Langbahn Team – Weltmeisterschaft

Modal share

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.[1] 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.[2]

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.[3] Surveys covering entire metropolitan areas are preferred over city proper surveys which typically cover only the denser inner city.

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

Metro area Walking Cycling Public transport Private motor vehicle Year Survey area Country
Australia Adelaide 3% 1% 11% 85% 2016[4] GCCSA Australia
United States Atlanta 1% 0% 3% 86% 2016[5] UA USA
Mexico Mexico City 1% 1% 71% 22% 2019[6] Mexico
Greece Athens 8% 2% 37% 53% 2006[7] Greece
New Zealand Auckland 5% 1% 12% 81% 2018[8] MUA New Zealand
United States Austin 2% 1% 3% 83% 2019[9] USA
United States Baltimore 3% 0% 7% 84% 2016[10] UA USA
Spain Barcelona 34.35% 2.28% 37.33% 26.04% 2018[11] Spain
China Beijing 21% 32% 26% 21% 2005/2011[12] China
Serbia Belgrade 23% 1% 49% 27% 2015 Serbia
Germany Berlin 30% 18% 27% 26% 2018 Germany
Australia Brisbane 4% 1% 14% 81% 2016[13] GCCSA Australia
Belgium Brussels 36% 9% 24% 29% 2022[14] Belgium
Colombia Bogota 15% 2% 64% 19% 2008[12] Colombia
United States Boston 5% 1% 14% 73% 2016[15] UA USA
Romania Bucharest 31% 2% 27% 36% 2015[16] Other (taxi): 4% Romania
Hungary Budapest 32% 1% 47% 20% 2011 Hungary
Canada Calgary 4% 1% 8% 84% 2021 [17] CMA Canada
United States Chicago 3% 1% 13% 77% 2016[18] UA USA
Germany Cologne 25% 19% 21% 35% 2017[19] Germany
United States Dallas 1% 0% 2% 90% 2016[20] UA USA
South Korea Daejeon 26% 2% 28% 44% 2012[21] South Korea
India Delhi 21% 12% 48% 19% 2008/2011[12] India
United States Detroit 1% 0% 2% 92% 2016[22] USA
United States Denver 2% 1% 4% 81% 2020[23] UA USA
Bangladesh Dhaka 19% 39% 29% 13% 2009[24] Bangladesh
Republic of Ireland Dublin 18% 7% 15% 59% 2020[25] Ireland
Canada Edmonton 3% 1% 6% 87% 2021 [26] CMA Canada
China Guangzhou 35% 19% 22% 23% 2021[27][28] China
Germany Hamburg 22% 22% 24% 32% 2022[29] Germany
Finland Helsinki 10.99% 9.34% 32.42% 46% 2016[30] MA, Other: 0.5% Finland
Hong Kong Hong Kong 11% 0.5% 77% 12% 2011[31] China
United States Houston 1% 0% 2% 91% 2016[32] UA USA
United States Indianapolis 1% 0% 1% 91% 2016[33] UA USA
Indonesia Jakarta 1% 0.2% 20% 78%* 2019[34] UA *67% motorbike Indonesia
