Name: Rowan Dempster
Date: Nov 30, 2022
Time: 11:00am
Location: EIT 3155
Supervisors: Derek Rayside
Title: Environment Modeling, Action Classification, and Control for Urban Automated Driving
Abstract: This seminar discusses the design and implementation of WATonomous' Automated Driving Stack (ADS), which is capable of performing robo-taxi services in specific operational domains when deployed to WATonomous' research vehicle (Bolty). Three ADS modules are discussed in detail: (1) mapping, environment modeling, and behavioral planning, (2) action classification in video streams, and (3) trajectory planning and control. Additionally, the software architecture within which the ADS is developed and deployed, and the ADS data pipeline itself, are outlined.