What impact has the 2020 COVID-19 pandemic had on road traffic volumes in Victoria?

Sun 3 May, 2020

[Last updated 2 June 2020]

Roads in Victoria have been noticeably quieter during the pandemic, but just how much has traffic reduced? Has it varied by day of the week, time of day, and/or distance from the city centre? How have volumes increased as restrictions have been eased?

To answer these questions I’ve downloaded traffic signal loop vehicle count data from data.vic.gov.au. The data includes vehicle detection loops at 3,760 signalised intersections across Victoria (87% of which are in Greater Melbourne).

I should state that it is not a perfect measure of traffic volume:

  • It may under-count motorway-based and rural travel which may cross fewer loop detectors.
  • There are occasional faults with loops, and I’m only able to filter out some of the faulty data (supplied with negative count values), so there is a little noise but I will attempt to wash that out by using median counts rather than sums or averages (although charts of averages show very similar patterns to charts of medians).
  • Some vehicles moving through an intersection might get counted at multiple loops, but I would hope this has minimal impact on overall traffic volume trends.

How have traffic volumes reduced during the pandemic?

Firstly, median 24-hour loop volumes for each day:

Note: the actual numbers aren’t very meaningful, it is the relative numbers that matter. Unfortunately at the time of updating, data for some dates was missing (or clearly erroneous so I have excluded it).

Traffic volumes declined over the second half of March 2020, as more restrictions were introduced, students stopped attending schools and universities, and workers were asked to work from home if possible.

School holidays started early (on Tuesday 24 March) although many students stayed home in the last days of term. School resumed on Wednesday 15 April with most students remote learning at home.

The first official easing of restrictions took effect from Wednesday 13 May (week 20) allowing some social gatherings and this has seen some significant traffic growth (although it appears traffic volumes were already slowly increasing before that date).

There are variances by day type and by week, so here is a chart looking changes by day of the week, relative to the first two weeks of March 2020:

At their lowest, weekday volumes went down around 40%, while weekend volumes went down more like 50%.

In late-May volumes were down more like 16-20%, with significant growth on weekends.

A curious outlier is Thursday in the week of 5 April – this was Thursday before Good Friday, so there may have been some travel to holiday homes, or other travel that happens normally on a Friday being the end of the working week.

However we should be careful because there is some underlying seasonality in traffic volumes, as well as week-to-week variations (perhaps impacted by events and/or weather). Here is a chart comparing 2020 with 2019 for weekdays, Saturdays and Sundays (excluding public holidays):

The next chart compares each 2020 week with the same week 2019, although it is important to note that there was quite a bit of week to week variation in 2019:

On this measure, weekdays were down around 38% on 2019, but have recovered to be ~17% down in week 22. Weekends were down around 50%, but Saturday 16 May was only ~22% down on the equivalent Saturday in 2019. Sundays had recovered to be only ~23% down on 2019 in week 21.

How has traffic reduced by time of day?

The traffic signal data is presented in 15 minute intervals, generating huge amounts of detailed data (more than I could load into Tableau Public which has a limit of 15 million records). I’ve managed to load data for most days of the week for March and April 2020.

Here’s a look at the traffic volumes by time of day for Wednesdays:

You can see a significant flattening of the traditional peaks from late March, although curiously the PM peak still commences around 3 pm, even during the school holidays.

Evening traffic was down considerably but it’s a little hard to gauge this reduction the chart. So here is a chart showing traffic volume changes relative to the first week of March:

Volumes were down the most in the evenings (particularly around 9 pm) which might reflect the closure of hospitality venues, cessation of sports and reduced social activity. The AM and PM peak periods are down around 50%, while the inter-peak period has held up the most – being only down around 30%.

I should point out that this analysis compares to a baseline of a single day, and there may be some associated noise (eg weather or event impacts on particular days).

Here is the same for Fridays:

10 April was Good Friday, hence much quieter traffic with retail trading restrictions.

Late evening traffic is down even more than for Wednesdays, which probably reflects higher volumes of hospitality-related travel on Friday nights.

Here is Saturdays:

The Saturday profile shape hasn’t changed as much as weekdays, but the evenings are down most significantly.

25 April was the Anzac Day public holiday, and the spike in afternoon travel probably reflects retail trading restrictions that apply until 1pm.

Curiously there are several spikes in the curve in the morning – and they are the 15 minute intervals leading up to the hours of 7am, 8am, 9am, and 10am. Initially I wondered if it was a data quality issue, but perhaps they reflect a surge in travel just in time for work shifts and other activities that start on the hour.

