Academic Project
QCar Vehicle Controls
My academic work involved a Simulink pipeline linking camera capture and HSV colour thresholding to steering calculation and speed control for a QCar.
Project at a Glance
- Approach
- Camera capture and HSV thresholding linked to steering calculation and speed control in Simulink.
- Key Finding
- The work connects image-processing signals with vehicle commands; tracking performance remains unmeasured.
- Tools
- Simulink · HSV image processing · Vehicle-control signals
- Evidence
- Documented academic workflow and an illustrative diagram; no measured demonstration is claimed.
Objective
Connect camera information with steering and speed commands in a QCar vehicle-control workflow.
My Contribution
I worked with the Simulink workflow linking camera capture, HSV colour thresholding, steering calculation and speed control. This involved working with the hardware-interface and control blocks and examining how image information passes into vehicle commands.
Method
The pipeline connects four stages:
- Capture camera images for processing.
- Use HSV colour thresholding to identify relevant image features.
- Calculate a steering command from the processed information.
- Supply a vehicle speed command through the speed-control logic.
Outcome
The work developed my understanding of how image-processing outputs connect with vehicle steering and speed-control signals.
Limitations and Next Steps
Quantitative tracking-error, lighting-sensitivity and processing-delay tests are needed to assess performance across operating conditions. I would like to develop repeatable tests of these factors; they are proposed extensions to this work.
Academic project: Connected Autonomous Vehicles, module 7ENT2060, University of Hertfordshire.