What impact has the 2020 COVID-19 pandemic had on pedestrian volumes in central Melbourne?

Mon 25 May, 2020

[update 8 July 2020]

Consistent with reductions in vehicle and cycling traffic, central city pedestrian volumes measured by the the City of Melbourne also dropped considerably during the pandemic.

How much have volumes reduced? How has this varied by day types, locations, and times of day? Join me as I dive into the data.

The City of Melbourne have installed 64 pedestrian counters in and around the CBD. Here’s a map of the sites and some (arbitrary) groups (which I’ll use later):

The sensors are not evenly distributed over the city, with a bias towards the central retail core, so they are unlikely to be perfectly representative of central city pedestrian activity, but the data is available and is interesting.

Of course sensors fail from time to time, so we don’t have a complete time series for all sites for all days. There have also been many more sensors added over time. Here is a chart showing the sensors reporting for each day since counting began in 2009:

To get a reasonable comparison, the following chart aggregates data from 44 measuring sites that have complete or near-complete data for 2019 and 2020 (so far):

The gaps in the lines are due to public holidays, which have been excluded (I have not coded Easter Saturday as a public holiday).

You can see volumes drop significantly from around week 12 onward in 2020 (starts Sunday 15 March), as restrictions were introduced.

You can also see significant week to week variations in volumes in 2019, so when measuring the decline I’m going to compare volumes with those in the first two weeks of March (when universities had commenced on-campus teaching).

Here are daily volumes relative to the average of the first two weeks in March:

You can see volumes down over 80% by early April, followed by some small growth until late June when things went back into decline as the number of COVID-19 cases reports in Victoria rose.

The reductions were fairly consistent across all day types, until May when Saturday volumes grew faster. The variation between consecutive days in February reduced dramatically, suggesting perhaps there was a lot less discretionary pedestrian activity during the lock down.

During the first recovery phase there have been a few outliers:

  • Thursday 9 April was the day before Good Friday when most retail trading is restricted.
  • Wednesday 29 April was a very wet day (23.6 mm of rain)
  • Saturday 16 May was the first Saturday after restrictions were eased (also a fine sunny day of maximum 18 degrees).
  • Monday 1 June was cold and wet.

While the Sunday decline appears to be the largest, Sunday 8 March was during the Moomba festival on a long weekend, so there were many more people in the city than normal that night, inflating the baseline.

Likewise the first two Saturdays in March had quite different volumes, which may be related to special events as well. So I would suggest not getting carried away with the exact decline percentages.

How have volumes changed in different parts of the city?

Of course the pedestrian volume reductions have not been uniform by place or day of the week. Here are the reductions on weekdays for week 14 (29 March – 4 April), when overall volumes bottomed:

Volumes were down the most around Melbourne University, and reductions of around 85% were typical in the CBD grid. There were smaller reductions in Docklands (which might reflect many pedestrians being residents), and around Queen Victoria Market (one site only down 44%).

Here’s the same again for Saturday 4 April:

The largest reductions around the arts precinct in Southbank, the retail core of the CBD, and around Melbourne University. Lesser declines are again in Docklands and around Queen Victoria Market.

And here is Sunday 5 April:

Patterns are similar again.

What are the trends in different parts of the city?

The next chart looks at the volumes trends for my sensor groups over time for weekdays:

The relative decline was initially fairly consistent across the groups over the weeks, with the university sites showing the biggest declines, and the residential and retail sites showing the least decline. The retail precincts of Lygon Street, CBD central, and Melbourne Central (around the station) have shown the most growth since May, as cafe restrictions were listed.

The story is quite different on Saturdays:

There is historically a lot more week to week variation, and the numbers for Docklands have bounced around a fair bit – with 16 May close to normal levels of pedestrian activity (a dry day with maximum 18 degrees, lower days had rain). Saturday 23 May was a fairly wet day, so might have discouraged travel.

Queen Victoria Market has also shown considerable growth since early April – with volumes within the bounds of regular volumes.

The spike for CBD east on 7 June was due to the Black Lives Matter protest.

Saturday pedestrian volumes have declined from late June as concern rose about a second wave.

Sundays are similar:

Docklands, Queen Victoria Market and Melbourne Central all increased on Sundays during May (all with little or no rain).