For some reason traffic volumes were relatively low around 6 am on Saturday 7 March, which has resulted in other days showing less reduction.

Saturday night travel is down considerably – by over 70% by midnight. You can also see early Saturday morning (Friday night) travel down around 60-70%.

Here is Sundays:

Sunday 12 April was Easter Sunday, which might explain quieter traffic. Sunday 8 March was on the Labour Day long weekend (including the Moomba festival), which probably explains the much busier traffic that Sunday night (not being a “school night”). You can more clearly see that on the following chart:

One aside on this – it’s possible to compare the traffic profiles of different days of the week (sorry I had to exclude Tuesdays and Thursdays due to data volumes). Here’s the first week of March before the shutdown:

This data suggests a roughly a one hour lag on Sunday mornings compared to Saturday mornings – ie travel volumes hold up an hour later on Saturday nights and ramp up an hour later on Sunday mornings. This pattern holds up for other weeks.

Here’s another look at relative time of day traffic volumes for March and most of April:

If you look closely (no, your eyes are not losing focus!) you can see:

  • Significant reductions after schools finished on 23 March
  • A surge in traffic on 9 April – the Thursday before Good Friday
  • Extremely quiet traffic on Good Friday (10 April)
  • Generally higher traffic on the last weekday of the week, particularly in the afternoon and evening (including during the shut down period)
  • The middle of the day being busier on (pre-shutdown) Saturdays compared to weekdays.

Have traffic impacts been different by distance from the CBD?

Here’s a chart showing year-on-year reduction in median traffic volumes at intersections by distance from the Melbourne CBD for weeks 14 and 15 (the lowest two weeks of the lock-down):

What is clear is that the central city experienced much larger traffic volume reductions than other parts of Melbourne, which makes sense as office workers stayed home, universities, cafes, restaurants and night-life closed, and (non-essential) retail activity slowed considerably.

There is some noise in the variations by distance from the CBD but I suggest not too much should be read into that as there will be various local factors at play.

Here is a look at a recent week compared to the first two weeks of March 2020, showing the pattern is similar, although volumes have risen at all distances.

Traffic signal data comes out daily, and so I will try to update this analysis at least once a week during the recovery period.


Update on Australian transport trends (December 2019)

Mon 30 December, 2019

Each year, just in time for Christmas, the good folks at the Australian Bureau of Infrastructure, Transport, and Regional Economics (BITRE) publish a mountain of data in their Yearbook. This post aims to turn those numbers (and some other data sources) into useful knowledge – with a focus on vehicle kilometres travelled, passenger kilometres travelled, mode shares, car ownership, driver’s licence ownership, greenhouse gas emissions, and transport costs.

There are some interesting new patterns emerging – read on.

Vehicle kilometres travelled

According to the latest data, road transport volumes actually fell in 2018-19:

Here’s the growth by vehicle type since 1971:

Light commercial vehicle kilometres have grown the fastest, curiously followed by buses (although much of that growth was in the 1980s).

Car kilometre growth has slowed significantly since 2004, and actually went down in 2018-19 according to BITRE estimates (enough to result in a reduction in total vehicle kilometres travelled).

On a per capita basis car use peaked in 2004, with a general decline since then. Here’s the Australian trend (in grey) as well as city level estimates to 2015 (from BITRE Information Sheet 74):

Technical note: “Australia” lines in these charts represent data points for the entire country (including areas outside capital cities).

Darwin has the lowest average which might reflect the small size of the city. The blip in 1975 is related to a significant population exodus after Cyclone Tracey caused significant destruction in late 1974 (the vehicle km estimate might be on the high side).

Canberra, the most car dependent capital city, has had the highest average car kilometres per person (but it might also reflect kilometres driven by people from across the NSW border in Queanbeyan).

The Australia-wide average is higher than most cities, with areas outside capital cities probably involving longer average car journeys and certainly a higher car mode share.

Passenger kilometres travelled

Overall, here are passenger kms per capital for various modes for Australia as a whole (note the log-scale on the Y axis):

Air travel took off (pardon the pun) in the late 1980s (with a lull in 1990), car travel peaked in 2004, bus travel peaked in 1990 and has been relatively flat since, while rail has been increasing in recent years.

It’s possible to look at car passenger kilometres per capita, which takes into account car occupancy – and also includes more recent estimates up until 2018/19.

Here’s a chart showing total car passenger kms in each city:

The data shows that Melbourne has now overtaken Sydney as having the most car travel in total.

