The Modular Package for Autonomous Driving (mPAD) allows any user to implement autonomous driving to various scaled vehicles with the appropriate hardware components. The need for this project comes from a lack of flexible and affordable educational tools as well as a limited supply of autonomous driving software packages available for non-commercial use. The technical design objectives considered were to develop a robust, modular, and intuitive package to be used in an academic setting by engineering students with minimal prior software development, electrical engineering and hardware design knowledge. mPAD V1 included a package that enabled self-driving capabilities through lane detection, and an online dashboard was used to display sensor readings and control the speed and steering of the car. However, the platform crashed frequently and it was difficult to operate due to insufficient documentation. To address the drawbacks of mPAD V1, our team improved the performance of the backend by updating the sensor package, reducing network traffic and revamping the communication system between the car, server, and client. We also improved the dashboard by including a tutorial walkthrough, hardware component testing, a manual driving mode, power level indicators, and the ability to change various advanced settings related to the car. Finally, we developed a comprehensive setup guide for our system that also includes troubleshooting suggestions. We have advanced mPAD to be capable of ensuring that the remote controlled car is capable of performing at least 5 laps without any manipulation. It is modular as the system is composed of entirely off-the-shelf components and is intuitive as the system is easy to set up and operate with little background knowledge.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Simpson, Lindberg
• Lima, Bryan
• Yang, William
• Riviere, Thomas
• LoPresti, Anthony

Subject

• Project-Based Learning
• Infrastructure
• Learning
• Computing
• Industry
• Innovation

Publisher

• Worcester Polytechnic Institute

Identifier

• 67141
• E-project-050222-152659

Keyword

• Autonomous Driving
• Mechatronics Educations
• Self Driving

Advisor

• Radhakrishnan, Pradeep
• Pahlavan, Kaveh

Year

• 2022

UN Sustainable Development Goals

• 4 - Quality Education
• 9 - Industry, Innovation and Infrastructure

Date created

• 2022-05-02

Resource type

• Major Qualifying Project

Major

• Robotics Engineering
• Electrical & Computer Engineering
• Computer Science

Rights statement

• In Copyright

License

• Creative Commons BY-NC Attribution-NonCommercial 4.0 International