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.
United Kingdom transport modal share from 1952 to 2014, Department for Transport
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 |
|---|---|---|---|---|---|---|
.svg.png){kind=small} | 3% | 1% | 11% | 85% | 2016[4] | GCCSA |
 |
1% | 0% | 3% | 86% | 2016[5] | UA |
 | 8% | 2% | 37% | 53% | 2006 [6] | |
 | 4% | 1% | 9% | 85% | 2011–2014[7] | MUA |
|
3% | 0% | 7% | 84% | 2016[8] | UA |
 | 32% | 2% | 39% | 27% | 2013[9] | |
 | 21% | 32% | 26% | 21% | 2005/2011[10] | |
 | 23% | 1% | 49% | 27% | 2015 | |
 | 30% | 18% | 27% | 26% | 2018 | |
| 4% | 1% | 14% | 81% | 2016[11] | GCCSA |
.svg.png){kind=small} | 25% | 2.5% | 28% | 43% | 2010[12] | |
 | 15% | 2% | 64% | 19% | 2008[10] | |
| 5% | 1% | 14% | 73% | 2016[13] | UA |
 | 32% | 1% | 47% | 20% | 2011 | |
.svg.png){kind=small} |
4.7% | 1.5% | 14.4% | 79.4% | 2016 | |
| 3% | 1% | 13% | 77% | 2016[14] | UA |
| 1% | 0% | 2% | 90% | 2016[15] | UA |
 | 26% | 2% | 28% | 44% | 2012[16] | |
 | 21% | 12% | 48% | 19% | 2008/2011[10] | |
|
1% | 0% | 2% | 92% | 2016[17] | |
|
3.7% | 1.0% | 11.3% | 84% | 2016 | |
| 28% | 12% | 18% | 42% | 2008[18] | |
 | 29% | 9% | 22% | 39% | 2018[19] | |
| 1% | 0% | 2% | 91% | 2016[20] | UA |
| 1% | 0% | 1% | 91% | 2016[21] | UA |
 | 1% | 0.2% | 20% | 78%* | 2019[22] | UA *67% motorbike |
| 1% | 0% | 4% | 90% | 2016[23] | UA |
 | 24% | 2% | 37% | 37% | 2016[24] | |
| 3% | 1% | 5% | 85% | 2016[25] | UA |
| 34% | 0.46% | 24.35% | 39.89% | 2018 [26] | |
 | 9% | 2% | 44% | 45% | 2019[10] | |
| 4% | 2% | 19% | 76% | 2016[11] | GCCSA |
|
2% | 1% | 4% | 87% | 2016[27] | UA |
 | 17% | 6% | 41% | 36% | 2007 [28] | |
 | 13% | 1% | 63% | 20% | 2016 [29] | |
| 5% | 2% | 22% | 70% | 2016[30] | CMA |
| 27% | 6% | 52% | 15% | 2008/2011[10] | |
| 24% | 18% | 24% | 34% | 2017 | |
| 6% | 1% | 33% | 55% | 2016[31] | UA |
 | 27% | 21% | 34% | 18% | 2000[32] | |
|
8% | 2% | 18% | 72% | 2016[33] | CMA |
 | 15% | 5% | 59% | 20% | 2010[34] | |
| 3% | 1% | 12% | 84% | 2016[11] | GCCSA |
| 4% | 1% | 10% | 80% | 2016[35] | UA |
| 2% | 1% | 2% | 87% | 2016[36] | UA |
| 3% | 3% | 7% | 78% | 2016[37] | UA |
 | 22.4% | 0.4% | 52% | 24.5% | 2017[38] | |
 | 29% | 3% | 43% | 25% | 2012[39] | UA |
| 4% | 1% | 29% | 66% | 2014[40] | |
| 2% | 0% | 3% | 90% | 2016[41] | UA |
| 3% | 1% | 3% | 85% | 2016[42] | UA |
| 5% | 2% | 20% | 64% | 2016[43] | UA |
| 2% | 2% | 5% | 84% | 2016[44] | UA |
| 32% | 1% | 36% | 31% | 2017[45] | UA |
| 4% | 1% | 10% | 77% | 2016[46] | UA |
|
N/A | 4% | 66% | 23% | 2014[47] | |
| 27% | 20% | 33% | 20% | 2009/2011[10] | |
 | 22% | 1% | 44% | 33% | 2011[10] | |
| 5% | 1% | 27% | 67% | 2016[11] | GCCSA |
 | 13% | 4% | 43% | 40% | 2016[48] | |
| 23% | 14% | 51% | 12% | 2008/2009[10] | |
| 5% | 1% | 24% | 68% | 2016[49] | CMA |
|
7% | 2% | 20% | 69% | 2016 | CMA |
 | 26% | 7% | 39% | 28% | 2014[50] | |
 | 18% | 3% | 47% | 32% | 2015[51] | |
| 4% | 1% | 16% | 72% | 2016[52] | UA |
Metropolitan Areas with over 250,000 inhabitants
| Metro Area | walking | cycling | public transport | private motor vehicle | year |
|---|---|---|---|---|---|
 | 7% | 27% | 19% | 43% | 2004 |
| 18% | 0% | 13% | 69% | 2004 |
 | 4% | 40% | 29% | 27% | 2014 |