Another interesting observation is that total car travel declined in Perth, Adelaide, and Sydney in 2018-19. The Sydney result may reflect a mode shift to public transport (more on that shortly), while Perth might be impacted by economic downturn.

While car passenger kilometres per capita peaked in 2004, there were some increases until 2018 in some cities, but most cities declined in 2019. Darwin is looking like an outlier with an increase between 2015 and 2018.

BITRE also produce estimates of passenger kilometres for other modes (data available up to 2017-18 at the time of writing).

Back to cities, here is growth in rail passenger kms since 2010:

Sydney trains have seen rapid growth in the last few years, probably reflecting significant service level upgrades to provide more stations with “turn up and go” frequencies at more times of the week.

Adelaide’s rail patronage dipped in 2012, but then rebounded following completion of the first round of electrification in 2014.

Here’s a longer-term series looking at per-capita train use:

Sydney has the highest train use of all cities. You can see two big jumps in Perth following the opening of the Joondalup line in 1992 and the Mandurah line in 2007. Melbourne, Brisbane and Perth have shown declines over recent years.

Here is recent growth in (public and private) bus use:

Darwin saw a massive increase in bus use in 2014 thanks to a new nearby LNG project running staff services.

In more recent years Sydney, Canberra, and Hobart are showing rapid growth in bus patronage.

Here’s bus passenger kms per capita:

Investments in increased bus services in Melbourne and Brisbane between around 2005 and 2012 led to significant patronage growth.

Bus passenger kms per capita have been declining in most cities in recent years.

Australia-wide bus usage is surprisingly high. While public transport bus service levels and patronage would certainly be on average low outside capital cities, buses do play a large role in carrying children to school – particularly over longer distances in rural areas. The peak for bus usage in 1990 may be related to deregulation of domestic aviation, which reduced air fares by around 20%.

Melbourne has the lowest bus use of all the cities, but this likely reflects the extensive train and tram networks carrying the bulk of the public transport passenger task. Melbourne is different to every other Australian city in that trams provide most of the on-road public transport access to the CBD (with buses performing most of this function in other cities).

For completeness, here’s growth in light rail patronage:

Sydney light rail patronage increased following the Dulwich Hill extension that opened in 2014, while Adelaide patronage increased following an extension to the Adelaide Entertainment Centre in 2010.

We can sum all of the mass transit modes (I use the term “mass transit” to account for both public and private bus services):

Sydney is leading the country in mass transport use per capita and is growing strongly, while Melbourne, Brisbane, Perth have declined in recent years.

Mass transit mode share

We can also calculate mass transit mode share of motorised passenger kilometres (walking and cycling kilometres are unfortunately not estimated by BITRE):

Sydney has maintained the highest mass transit mode share, and in recent years has grown rapidly with a 3% mode shift in the three years 2016 to 2019, mostly attributable to trains. The Sydney north west Metro line opened in May 2019, so would only have a small impact on these figures.

Melbourne made significant gains between 2005 and 2009, and Perth also grew strongly 2007 to 2013.

Here’s how car and mass transit passenger kilometres have grown since car used peaked in 2004:

Mass transit use has grown much faster than car use in Australia’s three largest cities. In Sydney and Melbourne it has exceeded population growth, while in Brisbane it is more recently tracking with population growth.

Mass transit has also outpaced car use in Perth, Adelaide, and Hobart:

In Canberra, both car and mass transit use has grown much slower than population, and it is the only city where car growth has exceeded public transport growth.

Car ownership

The ABS regularly conduct a Motor Vehicle Census, and the following chart includes data up until January 2019.

Technical note: Motor Vehicle Census data (currently conducted in January each year, but previously conducted in March or October) has been interpolated to produce June estimates for each year, with the latest estimate being for June 2018.

In 2017-18 car ownership declined slightly in New South Wales, Victoria, and Western Australia, but there was a significant increase in the Northern Territory. Tasmania has just overtaken South Australia as the state with the highest car ownership at 63.1 cars per 100 residents.

Victorian car ownership has been in decline since 2011, which is consistent with a finding of declining motor vehicle ownership in Melbourne from census data (see also an older post on car ownership).

Driver’s licence ownership

Thanks to BITRE Information Sheet 84, the BITRE Yearbook 2019, and some useful state government websites (NSW, SA, Qld), here is motor vehicle licence ownership per 100 persons (of any age) from June 1971 to June 2018 or 2019 (depending on data availability):

Technical note: the ownership rate is calculated as the sum of car, motorbike and truck licenses – including learner and probationary licences, divided by population. Some people have more than one driver’s licence so it’s likely to be an over-estimate of the proportion of the population with any licence.

