The Autonomous Vehicle Assistance Simulation (AVAS) is an innovative project developed for the McMaster Engineering Programming Competition 2023. This simulation demonstrates state-of-the-art functionalities in autonomous vehicle technology, focusing on route optimization, pedestrian safety, and driver assistance. Considering the project was developed within a 6-hour timeframe for the competition, it showcases significant achievement albeit with room for improvement.
Summary: The McMaster Engineering Programming Competition 2023 emphasized the development of innovative systems for autonomous vehicles. Participants were tasked with creating simulations encompassing features like parking assistance, environmental detection, driver communication systems, and power optimization. The competition criteria focused on safety, practicality, and creativity, judging submissions based on solution effectiveness, documentation quality, user interface design, and overall presentation.
- Route Optimization: Utilizes the A* algorithm to optimize routes for minimal energy consumption, catering to eco-conscious and efficiency-driven aspects of autonomous vehicles.
- Real-Time Path Calculation: Provides a dynamic user interface where users can input start and end locations, enabling real-time calculation of the optimal path.
- Pedestrian Detection: Incorporates advanced algorithms for detecting pedestrians, significantly enhancing road safety for both pedestrians and drivers.
- Automated Text Response System: Features a programmed set of text reply options and a user-friendly call interface to minimize driver distraction, thus enhancing road safety.
- User Interface: Developed using JavaScript and p5.js, combined with HTML and CSS for a smooth and interactive user experience.