What’s driving Melbourne public transport patronage?

Fri 11 May, 2012

[Updated June 2012 to include ratios over time, inner city parking, and other updated data. First posted January 2010]

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 informed 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

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. Here’s the ratio of patronage to population for all of Melbourne:

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 charts compare 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, but still not very strong.

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.

Here is the relationship shown as a ratio over time:

ABS publish figures monthly, and here’s the picture for total persons employed in Melbourne. There was virtually no growth between late 2010 and May 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 inner city (where it has the highest destination mode share), then if more people need to travel to the inner city, 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.

The next chart shows the same relationship as a ratio over time. The 2006 anomaly is much less noticeable (note not a huge variation in weekday daytime population the chart above). This suggests that City of Melbourne weekday daytime population is not directly proportional to public transport patronage (in other words: the y-intercept is not zero).

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.

Here’s the same relationship expressed as a ratio over time. The ratio is remarkably flat over time.

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).

Here’s the same relationship as a ratio over time, which is a little flatter:

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.

Here it is as a ratio over time, which is not entirely flat:

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.

Inner city parking

A commenter on this blog suggested I look at parking in the inner city. The following chart looks at public transport patronage and total commercial parking spaces the CBD, Southbank, Docklands and East Melbourne.

Between 2004 and 2006, commercial parking spaces grew strongly, while public transport patronage did not. Then public transport patronage grew strongly and there was actually a decline in the number of commercial parking spaces.

I would expect the price of parking to be a stronger driver of public transport use than the capacity available. Unfortunately I do not have a long enough time series of parking prices to test this hypothesis. See also my post on the Melbourne CBD.

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.

Here’s a chart showing the ratio of patronage to service kms for all modes:

This chart shows increasing intensity of use of trains and trams between 2004 and 2009, while buses have remained around 1.0-1.1 boardings per service km for at least 12 years running. The significant difference between trams and buses is best explained by the territory covered: trams mostly the CBD, buses mostly not the CBD.

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 rates, 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.

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 inner city.

But international students, radial motorway traffic 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.


Questioning assumptions about transport trends (presentation to Transport Economics Forum)

Wed 21 March, 2012

On Tuesday 20 March 2012 I gave this presentation to the Transport Economics Forum in Melbourne using material from this blog and some recently released data in BITRE’s Working Paper 127 on traffic growth in Australia. The presentation challenges some orthodox assumptions about transport trends in Australia and Melbourne.

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


Traffic volumes on Australian toll roads

Sat 3 March, 2012

[Fully revised March 2020]

What are the trends in traffic volumes on major toll roads in Australian cities? How sensitive are motorists to toll prices? How accurate have traffic forecasts been? Are traffic volumes on toll roads growing faster than traffic in general?

This post aims to shed some light on these questions.

I have sourced traffic data from various sources, including Transurban ASX releases, annual reports, Transport for NSW, operator websites and media reports (I cannot guarantee error-free data gathering).

Average daily volumes

Firstly, here is a chart showing the average daily volumes for toll roads where I have been able to obtain data. Note that I have used a log scale on the Y-axis. The label includes the most recent volume figure available. For some roads and time periods only report annual figures are available (shown as dots rather than lines).

Interact with this data in Tableau.

How have growth rates changed over time?

The following charts show traffic volume growth since an early reference year, compared to BITRE estimates of total vehicle kms for each city:

Citylink volumes grew faster than general traffic for the first decade, but has been more in line with general traffic since then. You can see there are periods of suppressed demand, which very likely correlate with periods of major roadworks. After each period of roadworks, traffic volumes have rebounded strongly and shown further growth (probably eroding congestion reduction benefits). The underlying rate of growth appears to be declining.

It’s a little more difficult to construct a chart for Sydney as different lengths of history are available for different roads. I’ve anchored the chart at 2011:

Most toll roads have had traffic growing faster than general traffic in Sydney. Westlink M7 and Hills M2 have had the highest growth since 2011, with the M1 Eastern Distributor showing the least growth. You can see declines on the Hills M2 and M5 (presumably during roadworks) followed by significant growth as capacity was made available.

Not all of Brisbane’s toll roads have growth faster than overall traffic. Transurban report that AirportLink and Clem7 volumes have recently been impacted by upgrades on the Gateway motorway.