| 13% | 1% | 14% | 72% | 2001 |
 | 33% | 17% | 27% | 22% | 2015[53] |
| 30% | 15% | 32% | 22% | 2015[54] |
| 23% | 0% | 34% | 43% | 2004 |
| 1% | 1% | 25% | 66% | 2001 |
| 8% | 4% | 21% | 67% | 2001 |
| 29% | 12% | 14% | 46% | 2008 |
 | 4% | 0% | 70% | 26% | 2004 |
| 5% | 2% | 57% | 32% | 2012 [55] |
| 6% | 1% | 14% | 79% | 2012 |
| 25% | 23% | 16% | 36% | 2013 |
| 19% | 8% | 12% | 55% | 2011 [56] |
| 5% | 3% | 8% | 85% | 2016[11] |
| 4% | 5% | 4% | 87% | 2011–2014 [7] |
| 7% | 15% | 28% | 50% | 2013 |
| 10% | 30% | 36% | 26% | 2012 |
| 18% | 1% | 10% | 71% | 2004 |
| 19% | 10% | 22% | 49% | 2019 |
| 26% | 18% | 20% | 36% | 2018 |
 | 13.2% | 7.6% | 21.5% | 48.5% | 2016[57] |
| 29% | 12% | 19% | 40% | 2013 |
| 3% | 24% | 8% | 65% | 2004 |
| 19% | 7% | 19% | 55% | 2019 |
| 8% | 4% | 21% | 69% | 2001 |
| 11% | 15% | 30% | 44% | 2015 |
| 29% | 34% | 16% | 21% | 2017 |
| 13% | 33% | 15% | 40% | 2018[58] |
| 20.8% | 5.9% | 32.1% | 41.2% | 2016[59] |
| 24% | 0% | 17% | 59% | 2004 |
 | 12% | 14% | 21% | 52% | 2004 |
| 8% | 1% | 12% | 78% | 2016[60] |
| 4% | 1% | 10% | 84% | 2016[61] |
| 26% | 19% | 19% | 36% | 2017 |
| 37% | 10% | 30% | 22% | 2016 |
| 12% | 0% | 24% | 64% | 2004 |
 | 10% | 0% | 46% | 40% | 2001 |
| 12% | 0% | 11% | 77% | 2004 |
| 6% | 25% | 18% | 51% | 2011 |
| 18% | 1% | 7% | 74% | 2004 |
| 13% | 0% | 26% | 60% | 2001 |
| 24% | 14% | 23% | 39% | 2019 |
 | 29% | 6% | 30% | 34% | 2013 |
| 12% | 1% | 9% | 78% | 2001 |
| 2% | 6% | 11% | 80% | 2016[62] |
| 5% | 14% | 25% | 56% | 2004 |
| 15% | 7% | 43% | 33% | 2004 |
 | 16% | 13% | 28% | 43% | 2015[63] |
| 5% | 22% | 30% | 43% | 2004 |
| 13% | 7% | 18% | 62% | 2014 |
| 26% | 5% | 24% | 45% | 2010 |
 | 11% | 2% | 35% | 48% | 2017[64] |
| 12% | 3% | 5% | 79% | 2004 |
| 3% | 34% | 24% | 39% | 2015 |
| 16% | 1% | 21% | 62% | 2004 |
| 22% | 1% | 20% | 57% | 2004 |
| 19% | 0% | 13% | 68% | 2004 |
 | 36% | 0% | 26% | 38% | 2011[65] |
| 10% | 1% | 23% | 62% | 2011–2014[7] |
|
10% | 7% | 11% | 70% | 2016 |
| 5% | 2% | 14% | 79% | 2016[66] |
| 45.91% | 2.90% | 23.71% | 26.88% | 2017 [67] |
| 33% | 12% | 32% | 21% | 2015[68] |
| Mean ± SD | 13±8% | 8±9% | 24±13% | 55±17% |
Notes: European data is based on the Urban Audit,[69]
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.[70] The cycling modal share is strongly associated with the size of local cycling infrastructure [71]
The Canadian city of Hamilton adopted a similar modal share target plan in 2005.[72]
gollark: Yep. 30 seconds is the limit.
gollark: The GEORGE one alternates every 30 seconds.
gollark: Esoserver, the recent fork.
gollark: One server I'm on rotates its icon by 0.5 degrees every 1850 seconds.
gollark: Someone *did* this? Cool.
See also
- Intermodal passenger transport
- Mode choice (the decisions that determine Modal share, especially in traffic analysis and forecasting)
- Mode of transport
- Rail usage statistics by country
External links
- Epomm – Modal share data for more than 300 Cities with more or less than 100,000 inhabitants, mostly in Europe
- – Modal share data and trends over the past 20 years for Australian cities (unpublished paper by David Ashley)
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