Michael Aeberhard

Simulation and Its Contribution to Evaluate Highly Automated Driving Functions

Overcoming Challenges of Validation Automated Driving and Identification of Critical Scenarios

Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data

A survey of deep learning techniques for autonomous driving

Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving

Overview of Environment Perception for Intelligent Vehicles

Analysis of Recurrent Neural Networks for Probabilistic Modeling of Driver Behavior

Autonomous Vehicle Safety: An Interdisciplinary Challenge

AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

Planning and Decision-Making for Autonomous Vehicles

Artificial intelligence, machine learning and deep learning in advanced robotics, a review

Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications

A Survey of Autonomous Driving: Common Practices and Emerging Technologies

Toward a Framework for Highly Automated Vehicle Safety Validation

Artificial intelligence applications in the development of autonomous vehicles: a survey

Survey on Scenario-Based Safety Assessment of Automated Vehicles

A Review of Motion Planning Techniques for Automated Vehicles

A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

Recent advances in artificial intelligence and machine learning for nonlinear relationship analysis and process control in drinking water treatment: A review

A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving

The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities

A Combined Model- and Learning-Based Framework for Interaction-Aware Maneuver Prediction

Object-Level Fusion for Surround Environment Perception in Automated Driving Applications

Track-to-Track Fusion With Asynchronous Sensors Using Information Matrix Fusion for Surround Environment Perception

Object-level fusion for surround environment perception in automated driving applications

A Game-Theoretic Approach to Replanning-Aware Interactive Scene Prediction and Planning

Experience, Results and Lessons Learned from Automated Driving on Germany's Highways