GreenGo, an early-stage mobility startup, aims to revolutionize urban driving with an innovative mobile app that predicts upcoming traffic light changes using AI. This project focuses on building a lightweight Minimum Viable Product (MVP) to validate the technical feasibility and user experience of the solution.

The primary goal is to enhance the driving experience by suggesting optimal, legal speeds to reduce unnecessary red light stops—ultimately improving traffic flow, fuel efficiency, and reducing emissions.

Key project objectives:

• Develop a basic AI model to predict traffic light changes based on simulated or sample data.
• Design a simple, intuitive user interface that displays light predictions and speed recommendations.
• Integrate the AI and UI into a functional MVP for user testing and iteration.

This hands-on project offers learners an opportunity to apply skills in artificial intelligence, mobile app development, UX/UI design, and systems integration in a real-world startup context.

The expected outcomes of this project include the following key deliverables:

• A functional MVP of the GreenGo mobile app, capable of demonstrating basic traffic light change predictions using a simplified AI model.
• A user-friendly interface design that visually communicates light phases and optimal driving speeds to users.
• A comprehensive development report detailing:
• The technical approach
• Key challenges encountered
• User testing insights (if applicable)
• Recommendations for future iterations
• A final presentation or demo showcasing the MVP and its potential impact on urban driving behavior, fuel savings, and traffic flow.

These deliverables will provide a strong foundation for future development and potential investor or grant presentations.