There’s been slowing growth over time, but Victoria has seen slow decline since 2011, and the ACT peaked in 2014.

Here’s a breakdown by age bands for Australia as a whole (note each chart has a different Y-axis scale):

There was a notable uptick in licence ownership for 16-19 year-olds in 2018. Otherwise licencing rates have increased for those over 40, and declined for those aged 20-39.

Licencing rates for teenagers (refer next chart) had been trending down in South Australia and Victoria until 2017, but all states saw an increase in 2018 (particularly Western Australia). The most recent 2019 data from NSW and Queensland shows a decline. The differences between states partly reflects different minimum ages for licensing.

The trends are mixed for 20-24 year-olds: the largest states of Victoria and New South Wales have seen continuing declines in licence ownership, but all other states and territories are up (except Queensland in 2019).

New South Wales, Victoria, and – more recently – Queensland are seeing downward trends in the 25-29 age bracket:

Licencing rates for people in their 70s are rising in all states (I suspect a data error for South Australia in 2016):

A similar trend is clear for people aged 80+ (Victoria was an anomaly before 2015):

See also an older post on driver’s licence ownership for more detailed analysis.

Transport greenhouse gas emissions

[this emissions section updated on 8 January 2020 with BITRE estimates for 1975-2019]

According to the latest adjusted quarterly figures, Australia’s domestic non-electric transport emissions peaked in 2018 and have been slightly declining in 2019, which reflects reduced consumption of petrol and diesel. However it is too early to know whether this is another temporary peak or long-term peak.

Non-electric transport emissions made up 18.8% of Australia’s total emissions as at September 2019.

Here’s a breakdown of transport emissions:

A more detailed breakdown of road transport emissions is available back to 1990:

Here’s growth in transport sectors since 1975:

Road emissions have grown steadily, while aviation emissions took off around 1991. You can see that 1990 was a lull in aviation emissions, probably due to the pilots strike around that time.

In more recent years non-electric rail emissions have grown strongly. This will include a mix of freight transport and diesel passenger rail services – the most significant of which will be V/Line in Victoria, which have grown strongly in recent years (140% scheduled service kms growth between 2005 and 2019). Adelaide’s metropolitan passenger train network has run on diesel, but more recently has been transitioning to electric.

Here is the growth in each sector since 1990 (including a breakdown of road emissions):

Here are average emissions per capita for various transport modes in Australia, noting that I have used a log-scale on the Y-axis:

Per capita emissions are increasing for most modes, except cars. Total road transport emissions per capita peaked in 2004 (along with vehicle kms per capita, as above).

It’s possible to combine data sets to estimate average emissions per vehicle kilometre for different vehicle types (note I have again used a log-scale on the Y-axis):

Note: I suspect the kinks for buses and trucks in 2015, and motor cycles in 2011 are issues to do with assumptions made by BITRE, rather than actual changes.

The only mode showing significant change is cars – which have reduced from 281 g/km in 1990 to 243 g/km in 2019.

However, the above figures don’t take into account the average passenger occupancy of vehicles. To get around that we can calculate average emissions per passenger kilometre for the passenger-orientated modes:

Domestic aviation estimates go back to 1975, and you can see a dramatic decline between then and around 2004 – followed little change (even a rise in recent years). However I should mention that some of the domestic aviation emissions will be freight related, so the per passenger estimates might be a little high.

Car emissions per passenger km in 2018-19 were 154.5g/pkm, while bus was 79.4g/pkm and aviation 127.2g/pkm.

Of course the emissions per passenger kilometres of a bus or plane will depend on occupancy – a full aeroplane or bus will have likely have significantly lower emissions per passenger km. Indeed, the BITRE figures imply an average bus occupancy of around 9 people (typical bus capacity is around 60) – so a well loaded bus should have much lower emissions per passenger km. The operating environment (city v country) might also impact car and bus emissions. On the aviation side, BITRE report a domestic aviation average load factor of 78% in 2016-17.

Cost of transport

The final topic for this post is the real cost of transport. Here are headline real costs (relative to CPI) for Australia:

Technical note: Private motoring is a combination of factors, including motor vehicle retail prices and automotive fuel. Urban transport fares include public transport as well as taxi/ride-share.

