Portal
On-demand bus riding application using machine learning
Portal: On-demand Bus Riding Application
Portal is an innovative on-demand bus riding application designed to transform public transportation in Bangkok by making it more responsive to actual demand patterns.
Project Overview
The application’s core algorithm is built using Python 3 and leverages machine learning principles with a trial and error approach on our simulation model. The system optimizes bus routes and scheduling based on real-time demand, creating a more efficient public transportation experience for users while reducing operational costs for providers.
Technical Approach
- Machine Learning Core: The routing algorithm learns from historical demand patterns to predict future demand
- Simulation-Based Testing: Extensive simulation modeling to validate performance before real-world implementation
- Dynamic Routing: Real-time route adjustments based on current passenger requests
- Zonal Optimization: Special focus on improving transportation efficiency within defined urban zones
Future Development
We are actively working to extend previously established research concepts into our model to further enhance its capabilities. The ultimate goal is to create a system that can be implemented across Bangkok to significantly improve public transportation accessibility and efficiency.
Current Status
The application is currently in trial design phase. The interface shown here represents our testing prototype and not the final design, which will be refined based on user testing and feedback.
