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Development and use of national transport model in Slovenia Gregor Pretnar CETRA

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Development of national transport models in Slovenia (by PNZ).

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Page 1: Modelling PNZ

Development and use of national transport model in Slovenia

Gregor Pretnar

CETRA

Page 2: Modelling PNZ

Presentation

• background• historical development and current status• features• use of model CETRA

Page 3: Modelling PNZ

About• established in 1953, located in Ljubljana• cca. 50 employees, four departments• 4‐5 mio € yearly turnover• owned by employees (present and past)• leading transport planner and designer in Slovenia

50‘ 60‘ 70‘ 80‘ 90‘ 00‘ 10‘

beginning

design of first highway in Yugoslavia

first transport studies

National Highway Development Plan

traffic studies abroad

transport model of wider Ljubljana region

national model of Slovenia

feasibility study for new railway

Page 4: Modelling PNZ

Planning referencesTranseuropean model TRANS-TOOLS (2011)

National model of Slovenia PRIMOS (2011)

CETRA model (2013)

Danube bridge and tunnel, Novi Sad (2009)

Sava bridge, Belgrade (2007)

Enlargment of ring road, Ljubljana (2009)

Masterplan, Belgrade (2008)

Page 5: Modelling PNZ

Role and function of models

Page 6: Modelling PNZ

Properties and use of national model• includes complete population and area of country,• enables interactive modelling of land use and transport,• determines individuals’ behaviour and decisions how, where, when, with which 

mode to travel and to transport• is a tool for forecasts and analyses of effects of different policies and measures,• enables modelling effects of tolling, congestion charge, pollution charge (with 

purpose of cost internalization), parking policies• integrated modelling of external costs (noise, air, accidents)• presents frame for demand modelling on detailed regional and local levels,• represents large database• enables broad array of detailed analyses

• no use of growth factors for transport

Page 7: Modelling PNZ

History and development• 2004‐2011 National transport model of Slovenia ‐ PRIMOS

– contracted by National Road Agency– 4‐step transport multimodal transport model (3‐step road freight model)– submodels for external costs (noise, accidents, gas emissions)– audit

• 2005‐2007 Multimodal transport model of wider Ljubljana region– household survey (2003)– 4‐step transport model (including 3‐step road freight model)

• 2012‐> Central European TRAnsport model CETRA– developed within and for project „Feasibility study for new railway connection 

Divača‐Ljubljana‐Zidani Most“– major overhaul and upgrade of existing PRIMOS model

• inclusion of 23 countries• development of 5‐step freight model (rail, road, ferry mode)• development of impedance function for frequency of public transport

Page 8: Modelling PNZ

Features

• data collection• network• methods• validation

Page 9: Modelling PNZ

Data

• behaviour data• socioeconomic data• international trade data• count data

Page 10: Modelling PNZ

• mobility rate and modal split ‐> household and other surveys– Household survey Ljubljana (2003) revealed preference– Stated preference survey for value of time (2007) and PuT quality (2009, 2012)– Mobilitat in Deutschland (2008)– Dateline (2003)– Eurostat– others

• motorization rate (submodel)– statistical data (STAT ‐ Slovenian statistical office)

Behaviour data

y = 0,0173x + 1,3084

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

0 20 40 60 80 100 120 140

mobility rate (trips per person per day)

GDP (purchase power parity, EU27=100)

Correlation mobility/GDP (EU27=100)

Page 11: Modelling PNZ

• population– STAT– Central Registry (number of people by house numbers)– EUROSTAT– national statistical offices (AT, IT, HU, HR)

• labour market– STAT (+ additional survey for exact locations)– EUROSTAT (NUTS3 level)

• other– shop floor area– school places– tourism capacities

Socioeconomic data

Page 12: Modelling PNZ

Economy and international trade data

• national production and consumption by commodities• STAT• FAOSTAT• dissagregation to zones based on number of working places by sectors

• international trade• COMEXT (EU countries)• UN Comtrade (other modelled countries)

Page 13: Modelling PNZ

Count data

• road transport– national road authorities and motorway operators (SI, IT, AT, HU, HR)

• public transport– passenger count on buses on major cross‐sections and regional centres  in 

Slovenia (2012)– passenger count on all railway sections and station (Slovenian Railways, 2012)

• rail freight transport– aggregated data for freight transport (STAT)– number of netto tonnes and trains per section per year (Slovenian Railways; 

2008, 2011)– Austrian National model Verkehr 2025+ (2005, 2015, 2025)– Transport Pocketbook 2012 (EU)

Page 14: Modelling PNZ

Modelling area of CETRA model 

Page 15: Modelling PNZ

Network

• road transport– existing Slovenian road network (BCP, Navteq)

• all national roads are included

– foreign network for 22 countries (Open Street Map)

• public transport– complete bus and railway system in Slovenia (lines, timetable)– railway connections between foreign zones (DB Journey Planner)

• rail transport– www.bueker.net. 

