The University of Waterloo Student Team Building a Self-Driving Car

WATonomous is a student design team at the University of Waterloo at the forefront in the design, creation, and neural training of autonomous self-driving vehicles. We are proud to be selected as one of two teams representing Canada in the SAE AutoDrive Challenge to create a fully autonomous vehicle in a four year timeframe.

The EV Bolt model with our designed competing roof rack

Research Papers

We are currently in the process of developing multiple research projects. They are all ongoing and will be ready by early fall. Check out the topics here!

 

Environment 

Modeling

Environment modeling is the backbone of how autonomous agents understand the world. 
We present a novel method for extending the priori relationship graph to include online observations, creating a unified environment model of both a priori and online data sources.

MPC Research

We present an optimal control problem
(OCP) formulation for the autonomous dynamic driving task
(DDT), and a model predictive control (MPC) solution method.

ROAD Dataset

In autonomous driving applications, understanding the world around the ego vehicle is paramount for decision-making. In this project, we explore the problem of understanding the surrounding environment of an ego vehicle in a semantically meaningful way using the ROAD dataset.

Lane Detection and Classification 

We explore Wayve's sim2real model to perform perception tasks such as performing detection and classification on the latent space.

Join us in the AutoDrive Challenge

Apply to Join
 
 

The Journey So Far

Check out everything we have accomplished in three years