In this post, I test out a number of possible explanations for the trend in Melbourne’s public transport (PT) patronage growth over recent years to try to find out what might be driving growth. Is it population growth, CBD employment, fuel prices, international students, or the widening of CityLink? You’ll have to read on.

The first chart shows estimated financial year public transport patronage in Melbourne. Note: The method of patronage estimation has changed over the years for all modes. I have assumed comparable measurement for trains and trams and applied my own educated adjustments to bus patronage history (although I am less confident about the early 1990s – officially patronage stayed much the same despite significant service cuts).

Patronage was bumpy in the 1990s, followed by modest growth for about 10 years and then a distinct uptick in growth around 2004/05.

I will attempt to find an explanation for this pattern in this analysis (particularly more recent years). Short of a fully comprehensive analysis, I will compare trends in possible drivers with the trend in public transport patronage.

Note due to the nature of available data sources, the years covered in chart will vary – you can spot each year by checking the year range in the chart titles.

Population growth

(note I have estimated 2010-11 population growth at 1.6% based on the trend in state population) If this was a dominant factor then you’d expect to see a straight line on this chart. It does show that as population growth has increased, so has public transport patronage growth, but the overall relationship isn’t very linear.

We know that public transport use is higher closer to the inner city of Melbourne. So is public transport better correlated with inner city population? The following chart compared PT patronage with “inner” population (LGAs of Melbourne, Port Phillip, Stonnington, Yarra, Hobsons Bay, Maribyrnong, Moonee Valley, Moreland, Darebin, Banyule, Boroondara, and Glen Eira).

The correlation appears to be slightly stronger.

Employment

People often use PT to get to work. The next chart compares total employed people in Melbourne to public transport patronage (employment figures average monthly total employed people for each financial year, from ABS Labour Force surveys).

Again, the relationship isn’t very linear – despite a small growth in employed persons in 2008-09, public transport patronage still increased significantly. But then in 2009-10, employed persons grew but patronage didn’t. Likewise PT patronage increased more between 2000/01 and 2001/02, despite little growth in total employment, whereas in the previous year employment grew strongly, but PT patronage didn’t.

This chart also shows kinks in the trend around 2005 and in 2008-09 – so employment doesn’t seem to explain the kink. Note also that journeys to work only make up around 40% of public transport trips in Melbourne (according to VISTA data). And public transport has a very low mode share of journeys to work outside the city centre.

ABS publish figures monthly, and here’s the picture for total persons employed in Melbourne. There was virtually no growth between late 2010 and the early April 2012 (at least). There was also a flat patch between the start of 2008 and the middle of 2009 (2008-09 shows substantial patronage growth on public transport).

City population (including visitors)

Another hypothesis suggests that if PT is heavily focussed on the CBD (where it has the highest destination mode share), then if more people need to travel to the CBD, this would probably increase PT patronage. This sounds very plausible, especially for trains and trams. The City of Melbourne has estimated weekday daytime population for 2004 to 2010 calendar years. So I am mixing calendar year visitor data with financial year PT patronage – which is not ideal. Anyway, here is what that relationship looks like:

The year 2005/06 includes the 2006 Commonwealth Games that were held in March 2006 and boosted city visitors considerably. If you take out this anomaly, the other four data points look like they form a very linear pattern (as drawn), suggesting it is quite probably a strong driver. There was weak growth in both public transport patronage and city population in 2009-10, suggesting a strong relationship.

A longer time series of CBD data is available for  employment, thanks to the City of Melbourne’s Census of Land Use and Employment. As it hasn’t been an annual survey (red dots are census results), I have made linear interpolations between the years for CBD employment numbers.

Between 1997/98 and 2007/08, the trend was remarkably linear suggesting a strong relationship. When CBD employment grew very weakly between 2002 and 2004, so did PT patronage. Looking at census data for 2001 and 2006, we know that PT mode share to the Melbourne CBD for journeys to work (well, technically the inner Melbourne SLA which is much the same) grew only slightly from 59.1% to 60.8%. So it looks fairly safe to assume that the growth in people using PT to get to jobs in the CBD grew at much the same pace as CBD employment itself.

However between 2007/08 and 2009/10 the trend seems very different. Public transport patronage grew strongly even though the number of employees in the Melbourne CBD did not show much growth at all.

Employment has grown around the Melbourne CBD in neighbouring Docklands, Southbank and there are also a number of office buildings in East Melbourne. In fact between 2008 and 2010 there were around 3,300 new jobs in the CBD, and 11,400 new jobs in Docklands.

These areas are also well serviced by public transport. Unfortunately data for these surrounding precincts only goes back to 2002. Here’s a chart comparing PT patronage to total employment in the CBD, Southbank, Docklands and East Melbourne for 2002 to 2010:

Suddenly the trend looks a lot more linear, with a deviation only for the interpolated result in 2008-09 (which might be a product of the GFC in that timeframe). CBD employment alone is no longer a strong driver of public transport patronage. Although bear in mind that public transport mode share in these CBD fringe areas was much lower than the CBD in 2006 (see previous post).

While the CLUE data series only runs until 2010 at present, a more timely and regular dataset that might be related to CBD employment is occupied office floor space, calculated from the Property Council of Australia’s Office Market Reports. While I do not have access to the reports themselves, much of the data is available on the internet in various forms, and I have used that data to reconstruct the data series (there is chance of errors creeping in, particularly for earlier years).

Here is the trend in occupied Melbourne CBD office space:

Slow growth until about 2005, then very strong growth. Does that trend sound familiar?

This charts shows very strong correlation (r-squared = 0.99). Although there are still a few small kinks such as 2009-10.

But the overall strong relationship this confirms the high likelihood of CBD employment being a very significant driver of public transport patronage. Ideally Southbank, Docklands and East Melbourne should be added to the mix, but the data is not readily available.

Fuel prices

I have taken the monthly average unleaded fuel prices for Melbourne, adjusted for CPI, and then averaged the months for each financial year, to produce the following chart:

Fuel prices are highly volatile, even on an annual basis. Again, even though fuel prices dropped in 2008-09, PT patronage still increased. There seems to be a lot more at work than fuel prices. That said, since 2004-05, real fuel prices jumped from around 115 cents to over 130 cents and have remained higher since. So fuel might be an explanation for the kick up in PT patronage since 2005, perhaps more as the breaking of a psychological price barrier. Or perhaps people’s responses to fuel prices have longer lag times that wash out short-term fluctuations - as people make major decisions – such as the decision to purchase a new car or not. More on that later.

International students

Another hypothesis is that the recent boom in international student numbers drove public transport patronage, as many international students come from countries where public transport is the “default” mode. And while their finances might stretch to studying in Australia, it might not stretch to owning a car (certainly in the car ownership maps we see low car ownership around many universities).

