673 citations · 1.5k across the 39 of their papers we have counts for
11 papers · 1 filter
Good Data Is All Imitation Learning Needs
Amir Samadi, Konstantinos Koufos, Kurt Debattista +1
In this paper, we address the limitations of traditional teacher-student models, imitation learning, and behaviour cloning in the context of Autonomous/Automated Driving Systems (A…
Towards A General-Purpose Motion Planning for Autonomous Vehicles Using Fluid Dynamics
MReza Alipour Sormoli, Konstantinos Koufos, Mehrdad Dianati +1
General-purpose motion planners for automated/autonomous vehicles promise to handle the task of motion planning (including tactical decision-making and trajectory generation) for v…
A Survey on Hybrid Motion Planning Methods for Automated Driving Systems
MReza Alipour Sormoli, Konstantinos Koufos, Mehrdad Dianati +1
Motion planning is an essential element of the modular architecture of autonomous vehicles, serving as a bridge between upstream perception modules and downstream low-level control…
Integrity Monitoring of 3D Object Detection in Automated Driving Systems using Raw Activation Patterns and Spatial Filtering
Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos +1
The deep neural network (DNN) models are widely used for object detection in automated driving systems (ADS). Yet, such models are prone to errors which can have serious safety imp…
SAFE-RL: Saliency-Aware Counterfactual Explainer for Deep Reinforcement Learning Policies
Amir Samadi, Konstantinos Koufos, Kurt Debattista +1
While Deep Reinforcement Learning (DRL) has emerged as a promising solution for intricate control tasks, the lack of explainability of the learned policies impedes its uptake in sa…
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns
Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos +1
Monitoring the integrity of object detection for errors within the perception module of automated driving systems (ADS) is paramount for ensuring safety. Despite recent advancement…
Taming Transformers for Realistic Lidar Point Cloud Generation
Hamed Haghighi, Amir Samadi, Mehrdad Dianati +2
Diffusion Models (DMs) have achieved State-Of-The-Art (SOTA) results in the Lidar point cloud generation task, benefiting from their stable training and iterative refinement during…
Optical Flow Based Detection and Tracking of Moving Objects for Autonomous Vehicles
MReza Alipour Sormoli, Mehrdad Dianati, Sajjad Mozaffari +1
Accurate velocity estimation of surrounding moving objects and their trajectories are critical elements of perception systems in Automated/Autonomous Vehicles (AVs) with a direct i…
Run-time Introspection of 2D Object Detection in Automated Driving Systems Using Learning Representations
Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos +1
Reliable detection of various objects and road users in the surrounding environment is crucial for the safe operation of automated driving systems (ADS). Despite recent progresses…
Benchmarking the Robustness of Panoptic Segmentation for Automated Driving
Yiting Wang, Haonan Zhao, Daniel Gummadi +3
Precise situational awareness is required for the safe decision-making of assisted and automated driving (AAD) functions. Panoptic segmentation is a promising perception technique…
Data-driven Camera and Lidar Simulation Models for Autonomous Driving: A Review from Generative Models to Volume Renderers
Hamed Haghighi, Xiaomeng Wang, Hao Jing +1
Perception sensors, particularly camera and Lidar, are key elements of Autonomous Driving Systems (ADS) that enable them to comprehend their surroundings to informed driving and co…