5 papers
A Causal Probabilistic Framework for Perception-Informed Closed-Loop Simulation of Autonomous Driving
Zhennan Fei, Rickard Johansson, Mikael Andersson +12
Software-in-the-loop (SIL) simulation is a cornerstone for the validation of modern automotive safety functions. However, many current frameworks utilize ideal sensing, which bypas…
From Concept to Capability: Evaluating 3D Gaussian Splatting for Synthetic Scene Editing in Autonomous Driving
Ali Nouri, Yifei Zhang, Yifan Zhang +5
The perception of an Autonomous Driving System (ADS) critically depends on relevant, comprehensive, and diverse datasets to ensure its safety while operating in the environment. Fi…
Large Language Models in Code Co-generation for Safe Autonomous Vehicles
Ali Nouri, Beatriz Cabrero-Daniel, Zhennan Fei +3
Software engineers in various industrial domains are already using Large Language Models (LLMs) to accelerate the process of implementing parts of software systems. When considerin…
On Simulation-Guided LLM-based Code Generation for Safe Autonomous Driving Software
Ali Nouri, Johan Andersson, Kailash De Jesus Hornig +5
Automated Driving System (ADS) is a safety-critical software system responsible for the interpretation of the vehicle's environment and making decisions accordingly. The unbounded…
Correlation of Software-in-the-Loop Simulation with Physical Testing for Autonomous Driving
Zhennan Fei, Mikael Andersson, Andreas Tingberg
Software-in-the-loop (SIL) simulation is a widely used method for the rapid development and testing of autonomous vehicles because of its flexibility and efficiency. This paper pre…