Unfortunately I’ve only found complete data for financial year 2002/03 onwards, and only at the state level (more detailed data is not freely available).

The boom in international students looks like it really took off in 2007, but fell away sharply in 2009-10 and has been lower since. In 2009-10 patronage grew more slowly, perhaps reflecting the drop in international student numbers. But 2010-11 patronage growth was strong again, despite little growth in international student numbers.

The international student numbers are very small in comparison to the total patronage. However if half of those students averaged 10 trips per week for say 40 weeks a year (purely a guess), that’s 38 million trips. I’ve not got data on what their PT use is actually like (I suspect many live close to their school or university and actually walk). And their boom doesn’t coincide with the boom in public transport patronage that started around 2005. So they might be having an impact – hard to conclude much.

Road congestion

Until 2006-07 there was a fairly linear correlation, but then speeds only slowed slight while public transport patronage increased. In 2009-10 speeds increased and public transport patronage grew slowly. Perhaps congestion wasn’t a driver for patronage growth in 2009-10?

Another point to note is the scale on the X axis – the average speed hasn’t changed by very much. Although the variations in AM peak speeds for particular road segments are likely to have changed more significantly, I somewhat doubt whether the average driver would notice the difference between 35.8 km/h and 34.8 km/h (the change between 2005/06 and 2007/08).

The opening of CityLink in 2001 may have led to a slight increase in AM peak speeds, but this seems to have been quickly eroded the following year (so do new freeways ease congestion?). I’m not sure why traffic sped up in 2003/04, but then dropped again significantly the next year.

Road congestion impacts the majority of the tram network, and essentially all of the bus network. So perhaps only trains are attractive as an alternative to driving in congested traffic. Here’s same chart again but plotted only against train patronage:

The chart looks much the same. So congestion might be a driver of PT patronage growth, but it probably doesn’t explain the growth in tram and bus patronage, and the relationship isn’t nearly as linear as other factors.

Perhaps also at play here is congestion being relieved for non-radial commuting, where PT had a low market share beforehand anyway. Further research might look at congestion on CBD-radial roads only, though even then, many will also cater for some cross-city trips.

Two of the radial freeways that feed inner Melbourne are operated as the CityLink toll roads, and quarterly data is available on average daily transactions. If the CityLink toll roads compete with public transport it is probably mostly with trains for longer distance travel to the inner city. Here is a chart showing growth in CityLink transactions and train patronage:

There was very little train growth in the first few years of CityLink (which started in 2001). But then train patronage grew strongly from 2005 while CityLink transaction growth went flat until 2010. A major upgrade project on the eastern leg of CityLink (M1 upgrade) caused delays between 2007 and early 2010, and there was little traffic growth. After the project was largely completed and the fourth lane opened, traffic growth accelerated over 2010. This happened at much the same time that trains recorded weak patronage growth. Then in 2011, train patronage grew again, while traffic seems to have flattened again.

To take a closer look at the two growth rates, here are financial year growth rates on CityLink and trains:

After most of the works were completed, CityLink transaction growth exceeded train patronage growth in 2009-10 and 2010-11 (note that the flattening evident in the previous chart doesn’t show with annual data). The evidence suggests there could well be a relationship between freeway capacity and train patronage, and that the M1 widening project may have reduced patronage growth on the train network. It has certainly enabled a return to strong growth on CityLink.

Car ownership

People who don’t own cars are probably much more likely to use public transport. The following chart uses cars per 100 persons aged 20-74 (as a proxy for people of car driving age).

This chart shows in the early 2000s that car ownership rose quickly, while public transport patronage growth was slow. Then from 2006-07, car ownership levels peaked and public transport patronage grew quickly. Car ownership dropped in 2008-09 just as public transport patronage surged, but recovered in 2009-10, as public transport stalled. This suggests there may be some relationship between PT patronage and car ownership, but the annual change rates aren’t always consistent.

Service kms

Another potential driver of PT patronage is the amount of service provided. Thankfully, this data is available in Victorian State Budget papers (hidden away in budget paper 3) on the number of timetabled service kms for each mode. As the modes are quite different, I’ve plotted modal charts:

Train patronage doesn’t seem to be very strongly related to timetabled kms. Perhaps this is because the service levels at peak times on most lines are already attractive from a frequency point of view at least. Many of the extra train kms are providing capacity without a substantial jump in frequency (although some of the additional kms have been in off-peak periods).  That’s not to suggest there isn’t a relationship, just that it doesn’t look likely to be the dominant driver. In the early 2000s it seems that there wasn’t a strong response to increased timetable kms (including Sydenham electrification in 2002), while in the mid 2000s patronage grew despite kms staying much the same (other factors must be at work).

Again, not a strong relationship between tram kms and patronage, despite strong growth in timetabled kms in the early 2000s (partly from tram extensions into lower density suburbs in 2003 (Box Hill) and 2005 (Vermont South) – see here for more history). It also looks like some cuts in 2000 (when some city routes had to be joined due to the loss of W class trams) were done in a way that didn’t result in a loss of patronage. Perhaps because service frequencies were still fairly good after the cuts.

There does seem to be a stronger relationship between bus kms and patronage. This is perhaps to be expected as bus service levels are on average very low in Melbourne, so improved service levels are likely to result in existing users travelling more, and better attract new users.

What is unexpected is that patronage grew at much the same rate as kms between 2005-06 and 2009-10 – an average elasticity of around 1, which is much higher than you would normally expect. In 2010-11, the annual elasticity fell to 0.42. One possible explanation for the slightly steeper rate in recent years is that more of the new kms have come in the form of SmartBus kms (with higher frequencies). We know that long run implied service elasticities for SmartBus can be around 2 – which is higher than the textbook expectation of service elasticities of up to 1 in the long run. Bus upgrades in the early 2000s were a little more focussed on providing new low-frequency services to the urban fringe, which would be unlikely to lead to as much patronage growth.

Comparing annual growth/change rates

The following table shows the annual change in Melbourne public transport patronage and a number of potential explanatory factors. I’ve used conditional formatting such that darker green cells indicate values you might expect to contribute to strong PT patronage growth. Rows that have dark green in the same years as PT patronage are potentially stronger at explaining the trends in public transport patronage. I’ve also included the r-squared value for a correlation for each factor compared to PT patronage (based on annual growth values, not actual values). You might need to click to enlarge and make it easier to read.

The table confirms a strong correlation with CBD+fringe employment, City of Melbourne visitors (2006 removed due to Commonwealth Games anomaly), international student enrolments, population (particularly inner city), and CityLink volumes.

There is an unexpected positive correlation with car ownership which doesn’t really pass the logic test – other factors must be at play and note the very small changes in car ownership (the table uses growth in cars per population aged 20-74).

