Big Data Challenges and Opportuni4es in Railway

Transcription

1 Big Data Challenges and Opportuni4es in Railway KTN H2020 Big Data Info London Piraba Navaratnam, Maria Grazia Viglio4 RSSB 08 Dec 2015

2 Rail Safety and Standards Board RSSB is an expert body with a wide range of knowledge, skills and experience. We re part of the rail industry, non profitmaking and independent of any commercial interests. Our research programme is crossindustry and mul4disciplinary, and is driven by the needs and aspira4ons of the railway. RSSB manages and maintains industry standards for the GB railway.

3 Future Railway Programme FUTURE RAILWAY Future Railway is a collabora4on between RSSB and Network Rail, delivering the Rail Technical Strategy objec4ves through research and innova4on.

4 The Railway Whole System Infrastructure Rolling Stock Control, command and communica4on Whole System Energy Informa4on 4 Customer Experience People Partnership

5 The Rail Technical Strategy (RTS) 2012 The 30 year vision 5 RTS video

6 Big Data in Railway 6 Data collec4on Infrastructure Rolling stock Work force Passengers Environment Tracks (incl. temp., vibra4on, etc.) Bridges and tunnels Signalling Level crossings Electrifica4on and plant Loca4on Capacity Status axel, wheels, breaks, doors, Vibra4on Skills Health Schedule Demand Preferences Special needs Behaviour Infotainment Terrain Climate Vegeta4on.. Data analy4cs and informa4on valorisa4on Data Centre Predic4on Decision support Control Planning Real 4me informa4on. Actua4on Automated trains Real 4me passenger informa4on Intelligent asset maintenance Improved safety and security Improved work force management Benefits Capacity Cost Carbon Safety Customer sa4sfac4on Sustainability

7 Challenges Quality and reliability Quality/accuracy of data collected / available Integrity of data sets collected from sources/sensors in noisy / open environment Heterogeneity Different proprietary data sources genera4ng various data sets with different data formats Sta4c data, dynamic data and semista4c data Structured data and unstructured data Data integra4on and management Security Data is ofen in silos lack of common seman4cs (and ontology) to allow a meaningful fusion Lack of big data management facili4es that make data/informa4on easily accessible Proprietary systems with low levels of interoperability Lack of standards and/or common plagorms for secure, trusted data/informa4on sharing between systems and/or stakeholders High security demand for ensuring safety Protec4on of privacy and integrity 7

8 Use Case 1 Intelligent Asset Management Network Rail s Vision Autonomous Intelligent System Smart Data Collec4on: Fixed and Mobile sensors Autonomous Inspec4on and Maintenance Planner based on asset condi4on Autonomous Robo4cs for Inspec4on and Maintenance Fail and find Beker data collec4on techniques, priori4sa4on of data, faster informa4on sharing, beker quality informa4on Predic4ve instead of reac4ve maintenance, autonomous decision making, based on cost/ risk analysis, less 4me needed on track Predict and prevent Safety of our staff, less staff on track during live running. More produc4ve Inspec4on and maintenance periods. 8

9 Use Case 2 Collabora4ve Disrup4on Management 9 Dynamic traffic management rerou4ng, 4metable adjustments, etc. Rolling stock and crew re- scheduling Automated booking/4cke4ng amendments Collabora4on with other transport modes for alterna4ve arrangements Passenger flow management Precise knowledge of people needs, preferences and their loca4ons Real 4me passenger informa4on and support Cross sector, cross modal data/informa4on sharing and exploita4on

10 Use case 3 Real Time Passenger Informa4on Infrastructure manager Train operators Other transport modes (e.g. TfL) NaBonal Rail Enquires Data Engines 1. Darwin GB railway s official train running informa4on engine, providing real4me arrival and departure predic4ons, plagorm numbers, delay es4mates, schedule changes and cancella4ons. 2. Knowledgebase Sta4c and real 4me informa4on about travelling by train in GB e.g. sta4on facili4es, service disrup4on, and engineering work. 3. Online Journey Planner to plan routes, calculate fares and establish 4cket availability. Open Rail Data Maintained and provided by ATOC APIs, XML feeds Applica4on developers => End user applica4ons Beker passenger informa4on during disrup4on Cross modal, cross sector, cross border and cross lingual informa4on Personalised travel services Passenger data privacy and security 10 Passenger entertainment

11 Use case 4 Endtoend mul4 modal travel Mobility as a Service Seamless E2E transporta4on of goods and passengers Cross modal informa4on sharing and exploita4on Dynamic, real4me op4misa4on methodologies and algorithms for collabora4ve transporta4on planning and delivery across modes Precise knowledge of goods and/or passengers their needs, preferences and loca4ons PrivatePublic collabora4ons 11

12 Who we are looking for big data R&I collabora4on? Sofware developers and system integrators working (or willing to work) on transport informa4on systems Data analy4cs Universi4es, research organisa4ons, industries and SMEs Applica4on developers able to innovate in mul4 modal travel solu4ons Transport infrastructure managers, operators and service providers willing to collaborate with other transport modes Notforprofit organisa4ons promo4ng digital economy on transport Standardisa4on and/or regulatory bodies on interoperable systems across modes, sectors and borders 12 What we bring? Data sets Use cases Tes4ng facili4es Railway knowledge and exper4se Railway stakeholders Facilita4on of market takeups

13 Thank you Let s make data driven future railway a reality! [email protected]