road traffic modelling

Cargo Movements on Austria„s Road Network (iMOVE)

EUROSTAT, Oct 11, 2012

Austria„s traffic model (current & future)

Used by the national & state

authorities to plan infrastructure

projects

Passenger & cargo induced road

and rail traffic considering public

as well as private transport

Forecast of volumes based on

demographic projections, trade

and production forecasts

A series of connected sub-models

with a detailed network at its

core to map actual and

forecasted O/D flows

Actual O/D data essentially

recompiled periodically (current

version 2009)

Network characteristics

Overall 243.000 km (o. w. 109.000 road, 84.000 rail)

Austria 32.300 km (o. w. 26.000 road, 6.300 rail)

2412 counties/municipalities in Austria; 216 NUTS3 / NUTS0 regions in Europe

Perceived weaknesses of the current approach

The model‘s empirical foundation

Insufficient accuracy of total transportation volume

Output of transportation sector 2004 estimates range between

363,5 and 415,8 mio. t/km depending on source

Underestimation by the European Road Freight Statistics ?

Inhomogeneous data collections

Spatial differences (NUTS3, highway sections, counties)

Methodological differences between countries in collecting

national road traffic data

Periodical differences (quarterly, yearly (t+1), every four

years) between surveys

Laborious, expensive production process of base data

Main objectives of the iMOVE project

Combine & harmonize different surveys

Incorporate highway toll data into the O/D flows

trips / between counties per truck category per day

Calibrate the O/D flows, using traffic count numbers of

permanent counting stations

[Verify and consider the hypothesized growth in

multimodal movements]

Prototype a repeatable data production process

Improve the production process and the quality of

the O/D flow matrices

Major data sources used to compile the O/D matrix

Austrian Road Freight Transport Statistics (SGVS) Sampling based on Austria‘s Vehicle Registry

Political District Level

Assumed underestimation (foreign (non EU) trucks/non-response)

European Road Traffic Statistics (D-Tables) Only trucks registered nationally are surveyed, combined at EU level

Movements at NUTS3 level

Assumed underestimation (foreign (non EU) trucks/non-response)

Toll data records & Traffic counts Complete set of records collected at gantries for 2009 (highways)

Traffic count data using automatic permanently installed systems (primary & secondary roads)

Cross Alpine Freight Data (CAFT) All trucks, irrespective of nationality are surveyed

Survey performed by Alpine nations every 4 years (O/D, cargo)

Performed at border crossings and major mountain passes

Planned production process

Calibration using the Network Model

Analyze and correct deviations

Traffic survey‘s

European

Road Freight

Austrian Road

Freight

Statistics

Combine &

disaggregate

Cross Alpine

Freight

Toll Data

Records

Traffic Count

Data

Traffic counts

Map flows onto

network graph

Experiences, Status

Combining different survey„s and traffic count information

Reconciling different value sets used in surveys to describe the same

properties: Truck sizes, cargo types, goods classifications

Harmonizing, separating the use of different NUTS3 levels for origin

and destination

Measuring the number of movements between two “traffic

cells”

Derivation of journey’s from data collected at toll bridges

Disaggregating journeys from reported levels to „traffic cells“, using

ecological inference approach.

Calibrating the route allocation of movements to road links

Minimizing deviations between calculated and counted traffic per link

observing O/D movement bounds using non-linear optimization.

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