The fact that the Southbank / River group has shown the largest decline is probably related to it having a high base – with the Moomba festival causing a spike in pedestrian volumes on 8 March.

How have volumes changed by time of day?

Here’s the profile of hourly volumes for sites with complete data for 2020 on weekdays:

You can see the normal AM peak, lunchtime peak, and PM peak, which have been largely flattened since the pandemic hit. Weekdays are now busiest in the afternoons – which is a profile much more like a normal weekend day (more on that in a moment).

If you follow the colours carefully you can see the rapid decline in late March, followed by slow growth, peaking in the week of 14 June, then declining again.

Here are hourly volumes relative to the first two weeks of March:

The biggest reductions have been in the AM peak and evenings, which reflects a reduction in commuters and hospitality activity. The reductions are slightly smaller mid-morning and mid-afternoon (between the regular peaks) reflecting a flattening of the profile.

The smallest percentage reductions have been at 4-5am in the morning, off a small base.

Here is Saturdays:

Reductions have again been largest in the evenings, just after midnight (Friday night), and least around dawn. You can see Saturday afternoons showing growth until mid June, but little growth in the evenings as restaurants, bars, and theatres remained closed.

Same again for Sundays:

Sunday 8 March is an outlier in the day and evening – with the Moomba festival on, and the following Monday being a public holiday.

Another way to visualise hourly data

Here’s a chart that shows pedestrian volumes for every hour of 2020 up to and including 7 July 2020. The rows are days, and the columns are hours of the day:

You can see how pedestrian activity very quickly became quiet in March. Before the shutdown you can also see the weekly patterns, with weekend activity starting later and finishing later.

The top row is New Years Day, and you can see high volumes in the first few hours from new year celebrations.

May 16th was the first Saturday after restrictions were eased and that shows up as the first spike in the recovery phase.

This can be filtered for locations. For example, here is the data for Queen Victoria Market sensors:

You can see clear stripes for days the market was open (including night markets). The first busy day after the shut down was the Thursday before Good Friday – perhaps people cramming shopping ahead of Good Friday (Easter Saturday was also busy). The market continued to trade throughout this time. Things started to quieten down in late June / early July.

I will try to periodically update this post during the recovery.

An aside: visualising activity over a long weekend

Nothing to do with the pandemic, but a bit of fun to finish. Here is an animation of pedestrian volumes over the Labour Day long weekend 6-9 March 2020 (Friday to Monday):

If you watch carefully you’ll spot some sudden surges from a Saturday evening event at Docklands Stadium.

What impact has the 2020 COVID-19 pandemic had on cycling patterns in Melbourne?

Sun 17 May, 2020

[fully revised 12 July 2020 with data up to 5 July 2020]

There has been talk about about a boom in cycling during the COVID-19 pandemic of 2020 (e.g. refer The Age), but has that happened across all parts the city, across lanes and paths, and on all days of the week?

About the data

In Melbourne there are bicycle counters on various popular bike paths and lanes around the city (mostly inner and middle suburbs), and so I thought it would be worth taking a look at the data. But I should stress that the patterns at these sites may or may not cycling patterns across Melbourne.

Here’s a map of the sites, including my classification of bike path sites into ‘recreational’ and ‘other’ (based on time of day demand profiles):

There’s also one bicycle counting site on Phillip Island, which I’m excluding this from this analysis as it is outside Melbourne.

But before plotting the data, it’s important to understand data quality. Since 2015 there have been 35 bicycle counting sites in Melbourne (most of them pairs counting travel in each direction). But for whatever reasons, data is not available at all sites for all days. Here is the daily number of sites reporting from January 2015 to 5 July 2020 (at least with data available as of 9 July 2020).

There are notable gaps in the data, including most of the latter part of November 2017, and around mid-2018.

So any year-on-year comparison needs to includes sites that were active in both years. For my first chart I’m going to filter for sites with complete data for 2019 (all) and 2020 (to 5 July). I’ve also filtered out a few sites with unusual data (very low counts for a period of time – possibly due to roadworks).

How do 2020 volumes compare to 2019?

Here is a chart showing average daily counts as a four week rolling average, dis-aggregated by whether the site was a bike lane (5 sites), recreational path (12 sites), or other path (9 sites) and whether the day was a regular weekday, or on a weekend/public holiday.

