Image de couverture de livre

Adversarial and Reactive Traffic Entities for Behavior-Realistic Driving Simulation: A Review

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ransiek, Joshua, Reis, Philipp, Schürmann, Tobias, Sax, Eric
Format:	Preprint
Publié:	2024
Sujets:	Robotics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Behavior Forests: Real-Time Discovery of Dynamic Behavior for Data Selection
par: Reis, Philipp, et autres
Publié: (2024)

Generative AI in Systems Engineering: A Framework for Risk Assessment of Large Language Models
par: Otten, Stefan, et autres
Publié: (2026)

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording
par: Reis, Philipp, et autres
Publié: (2025)

CLIPping the Limits: Finding the Sweet Spot for Relevant Images in Automated Driving Systems Perception Testing
par: Rigoll, Philipp, et autres
Publié: (2024)

A Hierarchical Pedestrian Behavior Model to Generate Realistic Human Behavior in Traffic Simulation
par: Larter, Scott, et autres
Publié: (2022)

A Framework for a Capability-driven Evaluation of Scenario Understanding for Multimodal Large Language Models in Autonomous Driving
par: Sohn, Tin Stribor, et autres
Publié: (2025)

Safety-Critical Traffic Simulation with Adversarial Transfer of Driving Intentions
par: Huang, Zherui, et autres
Publié: (2025)

GOOSE: Goal-Conditioned Reinforcement Learning for Safety-Critical Scenario Generation
par: Ransiek, Joshua, et autres
Publié: (2024)

Structuring Automotive Data for Systems Engineering: A Taxonomy-Based Approach
par: Hohl, Carl Philipp, et autres
Publié: (2025)

DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning
par: Guo, Ke, et autres
Publié: (2025)

Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learning
par: Flögel, Daniel, et autres
Publié: (2024)

Requirement Identification for Traffic Simulations in Driving Simulators
par: Tarlowski, Sven, et autres
Publié: (2025)

Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations
par: Bitzer, Matthias, et autres
Publié: (2024)

Goal-Oriented Reactive Simulation for Closed-Loop Trajectory Prediction
par: Yadav, Harsh, et autres
Publié: (2026)

Heterogeneous Self-Play for Realistic Highway Traffic Simulation
par: Qiu, Jinkai, et autres
Publié: (2026)

RIFT: Group-Relative RL Fine-Tuning for Realistic and Controllable Traffic Simulation
par: Chen, Keyu, et autres
Publié: (2025)

Versatile Behavior Diffusion for Generalized Traffic Agent Simulation
par: Huang, Zhiyu, et autres
Publié: (2024)

RealEngine: Simulating Autonomous Driving in Realistic Context
par: Jiang, Junzhe, et autres
Publié: (2025)

Navigating Dimensionality through State Machines in Automotive System Validation
par: Adolph, Laurenz, et autres
Publié: (2024)

PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment
par: Zhang, Chuancheng, et autres
Publié: (2026)

A Comprehensive Review on Traffic Datasets and Simulators for Autonomous Vehicles
par: Sarker, Supriya, et autres
Publié: (2024)

TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters
par: Lavington, Jonathan Wilder, et autres
Publié: (2024)

When Digital Twins Meet Large Language Models: Realistic, Interactive, and Editable Simulation for Autonomous Driving
par: Samak, Tanmay Vilas, et autres
Publié: (2025)

SymDrive: Realistic and Controllable Driving Simulator via Symmetric Auto-regressive Online Restoration
par: Liu, Zhiyuan, et autres
Publié: (2025)

HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving
par: Zhou, Hongyu, et autres
Publié: (2024)

Extraction of Road Users' Behavior From Realistic Data According to Assumptions in Safety-Related Models for Automated Driving Systems
par: Certad, Novel, et autres
Publié: (2023)

Generating Transferable Adversarial Simulation Scenarios for Self-Driving via Neural Rendering
par: Abeysirigoonawardena, Yasasa, et autres
Publié: (2023)

Challenges of Data-Driven Simulation of Diverse and Consistent Human Driving Behaviors
par: Kujanpää, Kalle, et autres
Publié: (2024)

CARLA-Autoware-Bridge: Facilitating Autonomous Driving Research with a Unified Framework for Simulation and Module Development
par: Kaljavesi, Gemb, et autres
Publié: (2024)

A Comprehensive Review of Reinforcement Learning for Autonomous Driving in the CARLA Simulator
par: Delavari, Elahe, et autres
Publié: (2025)

Toward Visually Realistic Simulation: A Benchmark for Evaluating Robot Manipulation in Simulation
par: Zhu, Yixin, et autres
Publié: (2026)

Human-Like Autonomous Driving on Dense Traffic
par: Yildirim, Mustafa, et autres
Publié: (2023)

Right in Time: Reactive Reasoning in Regulated Traffic Spaces
par: Kohaut, Simon, et autres
Publié: (2026)

Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review
par: Shi, Yining, et autres
Publié: (2023)

Literature Review on Maneuver-Based Scenario Description for Automated Driving Simulations
par: Neis, Nicole, et autres
Publié: (2024)

A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving Systems
par: Haghighi, Hamed, et autres
Publié: (2023)

nuPlan-R: A Closed-Loop Planning Benchmark for Autonomous Driving via Reactive Multi-Agent Simulation
par: Peng, Mingxing, et autres
Publié: (2025)

LLM-based Realistic Safety-Critical Driving Video Generation
par: Fu, Yongjie, et autres
Publié: (2025)

LCSim: A Large-Scale Controllable Traffic Simulator
par: Zhang, Yuheng, et autres
Publié: (2024)

Aligning Microscopic Vehicle and Macroscopic Traffic Statistics: Reconstructing Driving Behavior from Partial Data
par: Zhang, Zhihao, et autres
Publié: (2026)