most citedTrajectory Prediction with Observations of Variable-Length for Motion Planning in Highway Merging scenarios

1 citations · 1 across the 4 of their papers we have counts for

collaborators

9 papers

cs.RO2024

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…

cs.RO20241 cited

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…

cs.LG2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.LG2023

A Novel Deep Neural Network for Trajectory Prediction in Automated Vehicles Using Velocity Vector Field

MReza Alipour Sormoli, Amir Samadi, Sajjad Mozaffari +3

Anticipating the motion of other road users is crucial for automated driving systems (ADS), as it enables safe and informed downstream decision-making and motion planning. Unfortun…