NYC Beeline

NYC Beeline is a web application designed to address the inefficiency and inaccessibility of inter-borough transportation in New York City. While intra-borough travel is relatively manageable, long-distance travel between boroughs often involves longer waiting periods, congested routes, and higher costs. NYC Beeline solves this problem by calculating optimal multi-modal transportation routes across NYC.

Features

• Multi-Modal Transit Optimization: Combines buses, subway, e-bikes, taxis, and Uber to create optimal routes
• Real-Time Data: Integrates with transit APIs to pull current schedule, delay, and congestion information
• Vector-Based Algorithm: Uses linear algebra to calculate the best possible combinations based on:
  • Time efficiency
  • Cost optimization
  • Comfort factors
  • Safety considerations
  • Accessibility needs
• Interactive Map: Visualizes your route with detailed step-by-step navigation
• Personalized Recommendations: Top 3 route options calculated for your specific journey

Technology Stack

• Frontend: Next.js, React, TypeScript
• UI: Tailwind CSS
• Mapping: Leaflet
• State Management: React hooks & context
• API Integration: Axios for data fetching
• Utility Libraries: SWR for data fetching, Zustand for state management

Getting Started

Prerequisites

• Node.js 14.x or higher
• npm or yarn

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/nyc-beeline.git
   cd nyc-beeline
   

2. Install dependencies:

   npm install
   # or
   yarn install
   

3. Start the development server:

   npm run dev
   # or
   yarn dev
   

4. Open http://localhost:3000 in your browser to see the application.

How It Works

NYC Beeline uses a sophisticated vector-based scoring system to calculate optimal routes:

1. Data Collection: Real-time data is pulled from various transit providers (MTA, Citi Bike, Uber, etc.)
2. Vector Creation: For each possible route segment, we create a vector with dimensions for time, cost, comfort, safety, and accessibility
3. Ideal Vector: We compare each route vector against an "ideal" vector (faster, cheaper, more comfortable, safer, more accessible)
4. Dot Product Calculation: Routes are scored using the dot product between their normalized vector and the ideal vector
5. Optimization: The algorithm finds the optimal combination of transit modes based on this scoring system
6. Presentation: The top 3 routes are presented to the user with detailed information

Future Enhancements

• User accounts for saving favorite routes
• More detailed accessibility information
• Weather-aware recommendations
• Integration with additional transit providers
• Mobile app versions

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• NYC MTA for transit data
• OpenStreetMap and Leaflet for mapping capabilities
• All NYC transit providers for making their data available