Cover Image

Towards Selection and Transition Between Behavior-Based Neural Networks for Automated Driving

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aslam, Iqra, Anpilogov, Igor, Rausch, Andreas
Format:	Preprint
Published:	2024
Subjects:	Robotics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Method for the Runtime Validation of AI-based Environment Perception in Automated Driving System
by: Aslam, Iqra, et al.
Published: (2024)

Towards Human-Like Trajectory Prediction for Autonomous Driving: A Behavior-Centric Approach
by: Liao, Haicheng, et al.
Published: (2025)

Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling
by: Tan, Tianyi, et al.
Published: (2025)

Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework
by: Fang, Shiyu, et al.
Published: (2024)

A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Data
by: Bano, Iqra, et al.
Published: (2024)

Reinforced Imitative Trajectory Planning for Urban Automated Driving
by: Zeng, Di, et al.
Published: (2024)

Connected Dependability Cage: Run-Time Function and Anomaly Monitoring for the Development and Operation of Safe Automated Vehicles
by: Aslam, Iqra, et al.
Published: (2026)

Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction
by: Briechle, Dominique, et al.
Published: (2026)

Correcting Autonomous Driving Object Detection Misclassifications with Automated Commonsense Reasoning
by: Kimbrell, Keegan, et al.
Published: (2026)

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making
by: Abdelhamid, M. Youssef, et al.
Published: (2025)

Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning
by: Weiwei, Liu, et al.
Published: (2024)

MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving
by: Liao, Haicheng, et al.
Published: (2024)

NDST: Neural Driving Style Transfer for Human-Like Vision-Based Autonomous Driving
by: Kim, Donghyun, et al.
Published: (2024)

Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Driving
by: Jin, Guizhe, et al.
Published: (2025)

A Multimodal Neural Network for Recognizing Subjective Self-Disclosure Towards Social Robots
by: Powell, Henry, et al.
Published: (2025)

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

Automatic Curriculum Learning for Driving Scenarios: Towards Robust and Efficient Reinforcement Learning
by: Abouelazm, Ahmed, et al.
Published: (2025)

Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios
by: Li, Jingzheng, et al.
Published: (2025)

LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model
by: Li, Xiangyu, et al.
Published: (2026)

DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning
by: Yao, Wenhao, et al.
Published: (2025)

Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction
by: Li, Haoming
Published: (2024)

A Rule-Based Behaviour Planner for Autonomous Driving
by: Frederic, Bouchard, et al.
Published: (2024)

Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees
by: Ma, Xinhang, et al.
Published: (2025)

FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data through Learning Rate Enhancements for Autonomous Embedded Systems
by: Bano, Iqra, et al.
Published: (2024)

Pioneering SE(2)-Equivariant Trajectory Planning for Automated Driving
by: Hagedorn, Steffen, et al.
Published: (2024)

A Cognitive-Based Trajectory Prediction Approach for Autonomous Driving
by: Liao, Haicheng, et al.
Published: (2024)

SocRATES: Towards Automated Scenario-based Testing of Social Navigation Algorithms
by: Marpally, Shashank Rao, et al.
Published: (2024)

AuthSim: Towards Authentic and Effective Safety-critical Scenario Generation for Autonomous Driving Tests
by: Yang, Yukuan, et al.
Published: (2025)

Edge Case Detection in Automated Driving: Methods, Challenges and Future Directions
by: Rahmani, Saeed, et al.
Published: (2024)

Automated Parking Planning with Vision-Based BEV Approach
by: Zhao, Yuxuan
Published: (2024)

DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous Driving
by: Xu, Yinda, et al.
Published: (2023)

SenseRAG: Constructing Environmental Knowledge Bases with Proactive Querying for LLM-Based Autonomous Driving
by: Luo, Xuewen, et al.
Published: (2025)

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

Enhancing Safety Standards in Automated Systems Using Dynamic Bayesian Networks
by: Talluri, Kranthi Kumar, et al.
Published: (2025)

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

Driving-RAG: Driving Scenarios Embedding, Search, and RAG Applications
by: Chang, Cheng, et al.
Published: (2025)

RoCo Challenge at AAAI 2026: Benchmarking Robotic Collaborative Manipulation for Assembly Towards Industrial Automation
by: Liu, Haichao, et al.
Published: (2026)

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
by: Jiang, Hao, et al.
Published: (2025)

BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
by: Zhou, Zikang, et al.
Published: (2024)

Fully Spiking Neural Network for Legged Robots
by: Jiang, Xiaoyang, et al.
Published: (2023)