Modal share
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 |
|---|---|---|---|---|---|---|---|
| Template:Flagicon Adelaide | 3% | 1% | 11% | 85% | 2016[4] | GCCSA | Australia |
| Template:Flagicon Atlanta | 1% | 0% | 3% | 86% | 2016[5] | UA | USA |
| Template:Flagicon Mexico City | 1% | 1% | 71% | 22% | 2019[6] | Mexico | |
| Template:Flagicon Athens | 8% | 2% | 37% | 53% | 2006[7] | Greece | |
| Template:Flagicon Auckland | 5% | 1% | 12% | 81% | 2018[8] | MUA | New Zealand |
| Template:Flagicon Austin | 2% | 1% | 3% | 83% | 2019[9] | USA | |
| Template:Flagicon Baltimore | 3% | 0% | 7% | 84% | 2016[10] | UA | USA |
| Template:Flagicon Barcelona | 34.35% | 2.28% | 37.33% | 26.04% | 2018[11] | Spain | |
| Template:Flagicon Beijing | 21% | 32% | 26% | 21% | 2005/2011[12] | China | |
| Template:Flagicon Belgrade | 23% | 1% | 49% | 27% | 2015 | Serbia | |
| Template:Flagicon Berlin | 30% | 18% | 27% | 26% | 2018 | Germany | |
| Template:Flagicon Brisbane | 4% | 1% | 14% | 81% | 2016[13] | GCCSA | Australia |
| Template:Flagicon Brussels | 36% | 9% | 24% | 29% | 2022[14] | Belgium | |
| Template:Flagicon Bogota | 24% | 7% | 43% | 15% | 2019[12] | Colombia | |
| Template:Flagicon Boston | 5% | 1% | 14% | 73% | 2016[15] | UA | USA |
| Template:Flagicon Bucharest | 31% | 2% | 27% | 36% | 2015[16] | Other (taxi): 4% | Romania |
| Template:Flagicon Budapest | 32% | 1% | 47% | 20% | 2011 | Hungary | |
| Template:Flagicon Calgary | 4% | 1% | 8% | 84% | 2021 [17] | CMA | Canada |
| Template:Flagicon Chicago | 3% | 1% | 13% | 77% | 2016[18] | UA | USA |
| Template:Flagicon Cologne | 25% | 19% | 21% | 35% | 2017[19] | Germany | |
| Template:Flagicon Dallas | 1% | 0% | 2% | 90% | 2016[20] | UA | USA |
| Template:Flagicon Daejeon | 26% | 2% | 28% | 44% | 2012[21] | South Korea | |
| Template:Flagicon Delhi | 21% | 12% | 48% | 19% | 2008/2011[12] | India | |
| Template:Flagicon Detroit | 1% | 0% | 2% | 92% | 2016[22] | USA | |
| Template:Flagicon Denver | 2% | 1% | 4% | 81% | 2020[23] | UA | USA |
| Template:Flagicon Dhaka | 19% | 39% | 29% | 13% | 2009[24] | Bangladesh | |
| Template:Flagicon Dublin | 18% | 7% | 15% | 59% | 2020[25] | Ireland | |
| Template:Flagicon Edmonton | 3% | 1% | 6% | 87% | 2021 [26] | CMA | Canada |
| Template:Flagicon Guangzhou | 35% | 19% | 22% | 23% | 2021[27][28] | China | |
| Template:Flagicon Hamburg | 22% | 22% | 24% | 32% | 2022[29] | Germany | |
| Template:Flagicon Helsinki | 10.99% | 9.34% | 32.42% | 46% | 2016[30] | MA, Other: 0.5% | Finland |
| Template:Flagicon Hong Kong | 11% | 0.5% | 77% | 12% | 2011[31] | China | |
| Template:Flagicon Houston | 1% | 0% | 2% | 91% | 2016[32] | UA | USA |
| Template:Flagicon Indianapolis | 1% | 0% | 1% | 91% | 2016[33] | UA | USA |
| Template:Flagicon Jakarta | 1% | 0.2% | 20% | 78%* | 2019[34] | UA *67% motorbike | Indonesia |
| Template:Flagicon Kuala Lumpur | 0.5% | 0.5% | 21% | 78% | 2018[35] | Malaysia | |
| Template:Flagicon Las Vegas | 1% | 0% | 4% | 90% | 2016[36] | UA | USA |
| Template:Flagicon London | 26% | 2.5% | 44.5% | 27% | 2020[37] | UK | |
| Template:Flagicon Los Angeles | 3% | 1% | 5% | 85% | 2016[38] | UA | USA |
| Template:Flagicon Madrid | 34% | 0.5% | 25% | 40% | 2018[39] | Spain | |
| Template:Flagicon Manila | 9% | 2% | 44% | 45% | 2019[12] | Philippines | |
| Template:Flagicon Melbourne | 4% | 2% | 19% | 76% | 2016[13] | GCCSA | Australia |
| Template:Flagicon Miami | 2% | 1% | 4% | 87% | 2016[40] | UA | USA |
| Template:Flagicon Milan | 18% | 10% | 41% | 29% | 2014[41] | Italy | |
| Template:Flagicon Minsk | 13% | 1% | 63% | 20% | 2016[42] | Belarus | |
| Template:Flagicon Montreal | 5% | 2% | 22% | 70% | 2016[43] | CMA | Canada |
| Template:Flagicon Mumbai | 27% | 6% | 52% | 15% | 2008/2011[12] | India | |
| Template:Flagicon Munich | 33% | 21% | 22% | 24% | 2023[44] | Germany | |
| Template:Flagicon Nagoya | 15% | 13% | 30% | 43% | 2011[45] | Japan | |
| Template:Flagicon New York City | 30.7% | 1.1% | 32.1% | 30.2% | 2019[46] | UA | USA |
