Modal share

Share of mode of transport
title: "Modal share" type: doc version: 1 created: 2026-02-28 author: "Wikipedia contributors" status: active scope: public tags: ["low-carbon-economy", "transportation-planning", "transport-systems", "transport-by-mode"] description: "Share of mode of transport" topic_path: "sports" source: "https://en.wikipedia.org/wiki/Modal_share" license: "CC BY-SA 4.0" wikipedia_page_id: 0 wikipedia_revision_id: 0
::summary Share of mode of transport ::
::figure[src="https://upload.wikimedia.org/wikipedia/commons/2/20/UK_transport_modal_share_from_1952-2014.png" caption="United Kingdom transport modal share from 1952 to 2014, [[Department for Transport"] ::
A modal share (also called mode split, mode-share, or modal split) is the percentage of travelers using a particular type of transportation or number of trips using said type. In freight transportation, this may be measured in mass.
Modal share is an important component in developing sustainable transport within a city or region. In recent years, many cities have set modal share targets for balanced and sustainable transport modes, particularly 30% of non-motorized (cycling and walking) and 30% of public transport. These goals reflect a desire for a modal shift, or a change between modes, and usually encompasses an increase in the proportion of trips made using sustainable modes.
Comparability of data
Modal share data is usually obtained by travel surveys, which are often conducted by local governments, using different methodologies. Sampling and interviewing techniques, definitions, the extent of geographical areas and other methodological differences can influence comparability. Most typical surveys refer to the main mode of transport used during trips to work. Surveys covering entire metropolitan areas are preferred over city proper surveys which typically cover only the denser inner city. the reference years in these lists span over two decades, making comparisons problematic, especially given changing population, new transportation infrastructure and the effect of the COVID-19 pandemic, among other factors.
Modal split of journeys to work
The following tables present the modal split of journeys to work. Note that it is better to use a measure of all trips on a typical weekday, but journey to work data is more readily available. It would also be beneficial to disaggregate private motor vehicles figures to car driver, car passengers and motorbikes (especially relevant for Asian cities).
Metropolitan areas with over 1,000,000 inhabitants
::data[format=table]
| Metro area | Walking | Cycling | Public transport | Private motor vehicle | Year | Survey area | Country |
|---|---|---|---|---|---|---|---|
| AUS Adelaide | 3% | 1% | 11% | 85% | 2016 | GCCSA | Australia |
| USA Atlanta | 1% | 0% | 3% | 86% | 2016 | UA | USA |
