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High Quality Express Speed Asset Data Collection for Hungarian State Railways (MÁV)Barcza, PéterBPMC Ltd. Managing Director

High Quality Express Speed Asset Data Collection for Hungarian State Railways

barcza.peter@bpmc.hu

© 2011 Autodesk

Class Summary

This class gives an insight on how MÁV, the Hungarian State Railways has collected 1 350 000 objects with high precision (5 cm ~ 2 inch) with limited budget in 14 month. Data collection is key success factor of GIS projects. From 50 - 90% of resources are often used for data collection. The railway is a multi-utility environment including civil & electrical engineering. 220 object types were measured in one measurement process.

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Learning Objectives

At the end of this class, you will be able to:

Obtain high precision complex data with limited budget Build GIS + GPS based data collection process Assure „first catch data quality” and multiple layers of control Plan first major achievements within 12 month Communicate clearly current and future GIS project scope

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The Framework

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MÁV – The Hungarian State Railways

MÁV = Hungarian State Railways Co, the national railway infrastructure operator

7800 km railway lines 400 000 widely dispersed assets 93 030 km2 surface of the country Surroundings

60% Flat land covered with fields or forest 40% Hills covered with forests or trees

Measuring environment 5200 km non electrified line 2600 km electrified line 860 railway stations

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220 different object types to be measured

Objects for users in 6 + 1 groups Track Bridges Signaling Systems Energy supply and Overhead Line Telecommunications Real Estate and Facility Management Other non MÁV objects

Parallel measurement of 7 different „utilities”

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Challenges in May 2009

Limited budget 2011-01-02 deadline Limited availability of updated maps Some unsuccessful GIS initiatives No surveying experts

MÁV had to develop his own GPS based methodology to resolve data collection issues

Analyzed data collection alternatives:

Geodetic surveying Cost and time problem

Raster design based map processing Precision and availability problem

Helicopter based data collection Cost and time problem

New GPS devices Partially working, no experience

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Country wide GNSS infrastructure

Applied survey technology: RTK GNSS GNSSnet.hu – Hungarian reference station infrastructure operated by FÖMI, the

national surveying and mapping authority Accuracy: ≤2 cm (1σ) horizontal, ≤3 cm (1σ) vertical over the whole country 54 reference stations High-end geodetic equipment Nationwide GPS+GLONASS

coverage EUPOS services High availability (>99.5%) Monitored service quality Support hotline

07:30 – 19:00 every day Source – www.fomi.hu

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GNSS service quality control – on site

Minimum help desk support due to GNSSnet.hu Monitor – quality control on mobile phone GNSSnet.hu fleet management system

MÁV internal first level help desk

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T-Mobile – Countrywide GPRS coverage 2008-07-30

GPRS communication needed for high precision location correction

Countrywide coverage of GPRS services in Hungary

Areas of reception color codes Black – with 2 w internal antenna Gray – with 2 W external antenna White – no reception

Source – www.t-mobile.hu

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Design of Data Collection Quality

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Design Quality

AnalysisMaps

ObjectsAttributesQuantities

Interdependencies

DesignSystem

Maps & layersObjectsAttributesWorkflowReportsData collectionMeasurementData uploadQuality controlQuantity control

TestIntegrated System & Data collection testQualityQuantityControl systems

TrainingMeasurement leadersMeasurement supportsApproval staffAttributes upload staffData entry help deskSystem help desk

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Interdependencies

Map Level – 7 departments with independent graphical interpretation of maps Object hierarchy level – some assets are components of individual object Object level - some objects used by all departments Attribute level – Different attributes needed for specific objects – General

attributes are needed for all objects

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Central high level planning

Measurement area categories Between stations

1 track – 2 tracks Electrified – non electrified

Stations Small – Large – Extra

Old technology – new technology ratio Testing Category based measurement expectations

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Measurement Quality – GPS technology based

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Measurement Quality

Daily planTask analysisCathegory definitionDecentralized operative planWeekly update„Rainy” day handling

Task allocationGenerate taskAllocate resourcesHoliday planning

PreparationMap analysisSupport infoDevice update

MeasurementTeam approachOn site activitiesUse of advance infoHelp desk supportRemote controlLocal control

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Decentralized operative planning

Quick access to measurement area and knowledge of the territory assured by local people