Malaysia Kuala Lumpur 7.2% 1.0% 39.7% 52.1% 1992[35] Malaysia
United States Las Vegas 1% 0% 4% 90% 2016[36] UA USA
United Kingdom London 26% 2.5% 44.5% 27% 2020[37] UK
United States Los Angeles 3% 1% 5% 85% 2016[38] UA USA
Spain Madrid 34% 0.5% 25% 40% 2018[39] Spain
Philippines Manila 9% 2% 44% 45% 2019[12] Philippines
Australia Melbourne 4% 2% 19% 76% 2016[13] GCCSA Australia
United States Miami 2% 1% 4% 87% 2016[40] UA USA
Italy Milan 18% 10% 41% 29% 2014[41] Italy
Belarus Minsk 13% 1% 63% 20% 2016[42] Belarus
Canada Montreal 5% 2% 22% 70% 2016[43] CMA Canada
India Mumbai 27% 6% 52% 15% 2008/2011[12] India
Germany Munich 24% 18% 24% 34% 2017 Germany
Japan Nagoya 15% 13% 30% 43% 2011[44] Japan
United States New York City 30.7% 1.1% 32.1% 30.2% 2019[45] UA USA
Japan Osaka 7% 19% 61% 13% 2010[46] Japan
Canada Ottawa 8% 2% 18% 72% 2016[47] CMA Canada
France Paris 15% 5% 59% 20% 2010[48] France
Australia Perth 3% 1% 12% 84% 2016[13] GCCSA Australia
United States Philadelphia 4% 1% 10% 80% 2016[49] UA USA
United States Phoenix 2% 1% 2% 87% 2016[50] UA USA
United States Portland 3% 3% 7% 78% 2016[51] UA USA
Czech Republic Prague 35% 1% 37% 25% 2021[52] Czech Republic
Brazil Rio de Janeiro 29% 3% 43% 25% 2012[53] UA Brazil
Italy Rome 4% 1% 29% 66% 2014[54] Italy
United States San Antonio 2% 0% 3% 90% 2016[55] UA USA
United States San Diego 3% 1% 3% 85% 2016[56] UA USA
United States San Francisco 5% 2% 20% 64% 2016[57] UA USA
United States San Jose 2% 2% 5% 84% 2016[58] UA USA
Chile Santiago 34.5% 4% 29.6% 25.7% 2012[59] UA Chile
Brazil São Paulo 32% 1% 36% 31% 2017[60] UA Brazil
United States Seattle 4% 1% 10% 77% 2016[61] UA USA
South Korea Seoul N/A 4% 66% 23% 2014[62] South Korea
China Shanghai 27% 20% 33% 20% 2009/2011[12] China
Singapore Singapore 22% 1% 44% 33% 2011[12] Singapore
Bulgaria Sofia N/A N/A 73%[a] 27% 2010[63] Bulgaria
Sweden Stockholm 14% 7% 47% 32% 2011[64] Sweden
Australia Sydney 5% 1% 27% 65% 2020[65] Deloitte Australia
Taiwan Taipei 13% 4% 43% 40% 2016[66] Taiwan
Japan Tokyo 23% 14% 51% 12% 2008/2009[12] Japan
Canada Toronto 5% 1% 16% 76% 2021[67] CMA Canada
Canada Vancouver 6% 2% 15% 75% 2021[68] CMA Canada
Austria Vienna 32% 10% 32% 26% 2023[69] Austria
Poland Warsaw 18% 3% 47% 32% 2015[70] Poland
United States Washington, D.C. 3% 1% 6% 56% 2022[71] UA USA


