liu, Feifei, et al.
Pubblicazione: (2025)

FREA: Feasibility-Guided Generation of Safety-Critical Scenarios with Reasonable Adversariality
di: Chen, Keyu, et al.
Pubblicazione: (2024)

Operationalization of Scenario-Based Safety Assessment of Automated Driving Systems
di: Camp, Olaf Op den, et al.
Pubblicazione: (2025)