activity
20192021
most citedRule-based Optimal Control for Autonomous Driving

4 citations · 8 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG2021

The Reasonable Crowd: Towards evidence-based and interpretable models of driving behavior

Bassam Helou, Aditya Dusi, Anne Collin +7

Autonomous vehicles must balance a complex set of objectives. There is no consensus on how they should do so, nor on a model for specifying a desired driving behavior. We created a…

cs.RO20212 cited

Rule-based Evaluation and Optimal Control for Autonomous Driving

Wei Xiao, Noushin Mehdipour, Anne Collin +4

We develop optimal control strategies for autonomous vehicles (AVs) that are required to meet complex specifications imposed as rules of the road (ROTR) and locally specific cultur…

cs.RO2021

Plane and Sample: Maximizing Information about Autonomous Vehicle Performance using Submodular Optimization

Anne Collin, Amitai Y. Bin-Nun, Radboud Duintjer Tebbens

As autonomous vehicles (AVs) take on growing Operational Design Domains (ODDs), they need to go through a systematic, transparent, and scalable evaluation process to demonstrate th…

cs.RO2021

Safety of the Intended Driving Behavior Using Rulebooks

Anne Collin, Artur Bilka, Scott Pendleton +1

Autonomous Vehicles (AVs) are complex systems that drive in uncertain environments and potentially navigate unforeseeable situations. Safety of these systems requires not only an a…

cs.RO20214 cited

Rule-based Optimal Control for Autonomous Driving

Wei Xiao, Noushin Mehdipour, Anne Collin +4

We develop optimal control strategies for Autonomous Vehicles (AVs) that are required to meet complex specifications imposed by traffic laws and cultural expectations of reasonable…

eess.IV2020

Improved anomaly detection by training an autoencoder with skip connections on images corrupted with Stain-shaped noise

Anne-Sophie Collin, Christophe De Vleeschouwer

In industrial vision, the anomaly detection problem can be addressed with an autoencoder trained to map an arbitrary image, i.e. with or without any defect, to a clean image, i.e.…