| Template:Flagicon Osaka | 7% | 19% | 61% | 13% | 2010[47] | Japan | |
| Template:Flagicon Ottawa | 8% | 2% | 18% | 72% | 2016[48] | CMA | Canada |
| Template:Flagicon Paris | 40% | 2% | 22% | 34% | 2020[49] | Parisiens | France |
| Template:Flagicon Perth | 3% | 1% | 12% | 84% | 2016[13] | GCCSA | Australia |
| Template:Flagicon Philadelphia | 4% | 1% | 10% | 80% | 2016[50] | UA | USA |
| Template:Flagicon Phoenix | 2% | 1% | 2% | 87% | 2016[51] | UA | USA |
| Template:Flagicon Portland | 3% | 3% | 7% | 78% | 2016[52] | UA | USA |
| Template:Flagicon Prague | 35% | 1% | 37% | 25% | 2021[53] | Czech Republic | |
| Template:Flagicon Rio de Janeiro | 29% | 3% | 43% | 25% | 2012[54] | UA | Brazil |
| Template:Flagicon Rome | 4% | 1% | 29% | 66% | 2014[55] | Italy | |
| Template:Flagicon San Antonio | 2% | 0% | 3% | 90% | 2016[56] | UA | USA |
| Template:Flagicon San Diego | 3% | 1% | 3% | 85% | 2016[57] | UA | USA |
| Template:Flagicon San Francisco | 5% | 2% | 20% | 64% | 2016[58] | UA | USA |
| Template:Flagicon San Jose | 2% | 2% | 5% | 84% | 2016[59] | UA | USA |
| Template:Flagicon Santiago | 34.5% | 4% | 29.6% | 25.7% | 2012[60] | UA | Chile |
| Template:Flagicon São Paulo | 32% | 1% | 36% | 31% | 2017[61] | UA | Brazil |
| Template:Flagicon Seattle | 4% | 1% | 10% | 77% | 2016[62] | UA | USA |
| Template:Flagicon Seoul | N/A | 4% | 66% | 23% | 2014[63] | South Korea | |
| Template:Flagicon Shanghai | 27% | 20% | 33% | 20% | 2009/2011[12] | China | |
| Template:Flagicon Singapore | 22% | 1% | 44% | 33% | 2011[12] | Singapore | |
| Template:Flagicon Sofia | N/A | N/A | 73%Template:Efn | 27% | 2010[64] | Bulgaria | |
| Template:Flagicon Stockholm | 14% | 7% | 47% | 32% | 2011[65] | Sweden | |
| Template:Flagicon Sydney | 5% | 1% | 27% | 65% | 2020[66] | Deloitte | Australia |
| Template:Flagicon Taipei | 13% | 4% | 43% | 40% | 2016[67] | Taiwan | |
| Template:Flagicon Tel Aviv | 8.2% | 4.3% | 17.7% | 62.5% | 2022[68] | Israel | |
| Template:Flagicon Tokyo | 23% | 14% | 51% | 12% | 2008/2009[12] | Japan | |
| Template:Flagicon Toronto | 5% | 1% | 16% | 76% | 2021[69] | CMA | Canada |
| Template:Flagicon Vancouver | 6% | 2% | 15% | 75% | 2021[70] | CMA | Canada |
| Template:Flagicon Vienna | 32% | 10% | 32% | 26% | 2023[71] | Austria | |
| Template:Flagicon Warsaw | 18% | 3% | 47% | 32% | 2015[72] | Poland | |
| Template:Flagicon Washington, D.C. | 3% | 1% | 6% | 56% | 2022[73] | UA | USA |
Metropolitan areas with over 250,000 inhabitants
Notes: European data is based on the Urban Audit[105]
The Charter of BrusselsTemplate:Broken anchor, 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.[106] The cycling modal share is strongly associated with the size of local cycling infrastructure.[107]
The Canadian city of Hamilton adopted a similar modal share target plan in 2005.[108]
The modal share differs considerably depending on each city in the developing world.[109][110][111]
According to UNECE, the global on-road vehicle fleet is to double by 2050 (from 1,2 billion to 2,5 billion,[112] 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][113]
Legislation can discourage car ownership through, for example, taxation and conditions on new car purchases). This could help in achieving a modal shift.[114]
See also
- Air travel demand reduction
- Car ownership
- Circulation plan
- Phase-out of fossil fuel vehicles
- Intermodal passenger transport
- Mobility transition
- Mode choice (the decisions that determine Modal share, especially in traffic analysis and forecasting)
- Mode of transport
- Motonormativity
- Rail usage statistics by country
- Road reallocation
- Environmental aspects of the electric car
- Smart mobility
Notes
External links
- Epomm – Modal share data for more than 300 Cities with more or less than 100,000 inhabitants, mostly in Europe Template:Webarchive
- [1] – Modal share data and trends over the past 20 years for Australian cities (unpublished paper by David Ashley)
References
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