Identification of Vehicle Dynamics Parameters Using Simulation-based Inference

no code implementations • 27 Aug 2021 • Ali Boyali, Simon Thompson, David Robert Wong

Identifying tire and vehicle parameters is an essential step in designing control and planning algorithms for autonomous vehicles.

Autonomous Vehicles

Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision

1 code implementation • 5 Jul 2021 • Robin Karlsson, David Robert Wong, Simon Thompson, Kazuya Takeda

A formal road lane network model is presented and proves that any structured road scene can be represented by a directed acyclic graph of at most depth three while retaining the notion of intersection regions, and that this is the most compressed representation.

Autonomous Vehicles Self-Supervised Learning

Probabilistic Rainfall Estimation from Automotive Lidar

1 code implementation • 23 Apr 2021 • Robin Karlsson, David Robert Wong, Kazunari Kawabata, Simon Thompson, Naoki Sakai

Prior work has established that rainfall rate is a useful measure for the adversity of atmospheric weather conditions.

LIBRE: The Multiple 3D LiDAR Dataset

no code implementations • 13 Mar 2020 • Alexander Carballo, Jacob Lambert, Abraham Monrroy-Cano, David Robert Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

In this work, we present LIBRE: LiDAR Benchmarking and Reference, a first-of-its-kind dataset featuring 10 different LiDAR sensors, covering a range of manufacturers, models, and laser configurations.

Benchmarking