SAS Hackathon 2025: Harnessing Digital Twin Technology to Reduce Rail Disruption

Cities around the world are under growing pressure to manage complex transport systems, especially when faced with disruptions from extreme weather, technical failures, or large-scale events. Each incident can ripple across the rail network, causing cascading delays, passenger congestion, and communication challenges for operators and policymakers alike.

Building on our success as Global Grand Champions of the SAS Hackathon 2024, we wanted to continue pushing the boundaries of what’s possible with analytics and real-time data. We wanted to explore how analytics and real-time data could transform the way these challenges are managed. For our SAS Hackathon 2025 submission, our team developed a proof of concept for a Digital Twin of a regional rail network, built on SAS Viya.

What is the challenge?

Transport disruptions don’t happen in isolation. A single line closure, storm, or event can quickly affect multiple routes, impact passenger flows, and cause widespread knock-on effects. Yet, many transport networks lack the real-time systems needed to anticipate and model these impacts as they unfold.

Our challenge was to design a solution that could:

• Simulate and forecast the impact of rail disruptions in real time
• Enable operators to reroute services dynamically
• Forecast passenger numbers during peak hours or events
• Estimate financial and passenger impacts of delays and cancellations
• Support faster, data-informed decision-making

Our solution: The Event Horizon Digital Twin for the rail network

Using SAS Viya, we built a Digital Twin that integrates live data streams with forecasting, optimisation, and intelligent decisioning models to replicate the behaviour of a rail network under stress.

This system can:

• Predict disruptions caused by weather events, such as floods or storms, using live APIs and historical data
• Model the cascading effects of delays or closures across the wider network
• Suggest alternative routes or transport modes for passengers
• Forecast passenger volumes during events or peak travel times
• Automatically trigger alerts and rerouting workflows through Agentic AI

During the hackathon, we focused on one regional network to demonstrate how a framework like this could reveal where, when, and how disruptions matter most - not just for individual stations, but across the entire connected system.

How the Digital Twin works

Our approach brought together multiple SAS Viya components:

• SAS Studio – Data preparation and processing
• SAS Visual Analytics – Real-time dashboard and visualisation
• Model Studio & Model Manager – Predictive and forecasting model development
• Event Stream Processing – Integrating live API feeds (e.g. flood warnings)
• Visual Forecasting – Predicting passenger numbers at peak times and during major events
• Optimisation – Identifying the most efficient alternative routes
• Intelligent Decisioning – Automating alert workflows and rerouting logic

For example, when a flood warning API triggers an alert, the system immediately identifies the high-risk area, recalculates the most efficient routes using optimisation models, forecasts the impact on passengers, and automatically generates alerts to operators and customers.

All this information is displayed through a single Visual Analytics dashboard that updates as new data arrives, providing a unified, command-and-control view for transport planners and decision-makers.

The expected impact

By combining real-time data with predictive modelling and automation, our Digital Twin demonstrates how cities can move from reactive crisis management to proactive, data-driven transport planning.

Potential outcomes include:

• Reduced disruption impact through faster decision-making and automated rerouting
• Improved passenger experience with timely alerts and alternative travel options
• Stronger operational resilience for transport operators and emergency services
• Data-backed infrastructure investment decisions for policymakers

Ultimately, our goal is to help cities become more resilient, connected, and sustainable, ensuring public transport continues to run smoothly, even when disruption strikes.

About the SAS Hackathon

The SAS Hackathon brings together teams from around the world to collaborate on data-driven solutions that tackle real-world problems. Using SAS Viya’s powerful analytics, machine learning, and AI capabilities, participants design and prototype solutions across industries.

We are proud to have contributed an innovative approach to improving transport resilience and look forward to exploring how this concept could evolve into real-world applications for public infrastructure and mobility planning, and look forward to SAS announcing this year's winners in December.