Teaching Autonomous Driving Using a Modular and Integrated Approach

02/22/2018
by   Jie Tang, et al.
0

Autonomous driving is not one single technology but rather a complex system integrating many technologies, which means that teaching autonomous driving is a challenging task. Indeed, most existing autonomous driving classes focus on one of the technologies involved. This not only fails to provide a comprehensive coverage, but also sets a high entry barrier for students with different technology backgrounds. In this paper, we present a modular, integrated approach to teaching autonomous driving. Specifically, we organize the technologies used in autonomous driving into modules. This is described in the textbook we have developed as well as a series of multimedia online lectures designed to provide technical overview for each module. Then, once the students have understood these modules, the experimental platforms for integration we have developed allow the students to fully understand how the modules interact with each other. To verify this teaching approach, we present three case studies: an introductory class on autonomous driving for students with only a basic technology background; a new session in an existing embedded systems class to demonstrate how embedded system technologies can be applied to autonomous driving; and an industry professional training session to quickly bring up experienced engineers to work in autonomous driving. The results show that students can maintain a high interest level and make great progress by starting with familiar concepts before moving onto other modules.

READ FULL TEXT

page 3

page 7

page 8

page 9

page 10

page 12

research
09/21/2022

Teaching Autonomous Systems Hands-On: Leveraging Modular Small-Scale Hardware in the Robotics Classroom

Although robotics courses are well established in higher education, the ...
research
02/16/2021

Engineering Education in the Age of Autonomous Machines

In the past few years, we have observed a huge supply-demand gap for aut...
research
10/19/2022

Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey

Since the 2004 DARPA Grand Challenge, the autonomous driving technology ...
research
12/28/2020

Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics

We demonstrate the need and potential of systematically integrated visio...
research
06/02/2021

Coverage-based Scene Fuzzing for Virtual Autonomous Driving Testing

Simulation-based virtual testing has become an essential step to ensure ...
research
10/06/2020

The Autonomous Racing Software Stack of the KIT19d

Formula Student Driverless challenges engineering students to develop au...
research
02/03/2022

Ad-datasets: a meta-collection of data sets for autonomous driving

Autonomous driving is among the largest domains in which deep learning h...

Please sign up or login with your details

Forgot password? Click here to reset