Team of local people needed Local arrangements are needed for access of high risk – railway traffic areas MÁV has 6 territories for operation management The operative planning is performed in the 6 territories Central control is assured by reporting

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Team approach

7 different departments 220 different objects Some hardly visible (on the earth objects)

Limit the need of resources Preparation of lists for measurements Basic skills always available + colleagues with special skills if needed

Most expensive error –> repeated measurement needed

Average site access time

Average measurement time

Efficiency ratio

Normal data collection 2 hours 6 hours 75 %Error correction extreme 2 hours 0,5 hours 20 %

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Location based remote control GPS technology based data collection and control 16 groups work remotely over the whole country Measurement output is strongly related to measurement time Location of the measurement is important to follow the development of measurement FÖMI reporting assures strong control of both measurement time and measured territories

User name Device active time [UTC] Coordinates

mavmt201 2010-08-03 05:56:49 - 2010-08-03 14:48:37 46.72348, 16.95176

mavmt201 2010-08-04 05:57:48 - 2010-08-04 15:05:27 46.69108, 16.82461

mavmt201 2010-08-05 04:30:49 - 2010-08-05 12:21:15 47.195, 18.14913

mavmt201 2010-08-05 12:44:02 - 2010-08-05 14:41:32 47.19678, 18.15287

mavmt201 2010-08-06 03:28:41 - 2010-08-06 05:11:33 47.11792, 17.91125

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Upload Quality–AutoDesk TopoBase & MapGuide

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Upload Challenges

Upload time is equal to measurement time in normal procedures Automating upload is a performance and quality issue The measurement and upload is broken down to small cycles – jobs, colleagues

processed 1700 jobs alltogether 150 – 200 jobs were in progress x 7 divisions included in each approval

process, one process is built from 7 steps Audibility of any processes steps are

needed any time Task management „umbrella”

supports parallel processing and control

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Upload Quality

UploadDownload from deviceUpload to system

AdjustAutomaticManual

ControlLocal expert typesIntegration controlDocumentedfeedbackControlled timeFeedback control

Live dataData publicationData maintenance

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AutoDesk TopoBase and MapGuide based Upload

Expectations for the upload process Job based Automated Minimum manual only for corrections of measurements Parallel controll of 7 departments

Upload – entirely AutoDesk SW based with AU partner add on GPS output – limitations of GIS device in data processing

contains all necessary data for processing but not in final – GIS ready - form AutoDesk TopoBase 2008 based Upload

All postprocesses automatically performed for data adjustments Only unexpected corrections have to be performed manually

AutoDesk MapGuide based Job Management Integrated job management with TopoBase 2008 jobs Deadline control and Reporting for job status

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Documented feedback and controlled time

First level control in 6 territories 7 departments reviewing independently The uploader is not available at the review The control of correction has to be simple The uploader has to wait till all reviews are performed Task management functionality was introduced with parallel processing capabilities

Central second level support and control Discussing unified approach Controlling unified approach

Processing time control – 8 days for reviews

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Usage issues

Organize access to the data Organize feedback of data quality Plan for systematic quality improvement

and individual issue handling

Expect unplanned users to come with unplanned questions

Expect new report and interface requests

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Infrastructure management value generation cycle with GIS

At the moment working at MÁV Asset Management Reporting

All steps can be improved with location based info - GIS Stage by stage approcach needed to reach full inpact Boundaries of each stage have to be clearly communicated in basic dimensions:

Business benefits, Data, Functions, Number of Users, Interfaces

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Outstanding Results

1 350 000 graphical objects measured in 14 month

16 times cost saving for data capturing and upload Individual employee cost versus

external resource cost – 4 times savings

Traditional geo-referencing versus professional GPS – 4 times savings

Quality data – based on MÁV employees knowledge

„Our data = our system” effect

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Acknowledgements

The railway aspects of MÁV GIS project was governed by

Mr. Dr. László Mosóczi, Vice President of the Hungarian State Railways (MÁV)

© 2011 Autodesk

Autodesk, AutoCAD* [*if/when mentioned in the pertinent material, followed by an alphabetical list of all other trademarks mentioned in the material] are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiaries and/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders. Autodesk reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is not responsible for typographical or graphical errors that may appear in this document. © 2011 Autodesk, Inc. All rights reserved.