An important note on growth rate precision: Transurban report daily traffic volumes rounded to the nearest thousand. For roads with relatively small volumes (eg Clem7), the growth rates will be more impacted by rounding errors. For example, the traffic volumes on Clem7 went from 27+26+27+27=107 thousand in 2014/15 to 27+26+26+27=106 thousand in 2015/16, which is notional growth of -0.9%. But actual values for each quarter will be within +/-500, and the rounding errors will add up over the eight quarters making up the calculation. The actual growth could be anywhere between -4.6% and 2.9%, but is more likely to be in the middle of that range.

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. Transurban took over these roads and have reported traffic volumes since 2013 but they do not appear to be comparable measures so I have listed them separately.
  • In October 2011, Horizon Roads purchased Melbourne’s Eastlink, and they do not seem to be publishing traffic volumes.
  • I haven’t been able to source Clem7 data for 2012 and the first half of 2013.

Traffic growth on other toll roads

Sydney Harbour Bridge and Tunnel

Calum Hutcheson from Hyder Consulting has generously compiled and shared time-series data with me on traffic volumes going back to 1971 for these two toll roads. He has sourced data from several available sources but has had to estimate some figures where data is missing.

Sydney Harbour Traffic 2

Traffic volumes levelled off on the bridge around 1988 and on the combined bridge and tunnel around 2005. It would appear the tunnel brought additional vehicle capacity good for around 17 years’ growth but that has now been exhausted (although I’m far from an expert in Sydney traffic). Traffic volumes on the tunnel have barely growth since 2010.

In 1992 one southbound lane of the bridge was converted to a bus lane (presumably related to the capacity freed up by the tunnel). The bridge’s vehicular traffic levels have not returned to 1988 levels, but I suspect the number of people moved in (road-based) vehicles has increased significantly (not to mention the train line across the bridge).

Sydney Cross City Tunnel

The Cross City Tunnel was forecast to carry 87,088 vehicles per day in 2006, but in 2019 was still less than half this amount.

I have not been able to source much data pre-2013, but 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, and the forecast volumes were not achieved even when tolls were removed.

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. Owners at the time, Rivercity Motorways, went 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 up-tick 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. 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).

Traffic volumes on the Clem7 peaked at 30,000 in 2018, less than a third of the forecast for the year 2010.

Brisbane’s Airportlink

This toll road was forecast to attract 135,000 vehicles per day one month into operations, and have 165,000 vehicles per day after the ramp up period. Volumes in 2019 were around 63,000 – less than half the forecast after ramp up.

AirportLink traffic

The traffic volumes declined as tolls were progressively introduced to all traffic. BrisConnections, the owner of the road, went into voluntary administration in February 2013.

The Clem7 and Airportlink roads are the first two major tollways as part of the TransApex plan for adding major road capacity to Brisbane.

The third piece of this puzzle is the Go Between Bridge, now part-owned by Transurban and they report a flat 11,000 vehicles per day as of 2019. The forecast was for 17,500 by 2011 and 21,000 by 2021.

I’m guessing it may be a very long time before these TransApex roads reach capacity.

Eastlink

The following chart shows that Eastlink actual traffic volumes were fairly consistently around 60-65% of original (2004) forecast after 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 Australian Toll Roads

Here are some rough Google maps: Melbourne Sydney Brisbane.
Maps and more information about many of the roads is also available on the Transurban website.

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 operated the 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).

New South Wales traffic data is available for selected locations, as well as detailed data for toll roads.

Victorian data for non-tolled roads is available here, but unfortunately does not include time series history.


Are congestion costs going to double? An analysis of vehicle kms in Australian cities

Tue 25 October, 2011

A frequently cited forecast is that the avoidable costs of congestion in Australia will double in most Australian cities between 2005 and 2020. These BITRE forecasts were published in 2007 (Working Paper 71), assuming continued strong growth in vehicle kms in our cities (“business-as-usual” conditions). But as this blog has demonstrated several times, transport trends have not been business-as-usual in recent years.

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.
I’d like to acknowledge BITRE for conducting the excellent work that went into Report 124 and making the data publicly available, without which this analysis would not have been possible.