The cost of private motoring has tracked relatively close to CPI, although it trended down between 2008 and 2016. The real cost of motor vehicles has plummeted since 1996. Urban transport fares have been increasing faster than CPI since the late 1970s, although they have grown slower than CPI (on aggregate) since 2013.

Here’s a breakdown of the real cost of private motoring and urban transport fares by city (note different Y-axis scales):

Note: I suspect there is some issue with the urban transport fares figure for Canberra in June 2019. The index values for March, June, and September 2019 were 116.3, 102.0, and 118.4 respectively.

Urban transport fares have grown the most in Brisbane, Perth and Canberra – relative to 1973.

However if you choose a different base year you get a different chart:

What’s most relevant is the relative change between years – eg. you can see Brisbane’s experiment with high urban transport fare growth between 2009 and 2017 in both charts.

Hopefully this post has provided some useful insights into transport trends in Australia.


Update on Australian transport trends (December 2018)

Fri 28 December, 2018

For more recent trend information – skip to the December 2019 update on Australian transport trends.

Each year, just in time for Christmas, the good folks at the Australian Bureau of Infrastructure, Transport, and Regional Economics (BITRE) publish a mountain of data in their Yearbook. This post aims to turn those numbers (and some other data sources) into useful knowledge – with a focus on vehicle kilometres travelled, passenger kilometres travelled, mode shares, car ownership, driver’s licence ownership, greenhouse gas emissions, and transport costs.

Vehicle kilometres travelled

Road transport volumes are rising, and most of the traffic is of course cars:

Here’s the growth by vehicle type since 1971:

Light commercial vehicle kilometres have grown the fastest, curiously followed by buses (although much of that growth was in the 1980s).

Car kilometre growth has slowed significantly since 2004.

In fact, on a per capita basis car use peaked in 2004 and then declined until 2014, with a little growth since. Here’s the Australian trend (in grey) as well as city level estimates to 2015 (from BITRE Information Sheet 74):

Technical note: “Australia” lines in these charts represent data points for the entire country (including areas outside capital cities).

Darwin has the lowest average which might reflect the small size of the city. The blip in 1975 is related to a significant population exodus after Cyclone Tracey caused significant destruction in late 2014 (the vehicle km estimate might be on the high side).

Canberra, the most car dependent capital city, has had the highest average car kilometres per person (but it might also reflect kilometres driven by people from across the NSW border in Queanbeyan).

The Australia-wide average is higher than most cities, with areas outside capital cities probably involving longer average car journeys and certainly a higher car mode share.

Passenger kilometres travelled

It’s also possible to look at car passenger kilometres per capita, which takes into account car occupancy – and also includes more recent estimates up until 2017:

While car passenger kilometres per capita also peaked in 2004, they have increased slightly in recent years in Perth, Adelaide, Brisbane, and Sydney.

BITRE also produce estimates of passenger kilometres for other modes (data available up to 2017 at the time of writing).

Rail use is highest in Sydney followed by Melbourne. You can see two big jumps in Perth following the opening of the Joondalup line in 1992 and the Mandurah line in 2007.

(note: this includes both public and private bus travel)

Australia-wide bus usage is surprisingly high. While public transport bus service levels and patronage would certainly be on average low outside capital cities, buses do play a large role in carrying children to school – particularly over longer distances in rural areas. The peak for bus usage in 1990 may be related to deregulation of domestic aviation, which reduced air fares by around 20%.

Darwin saw a massive increase in bus use in 2014 thanks to a new nearby LNG project running staff services, while investments in increased bus services in Melbourne and Brisbane in the first decade of this century led to significant patronage growth.

We can sum all of the mass transit modes (I use the term “mass transit” to account for both public and private bus services):

We can also calculate mass transit mode share of motorised passenger kilometres (walking and cycling kilometres are unfortunately not estimated):

Sydney has maintained the highest mass transit mode share, while Melbourne made significant gains between 2005 and 2009, and Brisbane also grew strongly 2007 to 2013.

Here’s how car and mass transit passenger kilometres have grown since car used peaked in 2004:

Mass transit use has grown much faster than car use in Australia’s three largest cities. In Sydney and Melbourne it has exceeded population growth also.

Mass transit has also outpaced car use in Perth, Adelaide, and Hobart:

In Canberra, both car and mass transit use has grown much slower than population, and it is the only city where car growth exceeded public transport growth between 2004 and 2017.

Car ownership

The ABS regularly conduct a Motor Vehicle Census, and the following chart includes data up until January 2018.

