System and method for generating vehicle movement plans in a large railway network

Abstract

Disclosed is method and system for continuously re-generating reactive on-line train schedules for trains running in a large railway network. Railway network partitioned based on user configuration, into first type comprising trunk line and feeder line sub-networks, and second type comprising supervisory dispatch control territories. Sense and respond cycle is continuously executed on multi-processor computing environment, senses dynamic data from field about train movements, and other changes from users. For each first type sub-network, degree of deviation is computed from incumbent plans and congestion in sub-networks. Using degree of deviation and congestion, trains are rerouted and suitable scheduling methods are chosen for each sub-network and executed in parallel and first level train schedules are sent to second level train schedulers working on second type sub-networks which in parallel identify and resolve conflicts among first level train schedules. Second level train schedules are collated to generate reactive on-line network train schedule.

Description

[0001] priority statement [0002] This application claims priority from Indian Provisional Patent Application No. 1676 / MUM / 2014 filed on May 19, 2014. Its entire contents are hereby incorporated by reference. technical field [0003] The subject matter described herein relates generally to the planning and scheduling of trains in large-scale railway networks. More particularly, the subject matter relates to continuously regenerating a reactive on-line train schedule for trains traveling in a large-scale rail network by interactively partitioning the large-scale rail network. Background technique [0004] As the demand for the transportation of goods and passengers grows over large areas, there is an increased need for efficient and larger-scale rail networks. A large-scale rail network has many train stations and connects the stations to thousands of trains running on multiple tracks. In real life, continuously monitoring and rescheduling a large number of trains in a la...

AI Technical Summary

Problems solved by technology

In the prior art, several solutions are proposed for automatic train planning and scheduling, but all solutions are limited to a limited number of trains and train stations

These conventional methods for railway planning and scheduling deal with limited-sized railway networks and do not provide any solution to plan on large-scale railway networks with an unlimited number of trains, train stations, platforms, and multiple track lines and dispatch trains

Prior art solutions cannot be extended to address effective and efficient planning and scheduling of such large-scale railway networks

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