Fuel prices don’t show a strong relationship, although it is hard to believe that they would have no impact. If you offset the fuel price changes by one year the correlation rises to 0.3 so there might be some lag involved.

Conclusions

Based on these simple charts, I surmise that City of Melbourne (LGA) visitations is likely to be one of the strongest drivers of overall PT patronage in Melbourne (but certainly not the only driver). And it certainly stands to reason, given PT’s dominant mode share of travel to the CBD.

But international students, radial freeway volumes, population are probably also having an impact. The impact of fuel prices appears to be more complex.

Buses probably show less response to growth the inner city travel market (as most do not serve the city centre), so service kms are likely to be the strongest driver of bus patronage.

The PCA’s Office Market Report provides the most timely and frequent data relating to CBD employment growth and reveals much slower growth over calendar 2011 (1.4% in occupied office floor space). We might find this trend reflected in slower patronage growth on the train network as  figures are published.

Are greenhouse gas emissions from transport still on the rise in Australia? Are vehicle fuel efficiency improvements making a difference?

This post takes a look at available emissions data.

Australian Transport Emissions

The Department of Climate Change’s National Greenhouse Gas Inventory reports Australia’s emissions in great detail, and 1990 to 2010 data was available at the time of updating this post (there is usually more than a year’s lag before this data is released).

But the Department of Climate Change has recently began publishing quarterly reports that includes more recent transport figures. Here’s what the rolling 12 month trend looks like:

Transport emissions surged by 4.8% in 2011. The quarterly report attributes this growth mostly to aviation and road freight sectors.

Here’s the make up of those emissions to 2010:

In 2011 transport represented 16% of total Australian emissions (excluding land use).

Road transport contributed 86% of transport emissions (down slightly from a peak of 89% in 2004). Cars accounted for 50% of Australia’s transport emissions in 2010, but their share has been declining.

Note that the above chart does not include electric rail emissions (see below), indirect emissions, or emissions from international shipping and aviation. They are included in the following chart lifted from an 2008 ATRF paper by BITRE’s David Cosgrove shows this adds a lot on top (and the future projections are frightfully unsustainable). International transport emissions seem to sneak under the radar in the figures.

Per capita transport emissions

The following chart shows Australian transport emissions per capita have been fairly flat, with a drop in 2009 and 2010 but a resurgence in 2011:

An aside on electric rail emissions

Electric rail emissions are included under stationary energy, rather than “transport” in the main inventory. Melbourne train and tram electricity emissions have been estimated at 505  Gg for 2007 (ref page 8). Apelbaum 2006 estimated that Australia electric rail emissions in 2004/05 were 2,082 Gg (ref page 68), which is very similar to the inventory figures. I’ve struggled to find any other figures on electric rail emissions in the public domain.

Sectoral growth trends

Transport is now Australia’s second largest sector (after stationary energy), and transport has had the third highest rate of emissions growth (very close to second placed industrial processes).

Within the transport sector, civil aviation has had the strongest growth since 1990 (but note that a lot of this relates to the bounce-back from significant disruptions to domestic aviation in 1990). There’s been a lot of growth in light commercial vehicles, trucks and buses, and in more recent times, motorcycles and railways. Car emissions peaked in 2004 and have been trending downwards since.

Transport Emissions by state

The national inventory data allows us to see what is happening at a state level. As my interest is primarily in passenger transport here is a chart for road emissions:

The trends show strongest growth in Queensland and Western Australia, little growth in South Australia, and a recent decline in Victoria. It’s hard to see the trends on these charts for Tasmania and the territories due to the scale (sorry). And these growth rates will of course depend on various factors, such as economic development and population growth.

The following charts attempt to remove population growth by showing emissions per capita figures for each state (unfortunately the climate doesn’t take into account per capita (or per-GDP) emissions). Most states appear to be in decline except for Western Australia and the Northern Territory.

Car emissions reductions – mode shift or fuel efficiency?

The following chart shows car emissions per capita (which essentially removes freight from the road transport figures).

Again, all states (except WA and NT) show a decline in recent years, with stronger reductions in the states with cities showing more mode shift to public transport (refer to earlier post on BITRE data).

Is the drop in road transport emissions related to behaviour change and/or fuel/emissions efficiency?

The following chart shows that the average emissions per km of Australia cars has been trending downwards (I’ve used BITRE Working Paper 124 data on car kms travelled hence a little noise):

We’ve seen more significant declines in car emissions per capita since around 2004. So what if cars had made no improvement in emissions intensity since 2004? The following chart estimates what car emissions per capita would have been in that case:

Car emissions per capita  have dropped from 2.20 to 1.87 tonnes between 2004 and 2010. It would appear that emissions efficiency improvements since 2004 can explain 0.12 tonnes of this difference – around 36% of the overall decline. This would suggest that travel behaviour change has contributed around 64% of the reduction in car emissions since 2004.

What about transport emissions in cities?

As part of the Victorian Transport Plan, the Victorian Department of Transport commissioned the Nous Group to do a wedges exercise on Victorian transport emissions. This report included estimates of Melbourne’s 2007 transport emissions (12,270 Mt). In addition, Apelbaums’s Queensland Transport Facts 2006 was for a brief time on the internet and I was lucky enough to grab a copy. From that report, estimates of Brisbane’s 2003-04 transport emissions can be derived (7,312 Mt).

The breakdowns are remarkably similar:

What does this look like per capita? I’ve also added London and Auckland figures (though I am not aware of the make up of the Auckland data) to create the following chart:

Obviously these cities’ transport systems and energy sources are very different, but it shows what is possible even for a large city like London. Transport emissions will closely follow transport energy use per capita, which has been the focus of a lot of research, particularly by Prof Peter Newman (eg his Garnaut Review submission).

For 1995 measures of passenger transport emissions per capita for other cities, see this wikipedia chart created using UITP Millenium Cities Database for 1995. Note: these figures only include passenger transport and hence are different to the above.

Also, here is some data for US cities from the Brookings Institute, but it excludes industry and non-highway transportation so is not comparable to the above chart.

Where are transport emissions headed?

The most recent data suggests that Australian transport emissions are presently on the rise.

The 2010 Department of Climate Change projections suggest transport emissions will continue to rise, as shown in the following chart lifted from their website:

Most of the forecast growth is expected to come from freight vehicles (trucks and light commercials). Curiously they forecast quite small increases in car emissions.  This is based on forecast significant improvements in emissions intensity but also a return to growth in total car kms travelled (including car kms per capita).