Metropolitan areas with over 250,000 inhabitants

Metro area walking cycling public transport private motor vehicle year
Denmark Aarhus 7% 27% 19% 43% 2004
Spain Alicante 18% 0% 13% 69% 2004
Netherlands Amsterdam 5% 30% 19% 42% 2020[72]
Italy Bari 13% 1% 14% 72% 2001
Switzerland Basel 33% 17% 27% 22% 2015[73]
Switzerland Bern 30% 15% 32% 22% 2015[73]
Spain Bilbao 23% 0% 34% 43% 2004
United Kingdom Birmingham 1% 1% 25% 66% 2001
Italy Bologna 8% 4% 21% 67% 2001
Germany Bonn 28% 15% 17% 41% 2017[74]
Slovakia Bratislava 26.7% 1.6% 32.6% 37.7% 2014[75]
Czech Republic Brno 5% 2% 57% 32% 2012[76]
United States Buffalo 6% 1% 14% 79% 2012
Germany Bremen 25% 25% 15% 36% 2018
United Kingdom Bristol 19% 8% 12% 55% 2011[77]
Australia Canberra 5% 3% 8% 85% 2016[13]
New Zealand Christchurch 4% 6% 5% 84% 2018[8]
Denmark Copenhagen 30% 26% 18% 26% 2021[78]
Spain Córdoba 18% 1% 10% 71% 2004
Germany Dortmund 19% 10% 22% 49% 2019
Germany Dresden 26% 18% 20% 36% 2018
Republic of Ireland Dublin 13.2% 7.6% 21.5% 48.5% 2016[79]
Germany Düsseldorf 34% 13% 18% 35% 2017[80]
United Kingdom Edinburgh 19% 7% 30% 42% 2009–2010[81]
Netherlands Eindhoven 3% 24% 8% 65% 2004
Germany Essen 19% 7% 19% 55% 2019
Italy Florence 8% 4% 21% 69% 2001
Germany Frankfurt 11% 15% 30% 44% 2015
Germany Freiburg im Breisgau 29% 34% 16% 21% 2017
Belgium Gent 15.6% 33.8% 11.2% 39% 2021[82]
Poland Gdańsk 20.8% 5.9% 32.1% 41.2% 2016[83]
Spain Gijón 24% 0% 17% 59% 2004
Sweden Gothenburg 12% 14% 21% 52% 2004
Austria Graz 19% 19% 20% 42% 2018[84]
Netherlands The Hague 5% 22% 30% 43% 2004
Canada Halifax 8% 1% 12% 78% 2016[85]
Canada Hamilton 4% 1% 10% 84% 2016[86]
Germany Hanover 26% 19% 19% 36% 2017
Poland Kraków 28.4% 1.2% 36.3% 33.7% 2013
Spain Las Palmas 15% 0.42% 13% 68% 2011[87]
Portugal Lisbon 15.6% 2.5% 30.8% 50.2% 2020[88]
Spain Málaga 12% 0% 11% 77% 2004
Sweden Malmö 14% 26% 25% 34% 2018[89]
Spain Murcia 18% 1% 7% 74% 2004
Italy Naples 13% 0% 26% 60% 2001
Germany Nuremberg 24% 14% 23% 39% 2019
Norway Oslo 29% 6% 30% 34% 2013
Italy Palermo 12% 1% 9% 78% 2001
Spain Pamplona 42% 2% 13% 41% 2013[90]
Poland Poznań 20.6% 8.4% 33.7% 37.3% 2019
Canada Quebec City 2% 6% 11% 80% 2016[91]
Netherlands Rotterdam 5% 14% 25% 56% 2004
Israel Tel Aviv 16% 13% 28% 43% 2015[92]
Spain Seville 13% 7% 18% 62% 2014
Germany Stuttgart 29% 8% 23% 40% 2017[93]
Estonia Tallinn 14% 2% 34% 49% 2020[94]
Finland Tampere 10% 10% 14% 66% 2021[95]
Italy Turin 12% 3% 5% 79% 2004
Netherlands Utrecht 25.3% 48.4% 5.4% 18.7% 2018[96]
Spain Valencia 16% 1% 21% 62% 2004
Spain Valladolid 22% 1% 20% 57% 2004
Spain Vigo 19% 0% 13% 68% 2004
Lithuania Vilnius 36% 0% 26% 38% 2011[97]
New Zealand Wellington 21% 4% 23% 49% 2018[8]
Canada Victoria (CMA) 10% 7% 11% 70% 2016
Canada Winnipeg 5% 2% 14% 79% 2016[98]
Poland Wrocław 24.2% 6.3% 27.6% 41.4% 2018
Spain Zaragoza 45.91% 2.90% 23.71% 26.88% 2017[99]
Switzerland Zürich 33% 12% 32% 21% 2015[73]
Mean ± SD 13±8% 8±9% 24±13% 55±17%

Notes: European data is based on the Urban Audit[100]

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.[101] The cycling modal share is strongly associated with the size of local cycling infrastructure.[102]

The Canadian city of Hamilton adopted a similar modal share target plan in 2005.[103]

Modal share in the developing world

The modal share differs considerably depending on each city in the developing world.[104][105][106]

According to UNECE, the global on-road vehicle fleet is to double by 2050 (from 1,2 billion to 2,5 billion,[107] 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.[13][108]

Legislation impacting the modal share

Through legislation (i.e. taxing and conditions on new car purchases), car ownership can be discouraged. This could help in achieving a modal shift.[109]

See also

Notes

  1. ^ Result achieved using the percentage of commuters using PT (63%) plus Taxi (3%) and additionally marshrutkas (7%).

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