Skip to content

Developed a comprehensive system integrating Dijkstra’s and A* algorithms to optimize metro navigation and constraint programming for scheduling. Proposed a model that minimizes travel time and enhances commuter satisfaction by providing the shortest paths, efficient transitions, and adaptive scheduling.

License

Notifications You must be signed in to change notification settings

kishan-25/Metro-Routing-and-Scheduling-System

Repository files navigation

Metro Routing and Scheduling System

Overview

This project aims to enhance metro transportation efficiency by integrating advanced pathfinding algorithms with a scheduling system. It optimizes commuter travel routes and minimizes waiting times at stations, leading to improved operational efficiency and reduced travel time.

Features

  • Shortest Path Finder: Uses Dijkstra's Algorithm to compute the shortest paths from a source station to all other stations.
  • Targeted Route Finder: Implements A* Algorithm for finding the shortest path between a specific source and destination.
  • Line Change Optimization: Identifies optimal interchange stations for seamless multi-line journeys.
  • Travel Time & Distance Calculation: Computes estimated travel time and distance.
  • Efficient Scheduler: Generates metro train arrival and departure schedules to avoid congestion and ensure smooth operations.

Technologies Used

  • Algorithms: Dijkstra's Algorithm, A* Algorithm
  • Programming Language: C++
  • Scheduling Techniques: Constraint Programming
  • Graph Processing: Metro network representation using nodes and edges

Bhopal Metro Map

System Architecture

System Architecture

  1. Pathfinding Module:

    • Accepts user input for source and destination.
    • Uses Dijkstra’s Algorithm for shortest path calculation.
    • Uses A* Algorithm for targeted pathfinding based on heuristic evaluation.
  2. Scheduling Module:

    • Generates a timetable considering train frequency and station interconnections.
    • Computes travel time using predefined parameters such as buffer time and speed constraints.
  3. Navigation System:

    • Provides route details, estimated travel time, and required line changes.
    • Displays station connectivity and optimal routes.

Future Enhancements

  • Real-time Train Tracking: Incorporate live updates to dynamically adjust scheduling.
  • Adaptive Scheduling: Adjust train frequency based on real-time commuter demand.
  • Integration with Other Transport Systems: Provide multi-modal transport options for seamless urban mobility.

Authors

  • Balkishan Bajpay - IIIT Manipur
  • Moirangthem Dennis Singh - IIIT Manipur

For any inquiries, contact: [email protected]

License

This project is licensed under the IEEE Conference Publications framework.

About

Developed a comprehensive system integrating Dijkstra’s and A* algorithms to optimize metro navigation and constraint programming for scheduling. Proposed a model that minimizes travel time and enhances commuter satisfaction by providing the shortest paths, efficient transitions, and adaptive scheduling.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages