Shift2Rail (S2R) is a European rail initiative that aims to foster innovation in the railway sector through 5 innovation programs (IP). The CONNECTIVE project works on digital transformation of transport by facilitating data exchange and interoperability between systems. The In2Stempo project aims to improve railway infrastructure cost efficiency and reliability through smart power grid mapping and station improvements. Business analytics can provide descriptive, predictive and prescriptive insights through analysis of transportation data in areas like crowd management, demand forecasting, and ticketing performance.

1. ResearchandDevelopment
Innovationisinournature
Big Data in
Shift2Rail:
CONNECTIVE and
In2Stempo projects
European Big Data Value Forum, 14th October 2019
Helsinki, Finland
Aneta Tumilowicz, Network Rail (UK)

2. ResearchandDevelopment
Innovationisinournature
What is Shift2Rail (S2R)
Shift2Rail is the first pan-European rail industry initiative that
aims to foster innovation in the railway sector by accelerating
the integration of new and advanced technologies into
innovative rail product solutions.
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S2R research priorities are split into 5 innovation
programmes (IP):
Each IP aims to deliver
specific area
technology
demonstrators and is
split into smaller
projects

3. ResearchandDevelopment
Innovationisinournature Shift2Rail catalogue of 12
Railway Innovation
Capabilities
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4. ResearchandDevelopment
Innovationisinournature
IP4 context (overview and
objectives)
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• Put the traveller back at the
centre, ease access to rail,
increasing its attractiveness
• Complete multimodal travel offer
connecting the first and last mile
to long distance journeys
• Give access to all multimodal
travel services (shopping,
ticketing, and tracking) through
its travel-companion
• Build an open framework
providing full interoperability
whilst limiting impacts on
existing systems
Across Europe Across Modes
Door - to - Door Across Services
Planning
Shopping
Ticketing
Navigating
Tracking
Aftersales

5. ResearchandDevelopment
Innovationisinournature
CONNECTIVE Project
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CONNECTIVE: Connecting and Analyzing the Digital Transport
Ecosystem
The CONNECTIVE project works towards the digital transformation of rail and
all transport services, providing the framework, tools and technologies to allow
data exchange among different actors of the transport ecosystem and
facilitating interoperability among systems, but also the creation of added
value services using all available information.
TD4.1 Interoperability Framework
TD4.4 – Trip
Tracker
TD4.5 - Travel
Companion
TD4.2 - Travel
Shopping
TD4.6 - Business
Analytics
TRANSPORTATION
DATA
TD4.3 - Booking,
Ticketing
This project has received funding from the Shift2Rail Joint
Undertaking under the European Union's Horizon 2020
grant agreement no 777522

6. ResearchandDevelopment
Innovationisinournature
IP3 context (overview and
objectives)
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• The design, construction, operation and maintenance of
rail network infrastructure has to be safe, reliable,
supportive of customer needs, cost-effective and
sustainable
• There is a need for a step change in the productivity of
infrastructure assets. These will have to be managed in a
more holistic and intelligent way, using lean operational
practices and smart technologies that can ultimately help
improve the reliability and responsiveness of customer
service, as well as the capacity and overall economics of
rail transportation.
• Rail infrastructure must ensure compatibility between
infrastructures (interoperable and standardised
infrastructure), as well as with other modes (intermodal
infrastructure, including stations and passenger and
freight hubs).
Improving crowd management
in high and low capacity
stations, improving station
design and components,
improving accessibility to trains
and improving the safety and
security of passengers and
employees at stations.

7. ResearchandDevelopment
Innovationisinournature
In2Stempo Project
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In2Stempo: Innovative Solutions in Future Stations, Energy Metering and
Power Supply
This project has received funding from the Shift2Rail Joint
Undertaking under the European Union's Horizon 2020
grant agreement no 777515
This project aims to improve cost efficiency and ensure reliable, high capacity,
infrastructure.
In2Stempo has 3 primary objectives: developing a smart railway power grid in a
interconnected and communicated system, mapping of energy flows and usage within the
entire railway system allowing for more effective energy management strategies in the
future and improving the customer experience at railway stations.