Here is a chart of forecast of car emissions intensity, derived from their forecast data on vehicle kms and emissions:

Perhaps more optimistic is the assumption around future oil prices:

At the time of writing the oil price was $113/barrel (in April 2011 US dollars). Even with an inflation adjustment, this is certainly pushing the high end of their sensitivity testing. This prediction of oil prices doesn’t seem to take into account peak oil, or even much of an oil crunch (where supply cannot keep up with demand).

How much is Melbourne sprawling? Is urban consolidation happening? Is the Melbourne 2030 target for urban consolidation being realised?

This post sheds some light by looking at ABS population data and DPCD dwelling approval data.

Population growth

The first chart shows net annual population growth by regions of Melbourne. “outer-growth” refers to the designated growth local government areas (LGAs) on the fringe of Melbourne (see below for definitions of regions and note that the areas have different sizes).

As you can see, Melbourne’s population growth accelerated dramatically in the years up to 2008-09 and has since slowed down. There were a net 65,520 new residents in 2010/11, an average of about 1260 per week (annual growth of 1.7%).

The following chart shows how the growth was spread across Melbourne:

In 2009-10 there was a significant shift in the balance of growth towards the outer suburban designated growth areas, and jumping to 63% in 2010-11 (note the 2009-10 figure of 62% is revised up from a previously estimated 58%). As the first chart shows, very significant growth was recorded in 2009-10 and only slightly fewer people moved into the growth areas in 2010-11. The figures suggest Melbourne is sprawling more than ever.

Note that not all greenfields sites are in outer growth areas – the “outer” areas also include some smaller greenfields developments.

Growth compared to forecasts

The Victorian government periodically makes projections of population growth in all local government areas (LGAs). The following chart shows the ABS population estimates exceed Victoria In Future (VIF) forecasts made in 2008. However the annual growth rates for 2009-10 and 2010-11 were more in line with forecast annual growth rates.

Growth in dwellings

Data on dwelling approvals is published by the Department of Planning and Community Development.

The following chart shows a jump in dwelling approvals in 2009-10, after three years of tracking close to VIF 2008 forecasts. Note that dwelling approvals and ‘net new dwellings’ are not quite measuring the same thing, as a number of dwellings are demolished each year.

Impacts on household sizes

The following chart shows the ratio of population growth to dwelling growth. In 2008-09, there was one new dwelling approved for every 3 new residents, but this dropped one new dwelling for every 1.8 new residents in 2009-10 thanks to the surge of dwelling approvals in 2009-10. Earlier in the decade, the ratio was one dwelling for every 1.5 new residents.

The chart also shows the VIF 2008 forecast of average household size (of occupied dwellings), and forecast ratio of population growth to dwelling growth. The forecast was for slowly declining average household size (following a recent trend).

Until 2010, population growth outstripped dwelling growth which would suggest that actual average household sizes have been forced upwards. Given the surge in dwelling approvals in 2009-10, maybe the housing “crisis” has eased?

Curiously, the ratio of new residents to dwelling approvals was only 1.5 in the early parts of the decade, much lower than average household sizes. Does this reflect small dwelling sizes approved in those years, or a housing glut? I’ll leave that to the housing experts.

Note that not all dwelling approvals represent an increase in available housing stock for permanent residents. The RBA has estimated that around 15% of dwelling approvals replace demolished dwellings, and around 8% are second homes or holiday homes.

Measuring progress against the Melbourne 2030 urban consolidation target

Melbourne doesn’t have population targets for different regions, but there was a target for dwellings growth in the (now defunct) Melbourne 2030 strategy. It stated the aim to:

reduce the overall proportion of new dwellings in greenfield sites from the current figure of 38 per cent to 22 per cent by 2030

The greenfield sites in Melbourne 2030 were mostly (but not entirely) located in the designated growth areas. As “greenfields” dwelling approval data isn’t readily available, I have used dwelling approvals in the designated outer growth LGAs as a proxy (from DPCD’s Residential Land Bulletin). The stated figure of 38% appears to match the data for these LGAs.

The dashed red line is a straight line interpolation of the Melbourne 2030 target for greenfields dwelling share. The outer growth LGA’s share of dwelling approvals has been higher than the target, but fluctuates a fair bit, and curiously has been taking a dive since June 2010. But it seems clear that the Melbourne 2030 target share of dwelling growth in greenfields areas is not being met.

(Note: The outer-growth LGAs’ share early in the decade was much lower. This may reflect urban growth that was still occurring in areas I have classified as “outer” as opposed to “outer-growth” before the Melbourne 2030 plan was released in 2002.)

However, if you look at absolute volumes of population growth in established areas, the story is very different. The next chart shows the VIF 2004 forecasts for population growth by region (I use VIF 2004 because it came out soon after Melbourne 2030):

Urban consolidation in Melbourne has vastly exceeded the VIF 2004 forecasts, even with the slowdown in 2010, as the following chart attests:

[note: the above two charts have not been updated with 2011 data because I have misplaced my VIF2004 dataset. Can anyone help?]

I cannot comment on whether the 2004 forecasts were too conservative.

Unfortunately the available data doesn’t tell us whether this urban consolidation has occurred in designated activity centres, or it is spread throughout the urban area. It will be interesting to look at changes in population density between the 2006 and 2011 censuses.

Appendix: Definitions of regions

I have allocated local government areas to regions as follows:

Centre = Melbourne, Yarra, Port Phillip

Inner = Hobsons Bay, Maribyrnong, Moonee Valley, Moreland, Darebin, Banyule, Boroondara, Stonnington, Glen Eira, Bayside

Middle = Brimbank, Manningham, Whitehorse, Monash, Kingston, Greater Dandenong (all but one in the east)

Outer = Nillumbik, Maroondah, Yarra Ranges, Knox, Frankston, Mornington Peninsular (all in the east and south-east)

Outer growth = Wyndham, Melton, Hume, Whittlesea, Casey, Cardinia

Here is a map of Melbourne with the regions shaded (dotted white are indicates within the 2006 urban growth boundary, sorry the colours don’t match exactly).

Here is a reference map for those unfamiliar with Melbourne LGAs. You’ll need to click to enlarge so you can read the text.

When I get time, I hope to update existing posts to include the most recent data on (the lack of ) traffic growth.

What are the trends in traffic volumes on major roads in Australian cities? Unfortunately there isn’t a lot of data published about public roads, but most toll road operators do publish data on a regular basis. So I thought I’d take a look..

Traffic growth on roads with regular data

The first chart shows the relative growth in traffic volumes on several toll roads in Melbourne, Sydney and Brisbane (where regular data is published) since 2006:

You’ll probably need to click to zoom in to see all the detail (sorry the chart is a bit cluttered).