| MEX Mexico City | 1% | 1% | 71% | 22% | 2019 | Mexico | |
| GRE Athens | 8% | 2% | 37% | 53% | 2006 | Greece | |
| NZL Auckland | 5% | 1% | 12% | 81% | url=http://nzdotstat.stats.govt.nz/wbos/Index.aspx?DataSetCode=TABLECODE8298 | title=Main means of travel to work by age group and sex, for the employed census usually resident population count aged 15 years and over, 2018 Census | website=nzdotstat.stats.govt.nz |
| USA Austin | 2% | 1% | 3% | 83% | 2019 | USA | |
| USA Baltimore | 3% | 0% | 7% | 84% | 2016 | UA | USA |
| ESP Barcelona | 34.35% | 2.28% | 37.33% | 26.04% | 2018 | Spain | |
| CHN Beijing | 21% | 32% | 26% | 21% | title=From Transmilenio to Cycle Networks Lessons Learned from Bogotá's Comprehensive Urban Mobility Planning | url=https://itdp.org/wp-content/uploads/2023/05/From-Transmilenio-to-Cycle-Networks-Lessons-Learned-from-Bogotas-Comprehensive-Urban-Mobility-Planning-MAY4.pdf | archive-url=https://web.archive.org/web/20250307173857/https://itdp.org/wp-content/uploads/2023/05/From-Transmilenio-to-Cycle-Networks-Lessons-Learned-from-Bogotas-Comprehensive-Urban-Mobility-Planning-MAY4.pdf |
| SER Belgrade | 23% | 1% | 49% | 27% | 2015 | Serbia | |
| GER Berlin | 34% | 18% | 26% | 22% | 2023 | Germany | |
| AUS Brisbane | 4% | 1% | 14% | 81% | url=https://web.archive.org/web/20171026214129/https://chartingtransport.com/#mode | date=2017-10-26 }}, retrieved 27 October 2017 | GCCSA |
| BEL Brussels | 36% | 9% | 24% | 29% | 2022 | Belgium | |
| COL Bogotá | 24% | 7% | 43% | 15% | 2019 | Colombia | |
| USA Boston | 5% | 1% | 14% | 73% | 2016 | UA | USA |
| ROU Bucharest | 31% | 2% | 27% | 36% | 2015 | Other (taxi): 4% | Romania |
| HUN Budapest | 32% | 1% | 47% | 20% | 2011 | Hungary | |
| CAN Calgary | 4% | 1% | 8% | 84% | 2021 | CMA | Canada |
| USA Chicago | 3% | 1% | 13% | 77% | 2016 | UA | USA |
| GER Cologne | 25% | 19% | 21% | 35% | 2017 | Germany | |
| USA Dallas | 1% | 0% | 2% | 90% | 2016 | UA | USA |
| KOR Daejeon | 26% | 2% | 28% | 44% | 2012 | South Korea | |
| IND Delhi | 21% | 12% | 48% | 19% | 2008/2011 | India | |
| USA Detroit | 1% | 0% | 2% | 92% | 2016 | USA | |
| United States Denver | 2% | 1% | 4% | 81% | 2020 | UA | USA |
| BGD Dhaka | 19% | 39% | 29% | 13% | 2009 | Bangladesh | |
| IRL Dublin | 18% | 7% | 15% | 59% | 2020 | Ireland | |
| CAN Edmonton | 3% | 1% | 6% | 87% | 2021 | CMA | Canada |
| CHN Guangzhou | 35% | 19% | 22% | 23% | 2021 | China | |
| GER Hamburg | 22% | 22% | 24% | 32% | 2022 | Germany | |
| FIN Helsinki | 10.99% | 9.34% | 32.42% | 46% | 2016 | MA, Other: 0.5% | Finland |
| HKG Hong Kong | 11% | 0.5% | 77% | 12% | 2011 | China | |
| USA Houston | 1% | 0% | 2% | 91% | 2016 | UA | USA |
| USA Indianapolis | 1% | 0% | 1% | 91% | 2016 | UA | USA |
| IDN Jakarta | 1% | 0.2% | 20% | 78%* | 2019 | UA *67% motorbike | Indonesia |
| MAS Kuala Lumpur | 0.5% | 0.5% | 21% | 78% | 2018 | Malaysia | |