Weekday bike lane travel has reduced substantially, although in June the percentage reduction was less. This makes sense as most of these sites are on roads leading to the CBD, and most workers who normally work in the CBD have been working from home.

Volumes in bike lanes on weekends in 2020 have been very similar to 2019. This might reflect bike lanes not attracting additional recreational cyclists, or perhaps an increase in recreational cycling is offset by a decline in commuter cycling.

Volumes on recreational paths have been much higher than in 2019, most significantly on weekends. Again this makes sense, as people will be looking to exercise on weekends in place of other options no longer available (eg organised sports, gyms). In late June and early July, volumes did however reduce, perhaps as gyms reopened (22 June) and some sports resumed. This may change again during the second Melbourne lock down that commenced 9 July 2020.

Weekday traffic on paths not classified as recreational was down significantly in 2020. I’ll explore this more shortly.

How have volumes changed at different sites?

Here’s a look at the percentage change at each site on weekdays. I’m comparing weeks 14-19 of years 2020 and 2019 (33 sites have complete data for both periods). Weeks 14-19 mark the first four full weeks of the first full lock down.

You can see significant reductions near the CBD, and on major commuter routes (lanes and paths). The biggest reduction was 71% on Albert Street in East Melbourne.

The blue squares are mostly recreational paths where there has been massive growth, the highest being the Anniversary trail in Kew at +235%! However I should point out that these growth figures are often off very low 2019 counts. It may be that people working from home (or who have lost their jobs) are now going for recreational rides on weekdays.

You might notice one square with two numbers attached – the +27% is for the Main Yarra Trail (more recreational), and the -32% is for the Gardiners Creek rail (probably more commuter orientated at that point). The two counters are very close together so the symbols overlap.

Here is the same again, but with the changes in average daily counts:

Many of the high growth percentages were not huge increases in actual volumes. The bay-side trail experienced some of the bigger volume increases.

On weekends and public holidays, there were smaller percentage reductions near the city centre, and large increases in the suburbs:

The percentage increases on weekends are not as high because there was a higher base in 2019. The reductions in the central city are smaller, but still significant – this may reflect fewer CBD weekend workers with a downturn in retail activity.

Again, here is a map of the changes in volume on weekends:

How have volumes changed by distance from the CBD?

Here’s another way to view the data – sites by distance from the CBD:

Bike lane volumes are down significantly at most sites, particularly on weekdays. Bike path volumes are down on weekdays at most sites within 6 km of the CBD, but up at sites further out, and up at most sites on weekends.

How have volumes changed by time of day?

I’m curious about the volume changes on paths on weekdays, so I’ve drilled down to hourly figures. Here are the relative volumes per hour for the months April – June:

Bicycle volumes are down in weekday peak periods on all site types, which you might expect as a lot of peak period cycling trips are to/from the central city.

Daytime bicycle volumes are significantly higher on recreational paths, and to a lesser extent on other paths. For the warmer months of April and May there was a recreational peak around 4pm, while in June the profile was more of a single hump across the day.

So the changes in volumes on paths are certainly a mix of reduced peak traffic, and increased off-peak traffic. The middle of the day increase is perhaps people breaking up the day when working from home, or people who are no longer working.

On weekends bike lane volumes are slightly up in the middle of the day, but down in the morning and evening. There’s been a substantial increase in bike path volumes on weekends – suggesting people seeking recreational riding opportunities on the weekend are choosing the much more pleasant bike path environments.

What will happen post COVID-19?

Of course this data only tells us about what’s been happening during the first lock down and the gradual recovery thereafter (until just before the second lock down).

It will be interesting to see if there is an uptick in recreational cycling during the second lock down period, although it is in mid-winter.

Eventually there may well be a boom in cycling (particularly on bike lanes) when more people start returning to work – particularly in the central city – and look for alternatives to (what might be) crowded public transport.

I’ll try to keep an eye on the data over time and update this post periodically.

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

Sun 3 May, 2020

[Last updated 8 July 2020, not all charts]

Roads in Victoria were noticeably quieter during the depth of the pandemic shutdown, but just how much did 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? What has been the impact naming identifying hot spots and postcode lock downs?

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.

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.

The autumn school holidays started early (on Tuesday 24 March) although many students stayed home in the last days of term 1. School resumed on Wednesday 15 April with most students remote learning at home until late May when some returned.