Another way of looking at this data is to consider rolling year on year traffic growth:

Some observations:

• Most roads had a decline in traffic growth during 2008-09 (probably due to the GFC), rebounded in 2010 (except Sydney’s M4, where tolling ceased in 2010), and then growth declined again in 2011 (possibly due to economic slowdown).
• Growth has been much faster on non-radial roads. This might reflect the creation of new demand corridors as these roads provided significantly better links to the established road networks. But it also might reflect the low base from which the traffic volumes grow on these road. The high growth roads are:
  • Melbourne’s Eastlink, which runs north-south in the outer Eastern suburbs (I have set 2008Q4 as the baseline for Eastlink as it wasn’t open in 2006).
  • Brisbane’s Gateway and Logan Extension Motorways, most of which is an east-west freeway in the southern suburbs.
  • Sydney’s Westlink M7, which mostly runs north-south in the western suburbs.
• Melbourne’s CityLink saw dramatic growth in traffic in 2010, rebounding from a period of extensive road works (contributing to a decline in use in 2009). This growth eased off in 2011, perhaps returning to a 3% growth trend(?). The road upgrade appears to have had an impact on train patronage – refer another post.
• Traffic volumes on Sydney’s M2 declined in late 2011 (probably due to major roadworks).

Unfortunately data isn’t always readily available:

• The Brisbane Gateway Bridge and Logan/Gateway Motorway extension data is only available for financial years in annual reports up until 2010. A 2011 annual report has not published on their website last time I checked.
• In October 2011, Horizon Roads purchased Melbourne’s Eastlink, and they do not seem to be publishing traffic volumes.

Note also that less than 2 years of data is available for Clem7 and the Lane Cove tunnel making trend analysis difficult at this point.

Traffic growth on other toll roads

Sydney Harbour Bridge and Tunnel

RTA report data on traffic volumes every three years (in theory), but unfortunately the last published data is for 2005. However (as is often the case) some data was incidentally published about traffic volumes in 2008 and 2009 (close to, but not quite calendar years) following the implementation of time-based tolling.

I have plotted these on the following chart:

The Sydney Harbour Tunnel opened in 1992, and you can see total traffic volumes grew rapidly in the mid 1990s, before stabilising around 2002 (perhaps because capacity was reached).

Note that the 2008 and 2009 data points are twice the average weekday southbound traffic volumes. The true average all-week two-way traffic volume might be lower when weekends are taken into account, but might be higher if people make circular trips only crossing the harbour bridge/tunnel in the (free) northbound direction.

Sydney Cross City Tunnel

While there isn’t regularly published traffic data published that I can find, a 2006 NSW Auditor General’s report contains some traffic volume data for 2005 and 2006, reproduced here (from page 32 of the report).

It would appear that motorists are highly sensitive to toll pricing.

Brisbane’s Clem7 cross city tunnel

Brisbane’s first new road tunnel, the Clem7, opened in March 2010. During the first three weeks of toll-free operation, there was an average of 59,109 vehicles per day. During the first week of tolling, this fell to 20,602. The forecast was for initial traffic of around 60,000 vehicles per day, rising to 100,000 within 18 months.

Rivercity Motorways have gone to the extraordinary step of publishing daily traffic data, as can be seen in the following chart showing traffic volumes since tolling commenced:

You can see an uptick from the beginning of July 2010, when toll prices were cut. Tolls were raised in November 2010 and again in April 2011 and you can see corresponding drops in traffic volumes (suggesting a strong price elasticity effect). Average daily traffic in calendar 2011 was 10% lower than for the first 12 months of operation (includes one overlapping quarter).

During the 2011 flood crisis tolls were waived for one week, and at the end of that period on Monday 17 January 2011, 40,566 vehicles were recorded, the highest since tolling commenced. This may or may not have also reflected closures to other roads making Clem7 more attractive.

(footnote: actual weekend volumes have not been published for April 2010, so I have substituted the average non-workday figures, that have been published).

According to Wikipedia, this covers all major toll roads in Australia in operation at the time of writing. I’ll try to update these figures periodically.

Eastlink volumes compared to forecast

The following chart shows that Eastlink actual traffic volumes have been fairly consistently around 60-65% of original (2004) forecast since tolling began. It suggests the forecasts were good at estimating the ramp-up shape, but not so much the overall traffic volumes!

Note: ConnectEast issued revised forecasts in August 2009, including that (steady state annual) average daily trips in 2011 would be 209,900. That forecast doesn’t appear to have been realised either. Unfortunately data reporting stopped in October 2011 following the sale to Horizon Roads.

Maps of toll roads:

Brisbane Motorways

Sydney Motorways

Melbourne Citylink, Eastlink

Other sources of traffic volume data

See another post on Melbourne traffic volumes.

Some interesting recent data on Brisbane traffic volumes is in this report prepared for RiverCity Motorways (who operate the new Clem7). It shows many major roads in Brisbane with stable or declining traffic volumes (possibly because they are at capacity, or possibly because of a mode shift to public transport).

Patronage is growing strongly in Perth, Melbourne and Auckland. South East Queensland has possibly stalled, although issues in patronage estimation methodology may be masking underlying growth. Adelaide and Wellington are showing more modest growth, while Sydney, Canberra and Hobart continue to be laggards. Christchurch patronage unfortunately collapsed following the terrible earthquake.

For all the details, as well as some 110 year trends in Australian public transport patronage, read the updated post.

In other news, this blog is now available at the easier to remember address chartingtransport.com and there is a new public twitter stream if you want to track updates that way.

In August 2011, BITRE published revised estimates of vehicle kms in Australia (Report 124), derived from fuel sales data (using with fleet/fuel mix and fuel intensities etc).

How are we tracking with forecast traffic volumes?

I don’t have access to the complex model BITRE used to forecast congestion costs, but vehicle kilometres is an obvious major driver of congestion costs, and it is easy to compare the 2007 forecast (Working Paper 71) of vehicle kms in major cities with the most recent estimates of actuals (Report 124):

Consistent with other evidence, the growth in vehicle kilometres appears to be significantly below forecast. In 2007, BITRE assumed that city travel growth would fall to population growth rates, and that mode shares of travel would remain static. They also assumed world oil prices would peak at around US$65 in 2008 and drop to the low US$50s by 2011 (in 2004 dollars). None of these assumptions have played out in reality.

When looking at the components of the vehicle km estimates, the estimated actuals (in Report 124) for 2009-10 appear to be 15% lower than forecasts for cars and light commercial vehicles. For trucks, the 2009-10 estimated actual is around 8% lower than forecast.

To be fair, there was little evidence of the emerging mode shifts available at the time. That said, a BITRE forecast presented at ATRF in September 2011 showed a return to business as usual upwards growth, despite the last 6 years showing little growth.

What cost of congestion might we have avoided?

