CSP Tri 3 - Pilot City Project

Project Overview

Welcome to our AP Computer Science Principles Trimester 3 repository! The main focus of this project is the Qualcomm Autonomous Vehicle Navigation Enhancement (Pilot City).

Qualcomm Autonomous Vehicle Navigation Enhancement

We're developing a machine learning application that leverages Poway's Open Data Portal transportation data to enhance autonomous vehicle navigation. Our goal is to reduce travel time by 20% for local commuters through:

• Predictive traffic flow models
• Real-time route optimization algorithms
• Adaptive speed control systems

This project showcases Qualcomm's cutting-edge technology in real-world scenarios while addressing practical transportation challenges in our community.

Repository Structure

This project is split across two repositories:

• Backend Repository: Contains API endpoints, ML models, and data processing
• Frontend Repository: Contains user interfaces, visualization components, and API integrations

Project Timeline

• Week 1 (March 12-21): Discovery, Planning, Setup, and Titanic Model Adaptation
• March 23 - April 12: Pilot City Data Integration
• March 23 - April 19: ML Model Development
• March 30 - April 19: Backend Development
• April 6 - April 26: Frontend Development
• April 27 - May 10: Integration Testing
• May 11 - May 20: User Testing
• May 21 - May 30: Refinement
• May 31 - June 4: Final Deployment
• June 5 - June 9: Final Evaluation

Key Features

1. Traffic Prediction System

   • Forecasts congestion based on historical patterns
   • Incorporates weather and event data
   • Provides both short-term and long-term predictions

2. Route Optimization Engine

   • Dynamically calculates optimal routes
   • Considers multiple parameters (time, distance, fuel efficiency)
   • Learns from past journeys to improve accuracy

3. Adaptive Speed Control

   • Recommends optimal speeds based on traffic flow
   • Predicts traffic light timing
   • Calculates safe following distances

4. User Interfaces

   • Web dashboard for administrators
   • Mobile app for commuters
   • Vehicle HUD interface

Getting Started

Backend Setup

1. Clone the backend repository:

   git clone https://github.com/your-team/csp-tri3-pilot-city-backend.git
   cd csp-tri3-pilot-city-backend

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run the backend server:

   python main.py

Frontend Setup

1. Clone the frontend repository:

   git clone https://github.com/examplelink.git
   

2. Use the Makefile to set up and run:

   make

Contributing

1. Create a new branch for your feature or fix
2. Make your changes
3. Submit a pull request with a detailed description
4. Request review from team members

Team

This project is part of our AP Computer Science Principles coursework.

License

This project is for educational purposes only.