19 citations · 22 across the 10 of their papers we have counts for
11 papers
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…
From Research to Practice: An Interactive Rapid Review of Autonomous Driving System Testing in Industry
Qunying Song, Ali Nouri, Håkan Sivencrona +1
Autonomous driving systems (ADS) are increasingly deployed in real traffic, yet testing remains fundamentally challenging due to open environments, complex scenarios, and the lack…
Lying to Win: Assessing LLM Deception through Human-AI Games and Parallel-World Probing
Arash Marioriyad, Ali Nouri, Mohammad Hossein Rohban +1
As Large Language Models (LLMs) transition into autonomous agentic roles, the risk of deception-defined behaviorally as the systematic provision of false information to satisfy ext…
PCICF: A Pedestrian Crossing Identification and Classification Framework
Junyi Gu, Beatriz Cabrero-Daniel, Ali Nouri +2
We have recently observed the commercial roll-out of robotaxis in various countries. They are deployed within an operational design domain (ODD) on specific routes and environmenta…
The DevSafeOps Dilemma: A Systematic Literature Review on Rapidity in Safe Autonomous Driving Development and Operation
Ali Nouri, Beatriz Cabrero-Daniel, Fredrik Törner +1
Developing autonomous driving (AD) systems is challenging due to the complexity of the systems and the need to assure their safe and reliable operation. The widely adopted approach…
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…
Comparing Optical Flow and Deep Learning to Enable Computationally Efficient Traffic Event Detection with Space-Filling Curves
Tayssir Bouraffa, Elias Kjellberg Carlson, Erik Wessman +3
Gathering data and identifying events in various traffic situations remains an essential challenge for the systematic evaluation of a perception system's performance. Analyzing lar…
Engineering Safety Requirements for Autonomous Driving with Large Language Models
Ali Nouri, Beatriz Cabrero-Daniel, Fredrik Törner +2
Changes and updates in the requirement artifacts, which can be frequent in the automotive domain, are a challenge for SafetyOps. Large Language Models (LLMs), with their impressive…
Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models
Ali Nouri, Beatriz Cabrero-Daniel, Fredrik Törner +2
DevOps is a necessity in many industries, including the development of Autonomous Vehicles. In those settings, there are iterative activities that reduce the speed of SafetyOps cyc…
On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study
Ali Nouri, Christian Berger, Fredrik Törner
Safety analysis is used to identify hazards and build knowledge during the design phase of safety-relevant functions. This is especially true for complex AI-enabled and software in…