The relationship between travel volume and congestion costs is not linear. It is usually conceptually represented as an exponential curve. That is, a small reduction in traffic volumes will have a large impact on congestion costs (as evidenced each school holiday period where a claimed 5% reduction in traffic volumes has a significant impact on congestion levels).

While I am not equipped to do a robust calculation, the recent shift away from private car motoring is probably having a significant impact on the avoidable costs of congestion. Estimated actual capital city vehicle kms in 2010 (117.9 billion km) were just under the forecast for 2004 (118.2 billion km). The estimated cost of congestion for forecast 2004 vehicle km levels was $9.1b, while it 2010 it was forecast to be $12.9b. Road capacity has been increased in most cities between 2004 and 2010, which would reduce congestion costs for the same traffic volume, so the difference in 2010 between actual and forecast avoidable congestion costs might be in the order of around $3 billion.

So what is happening with vehicle kms per capita?

In another post, I used BITRE yearbook data on motorised passenger kms per capita. BITRE Report 124 only includes figures on vehicle (not passenger) kms, but they are still interesting figures.

And in response to requests from across the Tasman, I’ve added New Zealand’s one “big” city Auckland (data for ‘Auckland Region’ from their Transport Indicator Monitoring Framework, accessed October 2011).

Total vehicle kms per capita appear to be trending down in all Australian cities since around 2004/2005, with the sharpest drop in Melbourne in 2008-09. Auckland appears to be showing no such trend, with perhaps a flattening at best since 2005-06 (the vehicle km data is marked as under review, as is the public transport data which shows patronage growth of 25% in the four years to 2009-10).

Comparing values for different cities requires caution. The physical size of the urbanised area, and the administrative boundaries used to define cities will have an impact. For example, Adelaide shows up with lower vehicle kms per capita than Melbourne, even though it has much lower public transport mode share. The Adelaide urban area has a smaller footprint and is more constrained than Melbourne, which might explain this difference.

Car vehicle kms per capita appear to have peaked in either 2003-04 or 2004-05 in the five big cities, with Melbourne showing the biggest decline (a 14% decline since 2004-05).

The last two charts showed financial year estimates, but data is actually available at a quarterly level. I’ve created the following chart using simple interpolation of June estimates of residential population for each of the large Australian cities:

The underlying fuel data was actually seasonally adjusted, but there still appears to be some noise in the data (or the world may just be that variable, but I doubt it).

Vehicle use outside the big cities

What about traffic volumes in the rest of Australia? I’ve extracted the five big cities (Sydney, Melbourne, Brisbane, Perth and Adelaide) from the remainder:

The reduction in vehicle use does not appear to be limited to the big cities (most of which have seen strong growth in public transport). The trends for car km per capita outside the five cities are no different to overall vehicle use.

I should note: the report does not actually specify how vehicle kms for each state were split between capital city and other areas (section 8.2, citing unpublished data), but the fractions used were published.

What about total vehicle kms in cities?

While I like to look at per capita transport usage (everything is relative), it is instructive to look at trends in total volume as well. They provide some input into whether increased road capacity might be required, for example.

This charts shows that total vehicle kms in Melbourne, Sydney and Adelaide have been relatively flat since around 2004, while Auckland, Perth and Brisbane have shown continued growth. Perth and Brisbane show a downturn only in more recent times, but have had several years of declining vehicle kms per capita, the difference probably explained by stronger population growth.

How do BITRE Melbourne figures compare with VicRoads’ data?

Here is a chart comparing vehicle km index values for Melbourne from BITRE report 124, and an index created from annual growth figures reported in VicRoads Traffic Systems Performance Monitoring reports (with fully revised history):

A significant gap opens around 2003-04, but this substantially closes from 2008-09. Both datasets show a stabilisation of total traffic volumes, with BITRE data stabilising one year later than for VicRoads. BITRE aimed to estimate total metropolitan traffic, while the VicRoads figures are based on a defined set of monitored roads that might not reflect total traffic, particularly in growth areas on the fringe.

(Note: I did a similar comparison of VicRoads data to BITRE Working Paper 71 estimates of actuals in an earlier post).

In conclusion

• There is strong evidence that “business-as-usual” growth in vehicle kms is just not happening in Australian cities, and thus the 2007 forecast doubling of congestion costs by 2020 is very unlikely to play out.
• The dampened growth in travel demand is probably saving the economy a few billion in avoidable congestion costs, and has implications on the need for multi-billion dollar expansions of road capacity (though changes in demand will not be uniform across road networks).
• I’d also suggest it is important that planners and policy makers understand why travel demand trends have changed so significantly, and apply this understanding to forecasts of future demand.

Following a suggestion in the comments on my last post about car ownership, this post takes a detailed look at car/vehicle occupancy.

What are the trends in car occupancy? (direct measures)

Many state road agencies make direct and regular measurements of vehicle occupancy in capital cities and their data is collated by AustRoads.

Unfortunately only four cities report such data to AustRoads. Brisbane data has several missing years – and the three most recent years’ figures reported are all identical, so I’m inclined not to plot them. That leaves Melbourne, Sydney and Adelaide.

Firstly, all day (weekday) average occupancy:

There doesn’t appear to be much in the way of clear trends as the data seems quite noisy (I’m not sure anyone could explain the year by year variations). Perhaps Melbourne average all day occupancy is trending down?

Data is available for three sub-periods:

Again lots of noise, but maybe a downwards trend in Melbourne.

Noisy again. Possible downwards trend in Melbourne.

This data is remarkably flat for Sydney, while Melbourne again appears to be trending down.

It’s little surprise that AM peak has the lowest occupancy, as it is dominated by journeys to work. More on that soon.

What about trends on different road types?

Looking at Melbourne data in more detail, car occupancy appears to have declined most on freeways and divided arterials:

On freeways, the decline is most evident during business hours:

Notes on the AustRoads/VicRoads data:

Along with the noise in the data, there is some ambiguity in the methodology. The AustRoads website reports “car” occupancy, but the methodology doesn’t seem to filter for cars. Are buses included or not? It says the survey should be undertaken in March/April to avoid school and public holidays. But March and April have heaps of holidays (Easter, Anzac Day and Labour Day in many states).

But the AustRoads data is certainly collected on representative arterial roads, where you might expect lower occupancy because of longer trips that are more likely to be work-related.

What are the trends in car occupancy? (derived measures)

Car occupancy can also be measured as the ratio of car passenger kms to car vehicle kms.

BITRE provide estimates of both, but only for all passenger vehicles in Australia. The long-running Sydney Household Travel Survey provides estimates of both for Sydney. here’s what they look like:

The BITRE figures show a fairly smooth and slow downwards trend from 1.62 in 1990 to 1.59 in 2009. The Sydney figures are a little more noisy, but also show a slight decline – from 1.37 in 1999 to 1.35 in 2010. Presumably non-urban car trips have much higher car occupancy as there’s quite a difference between 1.59 and 1.35.