8. ResearchandDevelopment
Innovationisinournature
Business Analytics (BA)
Overview
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Descriptive Analysis
Use data aggregation and data mining to
provide insight into the past and answer:
“What has happened?”
I
Predictive Analysis
Use statistical models and forecasts
techniques to understand the future and
answer: “What could happen?”
Prescriptive Analysis
Use optimization and simulation algorithms to
advice on possible outcomes and answer:
“What should we do?”
II
III
UC1 UC2

9. ResearchandDevelopment
Innovationisinournature UC1: BA in the context of Future
stations (IP3)
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Assets management
Demand management
Passenger & Services Management
Multimodal
Business Data
Analytics
• Monitoring stations; optimize maintenance; optimize passenger flow
• Optimize revenue collection
• Fraud control
• Characterize problems/incidences and impact depending on type
of day
• Mobility patterns, demand prediction, OD Matrix
• Correlate demand and day type, events, weather, etc.
• What-If analysis, support to the deployment of strategies and offer-demand
adjustment
• Control passenger entrance at stations
• Patterns of transport usage depending on sociodemographic profiles
• Business KPI: cost and revenues
• Loyalty programs, ancillary services, preferred bookings, etc.
• Combining data from different TSP, users and IP4 services:
− Travel patterns: preferred multimodal itineraries, etc.
− Multimodal KPIs
− Multimodal hub analyses
− Resource management depending on other modes

10. ResearchandDevelopment
Innovationisinournature UC1: BA in the context of Future
stations (IP3)
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BA: UC1: Crowd management in stations
 Infrastructure design
 Offline analysis: Evaluate and
enrich evacuating existing
scenarios and train operators
 Online analysis: Forecasting
analysis
 Online analysis: What-if analysis
 Analytics:
• Machine Learning (virtual sensors
and labelled data)+Transfer learning
(real data and unlabelled or partially
labelled data)
• Data imputation algorithms
• Predictive Analytics: short and
medium terms predictions
• Prescriptive Analytics: What-if
analysis
 Visualization:
 Visualizing simulation, KPIs
Warsaw West station
 Real situation analyses
 Sensors installation inside the
station allowing simulation model
recalibration
 Video Analytics
 Creation of virtual sensor data based
on the simulated data
Objectives
Data available
Technical details
This project has received funding from the Shift2Rail Joint
Undertaking under the European Union's Horizon 2020
grant agreement no 777515

11. ResearchandDevelopment
Innovationisinournature UC1: BA in the context of Future
stations (IP3)
07/11/2019 14 This project has received funding from the Shift2Rail Joint
Undertaking under the European Union's Horizon 2020
grant agreement no 777515
From Real World … … To Simulated World/Digital Twin…
… And Back to Real World
Solve the reality gap problem
• Get simulations close to reality
• Get finer results (predictions, what-if analyses)
Populate Digital
Twin with people
Calibrate simulation with real data (VCA,
Traveller companion data, TSP data…)

12. ResearchandDevelopment
Innovationisinournature
UC2: BA in the context of Bus
company management
07/11/2019 15 This project has received funding from the Shift2Rail Joint
Undertaking under the European Union's Horizon 2020
grant agreement no 777522
Assets management
Demand management
Passenger & Services Management
Multimodal
Business Data
Analytics
• Monitoring stations; optimize maintenance; optimize passenger flow
• Optimize revenue collection
• Fraud control
• Characterize problems/incidences and impact depending on type of day
• Mobility patterns, demand prediction, OD Matrix
• Correlate demand and day type, events, weather, etc.
• What-If analysis, support to the deployment of strategies and offer-demand
adjustment
• Control passenger entrance at stations
• Patterns of transport usage depending on sociodemographic profiles
• Business KPI: cost and revenues
• Loyalty programs, ancillary services, preferred bookings, etc.
• Combining data from different TSP, users and IP4 services:
− Travel patterns: preferred multimodal itineraries, etc.
− Multimodal KPIs
− Multimodal hub analyses
− Resource management depending on other modes

13. ResearchandDevelopment
Innovationisinournature
UC2: BA in the context of Bus
company management
07/11/2019 16 This project has received funding from the Shift2Rail Joint
Undertaking under the European Union's Horizon 2020
grant agreement no 777522
Example UC: Analytics on Ticketing and service
performance Use available information from
ticketing equipment in metro
stations (vending machines, access
gates), which could be useful to:
 Enhance operators performance
and maintenance
 Allow users to know in advance
the situation of the equipment
in the stations as well as peak
times
 Total sales, sales per hour, sales per
location, average of sales.
 Validation per line, validation per
profile, validation per equipment.
 Demand prediction by line, stop, at
peak hour
 Total benefits, Payed transactions,
number of cards on the black list,
Transaction per minutes.
 Delay time for each stop, occupation
per service, occupation per service and
per stop place.
 Alarms and failures patterns
 Prediction of delays
Databases of urban operator
(Interbus, Madrid):
• Operation Assistance Services (OAS)
and Automatic Vehicle Location
(AVL)
• On board/ on station equipment:
• Sales
• Validations
• Alarms
Objectives
Data available
Analytics

14. ResearchandDevelopment
Innovationisinournature
Thank you for your
attention
07/11/2019 17
https://projects.shift2rail.org/