Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles

no code implementations • 12 Jul 2021 • Erwin de Gelder, Eric Cator, Jan-Pieter Paardekooper, Olaf Op den Camp, Bart De Schutter

In this paper, we propose a method to sample from a pdf estimated using KDE, such that the samples satisfy a linear equality constraint.

Density Estimation

Real-World Scenario Mining for the Assessment of Automated Vehicles

no code implementations • 31 May 2020 • Erwin de Gelder, Jeroen Manders, Corrado Grappiolo, Jan-Pieter Paardekooper, Olaf Op den Camp, Bart De Schutter

One of the benefits of our approach is that the tags can be used to identify characteristics of a scenario that are shared among different type of scenarios.