The Melbourne (VISTA) 2007-08 household travel survey nets an average car occupancy of 1.43 – that being the average over all car kms for trips by residents of the Melbourne Statistical Division (SD) that start and finish within the Melbourne SD. Include trips outside the Melbourne SD and you get 1.49. You could measure it a number of different ways.

The census journey to work question gathers data on how people travelled to work, including car drivers and car passengers. While not a clean measure, it is possible to calculate an implied car occupancy as (car drivers + car passengers) / (car drivers). For the purposes of this calculation, I have only taken “car driver only” and “car passenger only” trips (which excludes park-and-ride and kiss-and-ride public transport trips). I do not have data on trip lengths, and average car passenger trips might be different on average to car driver trips.

There’s a pretty clear downwards trend as fewer people travel to work as passengers. In fact, the data suggests extremely low levels of car pooling., and that over 90% of car journeys to work have no passengers in most cities.

So in summary, there is evidence of gradual declines in car occupancy for all travel, and strong evidence of a decline in car occupancy on the journey to work.

What’s the relationship between car ownership and car occupancy?

You might expect car occupancy to go down as car ownership goes up. In other words: we have more cars and need to share them less.

Here’s what the relationship looks like for Australia as a whole (using car occupancy derived from BITRE data):

There are four quite different periods:

• From 1993 to 1999 (bottom right) car occupancy declined as car ownership increased. As you might expect.
• From 1999 to 2001 car ownership stalled, but car occupancy continued to decline.
• From 2001 to 2005 car ownership rose again, but car occupancy declined more slowly.
• From 2005 to 2010 car occupancy increased slightly, while car ownership had slow growth. This is the period when public transport mode shift took hold in most Australian cities.

The relationship is changing, probably influenced by other factors. BUT it could also be that I’m reading too much into the precision of the car occupancy figures – we are talking about variations in the fourth significant figure only for the last few years. The BITRE figures are estimates themselves. Maybe someone from BITRE would care to comment on the precision?

What about different road types?

Here is a chart showing VicRoads’ 2009/10 car occupancy figures for arterial roads in Melbourne:

You can see car occupancy lowest on freeways, and highest on undivided arterials with trams (all in the inner suburbs). Otherwise very little difference (in 2009/10 at least).

How do Australian cities compare?

To try to take out some of the noise, I’ll take the average of the last four years for the AustRoads data and Sydney and Melbourne household travel survey data:

Melbourne appears to have the lowest occupancy, and Sydney the highest – except when it comes to household travel survey data where Melbourne is much higher. But this might just be differences in methodologies between states.

Factors influencing car/vehicle occupancy (in Melbourne)

Having access to the 2007-08 VISTA data, it’s possible to disaggregate vehicle occupancy on almost any dimension you can imagine. I’ll try to restrict myself to the more interesting dimensions!

For most charts I have used vehicle occupancy rather than car occupancy. Cars and 4WD/SUVs combined accounted for 88% of vehicle kms in the dataset so there shouldn’t be a lot of difference. But I’ll start with looking at..

Vehicle type

Now that’s a surprise: 4WD/SUVs have a much higher average occupancy than cars. Why is that?

Are they used for different purposes?

Not a great deal of difference between cars and 4WD/SUVs, although 4WD/SUVs are slightly more commonly used to pick up or drop off someone.

More likely explanations (from the data) are:

• 4WD/SUV come from larger households on average (3.5 people v 3.1 for cars).
• 4WD/SUVs are also more likely than cars to belong to households that are couples with kids.

Day of the week

Probably not a huge surprise that cars have less occupants on weekdays than weekends. Male drivers are much more likely to have no passengers on weekdays, but an average of one passenger on weekends. Whereas there is much less variation for females.

Is this traditional gender roles in the family? (There is a chart to answer almost any question you know..)

There you go: dads much more likely to drive the family around on weekends, and mums more likely to drive them around on weekdays. And while on the subject…

Household types and sizes

Little surprise that car occupancy increases with household size. It is easier to car pool when you have the same origin.

Note that the sample size of one parent households of size 5 are small (especially for male drivers). But curiously single mothers have much higher occupancies than single fathers.

There is also a small sample of other household structures with 5 people.

Unsurprisingly, people living alone are likely to have the lowest car occupancies. With increasingly prevalence of sole person households, you might expect continuing declines in average car occupancy.

Trip purpose

Again work trips are the least likely to involve passengers, particularly on weekdays (average occupancy 1.07). Driven trips to education are not far behind. Little surprise that accompanying someone, or picking up or dropping off someone averages around 2 or more. Occupancies for personal business, shopping, recreational and social trips are in the middle, but much higher on weekends when householders are probably more likely to travel together to common destinations.

Many people would argue that demand for public transport is lower on the weekend. These figures would support that argument, but lower weekend patronage would also reflect lower service levels.

Note: the sample sizes of weekend education and accompanying someone trips were too small to be meaningful so I left them off.

Time of day

[Note: this chart was corrected on 21/8/2011]

There you go, car occupancy peaks between 8 and 9am and between 3 and 4 pm on school days: parents driving kids to/from school.

But vehicle occupancy is highest on Saturday nights when people are socialising, and interestingly Sundays are well above Saturdays (less personal business on Sundays perhaps?). Non-school weekdays have higher occupancies than school weekdays, possibly with parents also taking time off work and spending time with kids.

Just looking at the school peak more closely, here is a chart showing car driver trip purposes by hour of the day on school weekdays. You’ll almost certainly have to click on this one to read the detail.

The most frightening statistics are in the school peaks. A staggering 40% of car trips between 8 and 9am, and 42% of car trips between 3 and 4pm are to pick up or drop off someone (suggesting a fault in the reported vehicle occupancy for trips picking up somebody). This will almost certainly be dominated by school children. No wonder traffic congestion eases so much in school holidays.

That said, car trips to/from school are shorter than other trip types (as we saw in an earlier post). The data suggests 19% of car kilometres of trips starting between 8-9am are to pick-up/drop-off someone, and for 3-4pm the figure is 24%. That’s still a sizeable chunk of total road traffic. It suggests there are huge congestion relief benefits to be had in getting kids to walk, ride or use public transport to/from school.

Geography

There’s not a lot of difference other than for the inner city, where school day occupancies are lower. For someone in the inner city to drive a car, they are probably heading out of the city and any other members of their household might be less likely to have the same destination and/or would have good public transport options for their travel.

The non-school weekday figures show some variation, and while the sample sizes are all over 250, there are some vehicles with an occupancy of 14 recorded. unfortunately because the underlying data is discrete, medians aren’t an easy way around this issue.

