Cognitive Automotive Racer
Optimization algorithms and models for autonomous cars in a racing scenario.
Overview
Most racing car scenarios are built with manual racing controls. This project is aimed at autonomous racing using advanced Machine Learning and Deep Learning algorithms.
Racing cars have always tested the limits of our understanding of path optimizations along with acceleration and declaration of the vehicle on a winding track. Once multiple racing cars are introduced the driver of the vehicle must not only optimize the path but avoid any obstacles (cars) in the path. This makes it a very complex problem to solve for an autonomous vehicle. This project aims to take up this challenge in a phased approach.
Architecture
The diagram illustrates the intercommunication between the components. For details please refer to the components.
Personas
Designing a solution requires empathy for the users. Here are some of the personas who may benefit from the product.
Racing
Team
Team is responsible for the car model and all of the mechanical, electrical and software components.
Race
Spectators
Spectators can access viewer data directly from the proximity network or from the Cloud.
Race
Administrators
Race administrators organize and monitor individual races. They support and on-premise racing infrastructure.
Components
This section shows all the major components of the project. The components are grouped under Hills or Epics for Cognitive, Internet-of-Things, etc. and Foundation.
Race
Car Model
Tamiya TT02 or similar scaled model for the car with custom fitted GPU and ARM based single board computer, cameras and sensors.
Data
Collector
On-premise network for collection of data from multiple vehicles and forwarding the information reliably to the Cloud.
Self-driving
Model
Reinforcement Learning model for accepting multiple inputs, algorithm for lane detection for inference on the car and simulation and training environments on the Cloud.
Projects
Collaboration with universities IBM Center for Advanced Studies and IBM Academy of Technology. Each Open Project is an iteration of a component of the asset.
North Carolina State University
Jeremy Edmondson,
Associate Director, Senior Design
Electrical and Computer Engineering
Project Id:
car-cog-cloud-002-ncsu
Program:
Component:
Model Analyzer
Groups:
API, Data, Model, IoT, Simulator
Students:
4
North Carolina State University
Dr. Rachana Gupta,
Director, Senior Design
Electrical and Computer Engineering
Project Id:
car-cog-onprem-002-ncsu
Program:
Component:
Car IMU
Groups:
Data Capture, Messaging
Students:
4
IBM Academy of Technology
Arunava Majumdar,
Lead, CAS Chicago, US-MW, India,
Lead, IBM Asset Strategy,
IBM Cloud Platform
Project Id:
car-phase-ii
Program:
Component:
CAR Research
Groups:
AI Model, UX, IoT
Developers:
3
Presentations
Student and professional presentations on the latest completed iterations of developments for the asset.
CAR Device
Iteration 001 presentation by the ECE students at NC State University.
“I always thought records were there to be broken.”
Michael Schumacher
Open Development 