| USA Las Vegas | 1% | 0% | 4% | 90% | 2016 | UA | USA |
| UK London | 26% | 2.5% | 44.5% | 27% | 2020 | UK | |
| USA Los Angeles | 3% | 1% | 5% | 85% | 2016 | UA | USA |
| ESP Madrid | 34% | 0.5% | 25% | 40% | 2018 | Spain | |
| PHI Manila | 9% | 2% | 44% | 45% | 2019 | Philippines | |
| AUS Melbourne | 4% | 2% | 19% | 76% | 2016 | GCCSA | Australia |
| USA Miami | 2% | 1% | 4% | 87% | 2016 | UA | USA |
| ITA Milan | 18% | 10% | 41% | 29% | 2014 | Italy | |
| Belarus Minsk | 13% | 1% | 63% | 20% | 2016 | Belarus | |
| CAN Montreal | 5% | 2% | 22% | 70% | 2016 | CMA | Canada |
| IND Mumbai | 27% | 6% | 52% | 15% | 2008/2011 | India | |
| GER Munich | 33% | 21% | 22% | 24% | 2023 | Germany | |
| JPN Nagoya | 15% | 13% | 30% | 43% | url=https://www.ido.city.nagoya.jp/machidukuri/genjo/traffic.html | script-title=ja:代表交通手段割合|名古屋市の交通の現状|交通まちづくり | language=ja |
| USA New York City | 30.7% | 1.1% | 32.1% | 30.2% | 2019 | UA | USA |
| JPN Osaka | 7% | 19% | 61% | 13% | title=大阪市における人の動き:平成 22 年 第5回近畿圏パーソントリップ調査集計結果から | url=https://www.city.osaka.lg.jp/toshikeikaku/cmsfiles/contents/0000177/177205/hitonougoki.pdf | website=第5回パーソントリップ調査 |
| CAN Ottawa | 8% | 2% | 18% | 72% | 2016 | CMA | Canada |
| FRA Paris | 40% | 2% | 22% | 34% | 2020 | Parisiens | France |
| AUS Perth | 3% | 1% | 12% | 84% | 2016 | GCCSA | Australia |
| USA Philadelphia | 4% | 1% | 10% | 80% | 2016 | UA | USA |
| USA Phoenix | 2% | 1% | 2% | 87% | 2016 | UA | USA |
| USA Portland | 3% | 3% | 7% | 78% | 2016 | UA | USA |
| CZE Prague | 35% | 1% | 37% | 25% | 2021 | Czech Republic | |
| BRA Rio de Janeiro | 29% | 3% | 43% | 25% | 2012 | UA | Brazil |
| ITA Rome | 4% | 1% | 29% | 66% | 2014 | Italy | |
| USA San Antonio | 2% | 0% | 3% | 90% | 2016 | UA | USA |
| USA San Diego | 3% | 1% | 3% | 85% | 2016 | UA | USA |
| USA San Francisco | 5% | 2% | 20% | 64% | 2016 | UA | USA |
| USA San Jose | 2% | 2% | 5% | 84% | 2016 | UA | USA |
| CHL Santiago | 34.5% | 4% | 29.6% | 25.7% | 2012 | UA | Chile |
| BRA São Paulo | 32% | 1% | 36% | 31% | 2017 | UA | Brazil |
| USA Seattle | 4% | 1% | 10% | 77% | 2016 | UA | USA |
| KOR Seoul | N/A | 4% | 66% | 23% | 2014 | South Korea | |
| CHN Shanghai | 27% | 20% | 33% | 20% | 2009/2011 | China | |
| SGP Singapore | 22% | 1% | 44% | 33% | 2011 | Singapore | |
| Bulgaria Sofia | N/A | N/A | 73% | 27% | 2010 | Bulgaria | |
| SWE Stockholm | 14% | 7% | 47% | 32% | 2011 | Sweden | |
| AUS Sydney | 5% | 1% | 27% | 65% | 2020 | Deloitte | Australia |
| TWN Taipei | 13% | 4% | 43% | 40% | 2016 | Taiwan | |
| ISR Tel Aviv | 8.2% | 4.3% | 17.7% | 62.5% | 2022 | Israel | |
| JPN Tokyo | 23% | 14% | 51% | 12% | 2008/2009 | Japan | |
| CAN Toronto | 5% | 1% | 16% | 76% | 2021 | CMA | Canada |
| CAN Vancouver | 6% | 2% | 15% | 75% | 2021 | CMA | Canada |
| AUT Vienna | 30% | 11% | 34% | 25% | 2024 | Austria | |