Technical note: Motor Vehicle Census data (currently conducted in January each year) has been interpolated to produce June estimates for each year.

Car ownership has continued to rise slowly in all states – except Victoria, which is consistent with a finding of declining motor vehicle ownership in Melbourne from census data (see also an older post on car ownership).

Driver’s licence ownership

Thanks to BITRE Information Sheet 84, here is motor vehicle licence ownership per 100 persons (of any age) going back to 1971:

Technical note: the ownership rate is calculated as the sum of car, motorbike and truck licenses – including learner and probationary licences, divided by population. Some people have more than one driver’s licence so it’s likely to be an over-estimate of the proportion of the population with a licence.

There’s been slowing growth over time, but Victoria has seen slow decline since 2011.

Here’s a breakdown by age bands (note each chart has a different Y-axis scale):

Motor vehicle licence ownership rates have increased for people over 70 (presumably due to a healthier ageing population), and declined for people under 30.

Licencing rates for teenagers have been trending down in South Australia and Victoria recently, but not in other states:

The trends are mixed for 20-24 year-olds:

New South Wales and Victoria are seeing downward trends in the 25-29 age bracket:

Licencing rates for people in their 70s are rising in all states (I suspect a data error for South Australia in 2016):

A similar trend is clear for people aged 80-89 (Victoria was an anomaly before 2015):

(see also an older post on driver’s licence ownership for more detailed analysis)

Transport greenhouse gas emissions

Australia’s domestic non-electric transport emissions have increased steadily since 1990 and show no signs of slowing down, let alone declining (latest data at the time of writing is up to June 2018):

Depending on how you disaggregate total emissions, transport is the second largest sector and the fastest growing.

Here’s breakdown of transport emissions (detailed data only available to 2016 at time of writing):

And the growth in each sector since 1990:

Domestic aviation has had the fastest growth, followed by buses. In more recent years rail emissions have grown strongly (note: most of this is rail freight as the vast majority of passenger train movements are electric). Car emissions have grown 27%, but make up the largest share of transport emissions.

Here are per capita transport emissions for each state:

The data is a bit noisy (largely due to fluctuations in aviation emissions). Here are road emissions per capita:

In 2016 there were sharp increases in Western Australia, Queensland and the Northern Territory, while most other states appear to be on a downward trend.

Car emissions per capita have been generally trending downwards in most states, again except Queensland, Western Australia, and the Northern Territory:

Of course if we are to avoid dangerous climate change, total emissions need to reduce substantially, not just per capita emissions!

It’s possible to combine data sets to estimate average emissions per vehicle kilometre for different vehicle types:

It’s difficult to see any significant reductions in emissions intensity, while average bus emissions intensity has increased recently (not sure why). Average car emissions have fallen slightly from 281 g/km in 1990 to 244 g/km in 2016.

However, the above figures don’t take into account the average passenger occupancy of vehicles. To get around that we can calculate average emissions per passenger kilometre for the high person-capacity modes:

Of course the emissions per passenger kilometres of a bus or plane will depend on occupancy – a full aeroplane or bus will have likely have significantly lower emissions per passenger km. Indeed, the BITRE figures imply an average bus occupancy of around 9 people (typical bus capacity is around 60) – so a well loaded bus should have much lower emissions per passenger km. The operating environment (city v country) might also impact car and bus emissions. On the aviation side, BITRE report a domestic aviation average load factor of 78% in 2016-17.

Cost of transport

The final topic for this post is the real cost of transport. Here are headline real costs (relative to CPI) for Australia:

Technical note: Private motoring is a combination of factors, including motor vehicle retail prices and automotive fuel. Urban transport fares include public transport as well as taxi/ride-share.

The cost of private motoring has tracked relatively close to CPI, although has been trending down since around 2008. The real cost of motor vehicles has plummeted since 1996. Urban transport fares have been increasing faster than CPI since the late 1970s.

Here’s a breakdown of the real cost of private motoring and urban transport fares by city (note different Y-axis scales):

Urban transport fares have grown the most in Brisbane, Perth and Canberra – relative to 1973.

However if you choose a different base year you get a different chart:

What’s most relevant is the relative change between years – eg. you can see Brisbane’s experiment with high urban transport fare growth between 2009 and 2017 in both charts.

To illustrate the data visualisation problem of choosing a base year – here is the same data for every base year between 1973 and 2018:

Hopefully this post has provided some useful insights into transport trends in Australia. A future post might examine the relationships between the data sets further.


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.