Page 16: Modelling PNZ

Main submodels of CETRA model

• development of macroscopic 4‐step model for passenger and 5‐step for freight transport

• development, calibration and validation of motorization model

• models for external costs

GENERAL PROCEDURES– zoning– network modeling– development of demand– development od 

assignment– calibration of all modes– validation according to 

international guidelines

Page 17: Modelling PNZ

• development, calibration and validation of macroscopic 4‐step model for passenger transport

Passenger model

Oi

Dj

Tij

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• for 23 countries• generation: 13 origin‐destination groups

– each group has own relevant person making trip (e.g. employee) and relevant attraction (e.g. working place)

• simultaneous distribution and mode choice (EVA method)• assignment

– road transport (Equilibrium Lohse)– public transport (Timetable) 

Passenger transport model

Page 19: Modelling PNZ

– number car trips– parking cost and availability in Slovenia– park&ride (P+R) trips in Slovenia– generalized cost [min] = a*journey time [min] + b*distance [km]+c*toll 

[€]

Private transport model

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 10 20 30 40 50 60 70 80 90 100upor w

verje

tnos

t izb

ire F

(w)

Page 20: Modelling PNZ

– lines– stop points (interchange)– timetable assignment– generalized cost [min] = a*journey time [min] + fare[€]

• including discomfort impedance in Slovenia

Public transport model

Page 21: Modelling PNZ

Freight model for 23 countries

• development, calibration and validation of 5‐step for freight transport

• focus on Slovenia• multimodal network

Page 22: Modelling PNZ

Freight model

• 56 commodities• aggregation for 

analysis, e.g.  9 main groups of freight

ID Commodity type logistics modelled

1 Living Animals

agriculture

fresh food Yes2 Cereals bulk: food+fodder Yes3 Potatoes fresh food Yes4 Pulses bagged cargo Yes5 Vegetables fresh food Yes6 Sugar Beet bulk: food+fodder Yes7 Fruits fresh food Yes8 Oli Crops bulk: food+fodder Yes9 Cotton bulk: food+fodder Yes

10 Meat

food and beverage

fresh food Yes11 Vegetable Oil fluid: food Yes12 Food Products bagged cargo Yes

13 Luxury Food Products bagged cargo Yes

14 Raw Wood

Wood

bulk: raw materials Yes

15 Processed Wood bulk: constructionmaterials Yes

16 Wood Products container Yes17 Paper container Yes18 Paper Pulp bulk: raw materials Yes... ... ... ... ...

Page 23: Modelling PNZ

Logistic Systems

• commodities with the same characteristics regarding physical conditions and transportability are allocated to one of the 11 logistic systems 

• different sets of transport costs for each logistic system

a fluid: crude oilb fluid: oil productsc fluid: foodd bulk: raw materialse bulk: construction materialsf bulk: food+fodderg bagged cargoh containeri special truckj fresh foodk natural gas

Page 24: Modelling PNZ

Transport costs )()( hkmfixij CTimeCLengthCw

Distance Costs (Commodity) = Distance Costs (Log. Sys.)Distance Costs in [€/km]‐> (Attribute cost_km of links and connectors)

Time Costs (Commodity) = Time Costs (Log. Sys.)+ Unit * Interest costs (Commodity) + Unit * Loss of Value (Commodity)Time Costs in [€/h] ‐> (Attribute cost_h of links and connectors)

Start Costs (Commodity) = Loading at origin (Log. Sys.) + loss ratio (Log. Sys.) * Value (Commodity) * Unit+ time for un/loading (Log Sys) * Interest costs (Commodity)  * Unit+ time for un/loading (Log Sys) * Loss of Value (Commodity)  * UnitStart Costs in [€] ‐> (Attribute cost_fixed of origin connectors)