| POL Warsaw | 18% | 3% | 47% | 32% | 2015 | Poland | |
| USA Washington, D.C. | 3% | 1% | 6% | 56% | 2022 | UA | USA |
| :: |
Metropolitan areas with over 250,000 inhabitants
::data[format=table]
| Metro area | walking | cycling | public transport | private motor vehicle | year |
|---|---|---|---|---|---|
| DEN Aarhus | 7% | 27% | 19% | 43% | 2004 |
| ESP Alicante | 18% | 0% | 13% | 69% | 2004 |
| NED Amsterdam | 5% | 30% | 19% | 42% | 2020{{cite web |
| ITA Bari | 13% | 1% | 14% | 72% | 2001 |
| SUI Basel | 33% | 17% | 27% | 22% | url=https://www.mobilitaet.bs.ch/dam/jcr:aa8aa166-f637-49ac-afd5-831744c3e74c/staedtevergleich_2015.pdf |
| SUI Bern | 30% | 15% | 32% | 22% | 2015 |
| ESP Bilbao | 68.1% | 0.9% | 19.6% | 11.1% | 2021 |
| UK Birmingham | 1% | 1% | 25% | 66% | 2001 |
| ITA Bologna | 8% | 4% | 21% | 67% | 2001 |
| GER Bonn | 28% | 15% | 17% | 41% | 2017 |
| SVK Bratislava | 26.7% | 1.6% | 32.6% | 37.7% | 2014 |
| CZ Brno | 5% | 2% | 57% | 32% | 2012 |
| USA Buffalo | 6% | 1% | 14% | 79% | 2012 |
| GER Bremen | 25% | 25% | 15% | 36% | 2018 |
| UK Bristol | 19% | 8% | 12% | 55% | 2011 |
| AUS Canberra | 5% | 3% | 8% | 85% | 2016 |
| NZL Christchurch | 4% | 6% | 5% | 84% | 2018 |
| DEN Copenhagen | 30% | 26% | 18% | 26% | 2021{{cite web |
| ESP Córdoba | 18% | 1% | 10% | 71% | 2004 |
| GER Dortmund | 19% | 10% | 22% | 49% | 2019 |
| GER Dresden | 26% | 18% | 20% | 36% | 2018 |
| IRE Dublin | 13.2% | 7.6% | 21.5% | 48.5% | 2016 |
| GER Düsseldorf | 34% | 13% | 18% | 35% | 2017 |
| UK Edinburgh | 19% | 7% | 30% | 42% | 2009–2010 |
| NED Eindhoven | 3% | 24% | 8% | 65% | 2004 |
| GER Essen | 19% | 7% | 19% | 55% | 2019 |
| ITA Florence | 8% | 4% | 21% | 69% | 2001 |
| GER Frankfurt | 11% | 15% | 30% | 44% | 2015 |
| GER Freiburg im Breisgau | 29% | 34% | 16% | 21% | 2017 |
| BEL Gent | 15.6% | 33.8% | 11.2% | 39% | 2021 |
| POL Gdańsk | 20.8% | 5.9% | 32.1% | 41.2% | 2016 |
| ESP Gijón | 24% | 0% | 17% | 59% | 2004 |
| SWE Gothenburg | 12% | 14% | 21% | 52% | 2004 |
| AUT Graz | 19% | 19% | 20% | 42% | 2018 |
| NED The Hague | 5% | 22% | 30% | 43% | 2004 |
| CAN Halifax | 8% | 1% | 12% | 78% | 2016 |
| CAN Hamilton | 4% | 1% | 10% | 84% | 2016 |
| GER Hanover | 26% | 19% | 19% | 36% | 2017 |
| POL Kraków | 28.4% | 1.2% | 36.3% | 33.7% | 2013 |
| ESP Las Palmas | 15% | 0.42% | 13% | 68% | 2011 |
| POR Lisbon | 15.6% | 2.5% | 30.8% | 50.2% | 2020 |
| ESP Málaga | 12% | 0% | 11% | 77% | 2004 |
| SWE Malmö | 14% | 26% | 25% | 34% | 2018 |
| ESP Murcia | 18% | 1% | 7% | 74% | 2004 |
| ITA Naples | 13% | 0% | 26% | 60% | 2001 |
| GER Nuremberg | 30% | 15% | 23% | 32% | 2023 |
| NOR Oslo | 32% | 6% | 31% | 29% | 2022 |
| ITA Palermo | 12% | 1% | 9% | 78% | 2001 |
| ESP Pamplona | 42% | 2% | 13% | 41% | 2013 |
| POL Poznań | 20.6% | 8.4% | 33.7% | 37.3% | 2019 |
| CAN Quebec City | 2% | 6% | 11% | 80% | 2016 |
| NED Rotterdam | 5% | 14% | 25% | 56% | 2004 |