The first official easing of restrictions took effect from Wednesday 13 May (week 20) allowing some social gatherings, and restrictions were further eased on 1 June (including allowing cafes to trade). However, on 20 June there was an announcement that easing of restrictions would slow, and some restrictions were actually tightened. Then on 2 July, ten postcodes went back into “lock down” with only essential travel permitted, with 2 more postcodes added from 5 July. The winter school holidays started on 29 June.

There are regular variances by day type (eg Fridays generally having the most traffic), 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-June volumes were down more like 10-20%, with significant growth on Saturdays. However there have been declines since the announcement of outbreaks on 20 June, and the start of winter holidays on 27 June.

A curious outlier is Thursday 9 April – the day before Good Friday, so there may have been some travel to holiday homes, and/or other travel that happens normally on the last workday of the week.

Another interesting pattern is that there was a surge in traffic volumes on the first weekend after restrictions where eased (16-17 May).

Have traffic trends been different in different parts of the state?

There have been many more COVID-19 cases in Melbourne than regional Victoria. Here’s a chart showing daily volume changes in Greater Melbourne:

There is very little difference compared to the whole of Victoria chart, as most signals are located within Greater Melbourne.

Since 20 June – a day on which 6 LGAs were nominated as having outbreaks of concern – there has been a general decline in traffic volumes, and a significant rise in the number of new cases per day. School holidays also commenced on 27 June which ordinarily results in a reduction in weekday traffic.

Here is a chart of only signals outside Greater Melbourne, showing much less decline in late June / early July.

For the next chart, I’ve divided signal sites into those outside Greater Melbourne, those in the six LGAs with warnings, and those in other areas of Greater Melbourne.

To overcome daily noise, I’ve calculated the rolling 7 day average volume – excluding public holidays with with some normalisation (see below chart explanation). That does mean that sudden daily changes in traffic are smoothed out over the following 7 days.

Here’s how that looks for the three divisions, together with the number of new COVID-19 cases per day:

Boring but necessary technical notes: Many traffic signals are on roads that are LGA boundaries – and which LGA an intersection falls into is almost random – it depends on the coordinates of the intersection point. To normalise volumes, I have calculated the ratio of the average volume for each day of the week in February to the overall February average, and then adjusted daily volumes using these ratios to produce a relatively smooth daily time series. The rolling 7 day average then omits any public holidays. It’s not perfect, as you can see around Easter, but it was necessary to avoid having large gaps or blips in the above chart. For this analysis I used February as the baseline, as there was a public holiday in the first two weeks of March, complicating the normalisation.

Following the LGA announcement, volumes started reducing significant in those LGAs, volumes reduced by a smaller amount in the rest of Melbourne, and initially volumes outside Melbourne increased (they peaked on 28 June then started declining).

Things next escalated on 25 June, when 10 suburbs were announced as outbreak concerns, with door-to-door testing campaigns to be conducted. These suburbs were within the 6 LGAs identified on 20 June, so this may have refined people’s concern.

It is possible to filter to sites in the listed hot spot suburbs, although there are only around 100 signalised such sites (and none at all fall into the small suburb of Albanvale) which makes for some noisy data. Also, I would dare say that a lot of traffic in these suburbs is through traffic rather than local traffic. That said, here’s how this looks:

Volumes immediately dropped more quickly in these suburbs compared to the rest of Melbourne. Regional volumes continued to rise until the start of the school holidays on 29 June.

Then on 30 June there was an announcement that 10 postcodes would return to “lock down” (only essential travel allowed) from 2 July. Those postcodes mostly – but not entirely – lined up with the 10 warning suburbs. Here’s a similar chart that separates out those postcodes:

There was a step change from 2 July as the restrictions took hold (on top of a reduction from the school holidays).

The 7 day averaging process hides a little of the behaviour change, so here is a daily volume chart for those 10 postcodes:

While volumes in these postcodes started declining from the first warning announcement on 20 June, if you look carefully you’ll see that on Wednesday 1 July there was little change in volume compared to the previous Wednesday. This was the last day before the lock down, and presumably some people made some extra travel that was about to become against the rules. Once the lock down had commenced, volumes were very similar to those experienced during the “stage 3” restrictions of early April.

An additional two postcodes were added to the lock down from 5 July, but then all of metropolitan Melbourne (and Mitchell Shire) are to lock down from 9 July.

