Step by step introduction kick off

10 April 2023

Step By Step

ERA-NET Transport III Kick Stepping Stones Program

Wim Korver

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Udo J. Becker

Lehrstuhl für Verkehrsökologie

Jeffrey Raymond Kenworthy

Professor in Sustainable Cities

Jasek Malasek

Transport researcher

Road and Bridge Research Institute

Helen Lindblom

Transport researcher

Wim Korver

Head R&D

Goudappel Group

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Content

• Background• Research questions• Base approach• Research Activities• Feedback on tendering and contracting

process

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Back

grou

nd

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Transport is a major CO2 producer

• Transport: 23% of energy related CO2 emissions

• Business as usual: transport share increases to 35%

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CO2 reduction: combination of (inter)national policy and local policy: the example Breda (medium sized city in NL)

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1990 2010 2044 BUA 2044 Confirmed PolicyPackage

2044 Additional PolicyPackage

CO

2 E

mis

sio

ns

Public Transport

Passenger Car

Trucks

-40%

A substantial extra effort is needed to

reach CO2 reduction goals

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Background

• Transport will become in

Europe the major producer of CO2 emissions• Technology will help, but on a local/regional

scale more is needed: without behavioral change no sustainable mobility system

• A lot of initiatives: e.g. CIVITAS, Better Benutten (NL) and Forschungsprogramm Stadtverkehr (GE)

• Which behavioral intervention, that is the question?

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Rese

arch

Que

stio

ns

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Main Objective

• Stepping Stones:1.To understand the successful (policy) measures aimed at

making mobility patterns more sustainable and the underlying mechanisms (the how) including social & psychological factors.

2.The research results should be of common interest across Europe or in several regions.

• Step By Step:• Identifying potential successful policy measures for changing

the transport behavior of people based on structural differences between cities and cultures

What we know after the project is

completed

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Research questions Step By Step

1. Framework to make a distinction between structural and behavioral factors

2. Creating a pan-European database of mobility patterns and the environmental effects

3. Identifying major structural factors for differences in mobility patterns

4. Identifying major behavioral factors for influencing mobility behavior

5. Identifying potential successful policy measures

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Base Research Approach

A. Empirical based: the use of (urban) cases

B. Structural versus behavioral factors

Base

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Empirical work based on approximately 30 cases _1Metropolitan region Case Code Country Type of Intervention

Car Sharing A1 NL Transport concept

Amsterdam West A2 NL Attitude

Amsterdam

Westpoort A3 NL Transport concept

Spitsscoren B1 NL Demand Rotterdam

Mobility Management B2 NL Demand

Lifestyle C1 NL Attitude Breda

Cargo Bike C2 NL Transport concept

Job Ticket D1 D Demand

Infineon D2 D Demand

Electric Busses D3 D Transport concept

Dresden

Commuter network D4 D Transport concept

Slow modes E1 D Transport concept Berlin

Car sharing E2 D Transport concept

New residents F1 D Attitude Munich

Increasing bicycle use F2 D Transport concept

Eco friendly license G1 D Demand Freiburg

Car free living area G2 D Attitude

Tübingen Mobility manager H1 D Demand

Congestion charges I1 S Demand Stockholm

MM for Kista business park & Galleria shopping centre

I2 S Demand

The West Swedish Solution J1 S Attitude Gothenburg

free pass for commuters J2 S Demand

No ridiculous car trips K1 S Attitude Malmö/Lund

Lundalänken K2 S Transport concept

P+R L1 PL Transport concept

Increasing bicycle use L2 PL Attitude

Warszaw

Bus lanes L3 PL Transport concept

Cracow City Bike M1 PL Transport concept

Wroclaw Integrated Cycling Policy N1 PL Attitude

Mobility data on metropolitan level

Behavioral knowledge based

on cases

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UK cases (2) will be

chosen later

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Empirical work based on approximately 30 cases _2

Distribution among countries

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NL GE SW PL UK

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Empirical work based on approximately 30 cases _ 3

Case Characteristics

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Attitude

Demand

Transport concept

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Structural versus behavioral factors _1

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Structural versus behavioral factors _2Cities with high densities have lower transport related emissions

CO2-emission of passenger mobility of inhabitants of Dutch municipalities (ton CO2 per year

Source: CO2 benchmark Goudappel Coffeng)

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• Transport behavior between cities (could) differ due to:• Density• City size • Demographic structure environmental taxation• Climate• Supply of transport• Geographic characteristics (hilly)• Economic welfare level• (Environmental) taxation• …..

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• We are not starting from scratch• Mobility data available for (international Database Kenworthy):

Berlin, Frankfurt, Hamburg, Munich, Zurich, Copenhagen, Helsinki, Oslo, Stockholm, London, Manchester, Stuttgart, Amsterdam, Rotterdam and Breda

• A lot of experience in the consortium with international comparative analyses

• Ambition to create:• Mobility indicators

• Environmental Indicators (CO2 emissions, PM10 and NOx)

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Behavioral analysis can become quite complex

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But our knowledge increases

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• Behavioral Analysis:• Framework of Caldini

• SUMO (System for

Evaluation of Mobility

Projects)

• New insights from

behavioral economics

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SUMO Analysis levels

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Rese

arch

Act

ivitie

s

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Planning

Step by step introduction kick off

Technology

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