| ESP Seville | 13% | 7% | 18% | 62% | 2014 |
| GER Stuttgart | 29% | 8% | 23% | 40% | 2017 |
| EST Tallinn | 14% | 2% | 34% | 49% | 2020 |
| FIN Tampere | 10% | 10% | 14% | 66% | 2021 |
| ITA Turin | 12% | 3% | 5% | 79% | 2004 |
| NED Utrecht | 25.3% | 48.4% | 5.4% | 18.7% | 2018 |
| ESP Valencia | 16% | 1% | 21% | 62% | 2004 |
| ESP Valladolid | 22% | 1% | 20% | 57% | 2004 |
| ESP Vigo | 19% | 0% | 13% | 68% | 2004 |
| LTU Vilnius | 36% | 0% | 26% | 38% | 2011 |
| ESP Vitoria-Gasteiz | 45.6% | 8.0% | 9.5% | 35.5% | 2021 |
| NZL Wellington | 21% | 4% | 23% | 49% | 2018 |
| CAN Victoria (CMA) | 10% | 7% | 11% | 70% | 2016 |
| CAN Winnipeg | 5% | 2% | 14% | 79% | 2016 |
| POL Wrocław | 24.2% | 6.3% | 27.6% | 41.4% | 2018 |
| ESP Zaragoza | 45.91% | 2.90% | 23.71% | 26.88% | 2017 |
| SUI Zürich | 33% | 12% | 32% | 21% | 2015 |
| Mean ± SD | 13±8% | 8±9% | 24±13% | 55±17% | |
| :: |
Notes: European data is based on the Urban Audit
Modal share targets
The Charter of Brussels, signed by 36 cities including Brussels, Ghent, Milan, Munich, Seville, Edinburgh, Toulouse, Bordeaux, Gdansk, and Timișoara, commits the signatories to achieve at least 15% of bicycling modal share by 2020, and calls upon European institutions to do likewise. The cycling modal share is strongly associated with the size of local cycling infrastructure.{{cite journal | last = Mueller | first = N | title = Health impact assessment of cycling network expansions in European cities. | journal = Preventive Medicine | volume = 109 | issue = | pages = 62–70 | year = 2018 | pmid = 29330030| doi = 10.1016/j.ypmed.2017.12.011 | hdl = 10230/42143 | s2cid = 3774985 | url = https://www.zora.uzh.ch/id/eprint/148599/1/Health-impact-assessment-of-cycling-network-expansions-in-European-cities.pdf | hdl-access = free
The Canadian city of Hamilton adopted a similar modal share target plan in 2005.
Modal share in the developing world
The modal share differs considerably depending on each city in the developing world.
According to UNECE, the global on-road vehicle fleet is to double by 2050 (from 1,2 billion to 2,5 billion, see introduction), with most future car purchases taking place in developing countries. Some experts even mention that the number of vehicles in developing countries will increase by 4 or 5-fold by 2050 (compared to current car use levels), and that the majority of these will be second-hand.
Legislation impacting the modal share
Legislation can discourage car ownership through, for example, taxation and conditions on new car purchases). This could help in achieving a modal shift.
Notes
References
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- "How do people move around?".
- "Used vehicle background overview".
- "Regulation for 2nd hand vehicles".
- "Green light for sustainable mobility".
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