End Costs (Commodity) = Unloading at destination (Log. Sys.)+loss ratio (Log. Sys.) * Value (Commodity) * Unit+ time for un/loading (Log Sys) * Interest costs (Commodity)  * Unit+ time for un/loading (Log Sys) * Loss of Value (Commodity)  * UnitEnd Costs in [€] ‐> (Attribute cost_fixed of destination connectors)

TRANSSHIPMENT COSTS =COST_FIXED (Transshipment link)+ loss ratio (Log. Sys.) * Value (Commodity) * 1/2 (because of two links per transshipment)+ idle time (transhipment link) * Interest costs (Commodity)+ idle time (transhipment link) * Loss of Value (Commodity)

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Freight Generation

Detailed approaches for different types of goodsProduction onNational  level

Consumption onNational  level

Production perTraffic zone

Consumption perTraffic zone

Type I:AgricultureProducts/food

1.National

Productionfrom

statistics

2.National

consumptionfrom balancecondition

3.Break down 

to zone level by number of livestock/field area

4.Break down

to zones by population/food industry

Page 26: Modelling PNZ

Freight Distribution

A. impedance matrices: • function of link (considering transport costs)• additional: different types of border crossings

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Freight Distribution

B. distribution function: gravity model in Slovenia• different functions for each commodity

results of distribution: • origin‐destination matrices for each commodity• tonnes flows between zones for each commodity

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Assignment 

combination of • mode choice (traditionally step 3 of transport model)• route choice (traditionally step 4 of transport model)• additional 5th step ‐> creation of subnetworks and joint 

assignment of heavy goods vehicles with cars• most cost efficient route and transport mode chosen

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Assignment Results of assignment: • origin, destination, mode and route for each commodity• transport volumes on all links of the network by commodity• total flows on all links

Basis for further analyses:• desire lines• selected link analysis• modal split

Page 30: Modelling PNZ

Validation results

• passenger model• freight model

– tonnes per year– number of trains– heavy goods vehicle validation

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Freight model (road&rail)

Page 32: Modelling PNZ

Number of trains per day

indicator correlation total difference

netto tonnes/year 0,97 <1%

freight trains/year 0,95 ‐12%

freight trains/day 0,93 ‐12%

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Number of road goods vehicles per daycriteria LGV (Slovenia) HGV (CETRA)RMSE 0,809 0,346transport work ‐2.9% ‐0,3%correlation 0,860 0,985number of sections with GEH <5 83% 95%average GEH 2,97 1,50standard deviation [vehicles] 347 171number of sections 1.002 906

Page 34: Modelling PNZ

Road transport (all vehicles per day)criteria vehiclesRMSE 0,299transport work 0,2%correlation 0,970

number of sections with GEH <5 66,4%average GEH 4,62standard deviation [vehicles] 1.456number of sections 1.002

Page 35: Modelling PNZ

Public passenger traffic

Mod

el a

ttrib

ute

(Vol

Per

sPuT

(AP

))

Page 36: Modelling PNZ

• development of models for traffic accident prediction, gas(CO2, NOx,…) and noise imissions

Models for external costs

Page 37: Modelling PNZ

Railway operation model

• rail infrastructure and equipment modelling• timetable modelling• microscopic simulation 

Page 38: Modelling PNZ

• relevant forecast measures– large scale infrastructure measures, e.g. road, rail– improvement of border crossings 

• CETRA projects (23 countries)– major infrastructure measures (e.g. Koralm bahn)

• additional national projects– projects currently under construction or planning with relevance

for the model (e.g. Koper‐Divača)

Network updates for forecast

Page 39: Modelling PNZ

• population development– population on national level for 2020 and 2030– source: EUROPOP 2008, UN

• economic Development– GDP growth until 2030– economical development (value added by sectors) 

– ‐> elasticity for international trade– ‐> study PRIMES

Socio economic data forecast

Page 40: Modelling PNZ

Practical of use of model CETRA (PRIMOS)• baseline scenario• 3 scenarios• results

Page 41: Modelling PNZ

Balanced scenario (road network)

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Balanced scenario (public transport)

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Forecast of transport conditions

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Traffic volumes

road volumes, average working day, year 2030, balanced scenario

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Traffic volumes

passengers on public transport, average working day, year 2030, balanced scenario

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Accessibility

accessibility  to major cities with public transport, average working day, year 2008

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External costs (noise, air, accidents)

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tourist peak, year 2030, scenario of enhanced role of public transport

Capacity analysis

Page 49: Modelling PNZ

Development and use of national transport model in Slovenia

Gregor Pretnar, M.S.CE ([email protected])

CETRA