Age

This would suggest traditional gender roles are in play: Average car occupancy is highest for drivers aged 30-45, the most common age groups for parents of pre-driving aged children. And women seem to be doing more ferrying of the kids than men.  In the older age groups men are more likely to be driving with passengers.

Income

Vehicle occupancy seems to go down as we have higher incomes (moreso for females), but there seems to be some noise in the data (eg the spike at 3000 is due to one vehicle with 12 occupants). Females with lower household incomes have higher vehicle occupancies (maybe those without an income but looking after a family).

This trend reflects the fact that car/vehicle ownership goes up as wealth goes up:

The threshold for car ownership is around $1250 per week (equivalised to a single occupant household). As Australians have become increasingly wealthy in real terms, we can afford to own more cars.

Trip distance

While there is probably a little noise in this data, there is a fairly clear pattern. Very short trips and very long trips are likely to have higher occupancies. The median trip distance for non-work trips is around 4kms, while work trips are much longer, which fits with the average occupancies for different trip purposes.

In fact, here is a mode share breakdown by trip distance (for trip legs):

You can see car passenger becomes more common for very long trips (note the X axis scale is not uniform). (Don’t ask me why driving is so popular for distances of 16-16.9 kms! It’s probably a bit of noise)

And if you look at the trip purposes of these very long trips, you’ll longer trips are more likely to be social or personal business:

(note: this chart is by trips, and not trip legs)

Main Activity

Probably little surprise that those “keeping house” have the highest occupancy in general, but that full-time workers have very low occupancy on weekdays, but very high occupancy on weekends.

There you go, possibly more than you ever wanted or needed to know about vehicle occupancy!

Firstly, by car ownership rate I mean the ratio of the number of registered “passenger vehicles” (from the ABS Motor Vehicle Census) to population (also from ABS). Of course some of these cars are owned by companies and not garaged at households, but the data is what it is.

When looking over the last 23 years, it is no surprise to see car ownership rates in Australia have risen considerably:

(click on the chart for a less blurry version)

What is interesting in this chart is the relative rate of car ownership between states and territories. The Northern Territory is consistently the lowest – I’m guessing related to the relatively large indigenous population. I’m not sure for the reasons for other differences. It may be the percentage of the population that is in big cities and the car mode share of those cities. It might also be slight differences in reporting from the state agencies (see ABS’s explanatory notes).

But what about the most recent trends? Here is the same data zoomed in to the last 8 years:

It appears car ownership has more or less levelled-out in a few states:

• Victoria, between 2006 and 2010
• Western Australia, from 2007 onwards
• Queensland, from 2008 onwards (it has actually declined very slightly)

This is fairly consistent with other evidence about declining car use and mode shift to public transport in Australia’s cities.

And the overall rate for Australia appears to have levelled out between 2008 and 2010.

Are cars getting cheaper?

Certainly motor vehicles have been getting cheaper in real terms since around 1996 (relative to overall CPI). They’ve also actually been getting cheaper in nominal dollar terms since 1995.

You might have thought increasing affordability was a strong driver of car ownership rates, but it doesn’t explain growth in car ownership pre 1995, or the slowing of car ownership rates around 2008.

What about usage of each car?

Using data from the BITRE 2011 yearbook, it is possible to calculate an estimated annual kms per passenger car. For this I’m comparing the number of vehicles at the motor vehicle census date with an estimate of total car kms in the previous 12 months (straight line interpolation of BITRE year ending June figures). This isn’t a perfect measure as the number of cars grows throughout the 12 month period where kms are taken, but it is still a guide to the trend.

That’s a pretty clear downwards trend, particularly in recent years.

What might explain this?

• From 1995 to 2005 cars have become more affordable and so we can own more cars and need to share them less.
• From 2005 to 2010 car ownership rates have slowed and we are driving cars less as we travel less and/or shift to other modes.

What about car ownership in cities?

The data available on the ABS website is only available at the state and postcode level (and at postcode level only for recent years). However with some GIS calculations I’ve been able to come up with an estimate of the number of passenger cars with an owner address within the Melbourne Statistical Division (postcode boundaries sometimes do not perfectly align with the Melbourne SD boundary on the fringe, but this is fairly minor and mostly in rural postcodes).

Here is a chart comparing Melbourne, Victoria, and Australia:

So after quite a bit of work extracting and processing all the data, I’ve found very little difference between the Melbourne and Victoria rates or trends. Which does seem a little odd given it is probably easier to live without a car in Melbourne than the rest of the state. It might be that there are many cars with an ownership address in Melbourne, but garaged outside Melbourne. I’m not sure (anyone know more?).

I have covered the spatial variations of car ownership in Melbourne in another post.

What about motorcycles?

Are more people owning motorcycles instead of cars?

You can see motorcycle ownership rates have grown significantly since around 2004 (although still very small).

Does it explain the slowdown in the car ownership rate?

This chart still shows a slow-down after 2008, so it doesn’t look like rising motorcycle ownership explains the car ownership slow-down. Motorcycle ownership took off in 2004, but car ownership slowed in 2008.

What about the ageing population?

Could the data be impacted by a changing age profile? Very old people are probably less likely to drive and hence own a car, so maybe this would lead to a declining car ownership rate per head of population as a greater portion of the population is older.

Suppose most car owners are aged 18 to 80 years. Here’s the percentage of Australia’s population within that age band:

The share has been very steady at around 73 to 74% for all of the last 16 years, which suggests little impact on overall car ownership rates.

Then again, those aged 80 today might be healthier and/or wealthier and more likely to own cars that those aged 80 in 1994. In that case, the rate of car ownership of younger people would have seen less growth, but this is purely speculation and I’m not aware of any available data that could enable a test of this hypothesis.

Notes on the data:

• The ABS Motor Vehicle Census has been taken in different months in different years. State population estimates are only available on a quarterly basis. I have used the nearest quarterly population figure for each motor vehicle census where they do not align (never more than one month out).
• Melbourne population estimates are only available at June each year. I have used straight line interpolation of passenger car figures to produce a June estimate of passenger cars per capita for each year (same as for annual car kms).

Or per capita growth:

I think those charts mostly speak for themselves.

(For the record, the five biggest cities are Sydney, Melbourne, Brisbane, Perth, and Adelaide)

By popular demand, here are charts for each city (plus Canberra):

Note:

• These charts have very different scales on the Y axis. Compare with caution.
• Canberra public transport passenger km (actually just bus passenger kms) is reported as “0.25″ billion passenger kms for five straight years, hence the straight green line.
• While I haven’t drawn the second set of charts for each city, in all cities, car passenger kms per capita have reduced (red lines below blue lines). Public tranpsort passenger kms per capita have increased in all cities except Canberra.