Implementation of Vision- Based Trajectory Control for Autonomous Vehicles.
Date
2017-04
Authors
Journal Title
Journal ISSN
Volume Title
Type
Article
Publisher
ASAT
Series Info
17 th International Conference on AEROSPACE SCIENCES & AVIATION TECHNOLOGY;18 p
Doi
Scientific Journal Rankings
Abstract
This paper demonstrates building, implementing, and developing a trajectory
tracking control system based on computer vision for autonomous vehicles. The main goal of
this system is to enforce the autonomous vehicle to be able to track road lane. This system
includes a single digital camera, an embedded computer, and a microcontroller board. The
digital camera is mounted at the top of the vehicle along its longitudinal axis. It captures a
real-time sequence of images during vehicle motion. The captured images are then processed
using Open-CV library for Python compiler over Linux operating system. These software
packages are running on the embedded computer (Raspberry Pi 2) to obtain geometrical data
of road lane. From this data, the observable errors can be determined. These errors are vehicle
lateral offset and a heading error. Finally, a steering controller utilizes these errors in control
law to compute the steering command. This command corrects offset and heading errors to
ensure that the vehicle is in its way. The embedded computer then paths this command to
Arduino microcontroller board to adjust the steering servomotor. The proposed
implementation also demonstrates the integration between the embedded computer and
microcontroller using Ethernet. During this work, a set of autonomous driving experiments is
performed. Significant results are obtained that demonstrate the accuracy and robustness of
the lane detection and control algorithms.
Description
Keywords
University for Arduino., Raspberry Pi, Autonomous Vehicle, Lane detection, Vision-based