How does 2020 compare to 2019?

The above analysis hasn’t differentiated school days and school holidays, and any general seasonality across the year. Here is a chart comparing 2020 with 2019 for weekdays, Saturdays and Sundays (excluding public holidays):

I will emphasise that there will be week-to-week variations, particularly on weekends, due to short term factors such as weather and special events. Also, while school returned in week 16 of 2020, most students were not attending schools in person.

The winter school holidays began in week 27, and traffic volumes in 2020 appeared to drop in proportion to the traffic reduction in the same week in 2019.

The following chart compares 2020 to 2019 on a daily basis (with 2019 days offset by -1 to align days of the week):

We can also look at the percentage difference between the years, but only for days that have the same day type in terms of school term or holidays, and public holidays where they fall on the equivalent day of the year. So there are some gaps in the following chart, plus some noise due to daily fluctuations:

This chart shows January to early July. There are gaps around the autumn school holidays and Easter as they didn’t perfect match days of the year perfectly.

You need to not get too excited about daily variations (the Tuesday in the second week of 2019 school holidays had unusually low volume in Melbourne for some reason, which shows up as a spike for 2020).

This chart gives a feel for variations from expected patterns. Traffic in the Melbourne was down a similar percentage in the first week of the winter school holidays compared to the previous week of school. Melbourne traffic volumes began falling in the second week of winter school holidays with the rise in cases and commencement of some postcode lock downs.

However in regional Victoria volumes were relatively higher in the winter school holidays – perhaps as Melbourne people were more likely to travel intrastate for holidays (interstate travel being heavily restricted, and travel not having been an option in the previous autumn school holidays). Regional Victoria travel volumes (at least up to 7 July) were down a similar percentage on 2019 as the first week of school 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, and the autumn school holidays started a couple of weeks earlier in 2020.

On this measure, weekdays bottomed out around 38% below 2019, but recovered to be ~10% down in week 24 (on weekdays). Weekends were down around 50%, but recovered to around 10-15% down.

How has traffic reduced by time of day?

The traffic signal data is available in 15 minute intervals, so it is possible to examine patterns in more detail.

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. From late May there was a significant jump in peak period traffic, coinciding with the return to school of grades Prep, 1, 2, 11 and 12.

1 July was the first week of the winter school holidays and you can see substantial traffic reductions at school times, most notably in the AM peak. Meanwhile the PM commuter peak (around 5 pm) was very similar to late June.

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 two weeks of March (with apologies to anyone with colour-blindness):

Volumes went 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 were down around 50% at the bottom, while the inter-peak period has held up the most – being only down around 30%.

More recently volumes have recovered considerably, with volumes around 3pm back near pre-COVID levels (prior to the winter school holidays). The AM peak is interesting – at 7am, traffic on 17 June was still down around 28%, but at 8:45am is was only around 9% down – possibly reflecting the school peak, and/or a narrowing of the commuter peak (as lower congestion provides less incentive for peak spreading). As at mid-June, evening traffic was still down around 40%.

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

Here is the same for Fridays (excluding the Good Friday public holiday):

Late evening traffic was down even more than for Wednesdays, which probably reflects higher volumes of hospitality-related travel on Friday nights. Friday evening traffic jumped on 15 May when small social gatherings were allowed, and again on 5 June when restaurants and cafes were allowed to have dine-in patrons.

Here is Saturdays (excluding Anzac Day):

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

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 I suspect it reflects a surge in travel just before 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 was down considerably – by over 70% by midnight at the depths of the shutdown, but jumped with restrictions easing, similar to Friday evenings. As of mid-June it was down around 25-30%.

You can also see early Saturday morning (Friday night) travel down around 60-70% at worst (discounting 11 April which was the Saturday morning following Good Friday).

Here is Sundays:

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:

Another anomaly here is Sunday 7 June – which was another public holiday eve.

Here’s the profile by day of the week for each week since February (public holidays excluded):

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. It also shows the middle of the day on Saturdays to mostly be busier than the same time on weekdays.

Here’s another look at relative time of day traffic volumes for March through to June:

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

  • Significant volume 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)

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.

The following animated chart shows median weekday volumes per week, by distance from the CBD, since the start of March 2020:

You can see the traffic decline has remained the largest in the central city. The reduction in traffic in the week of 28 June was mostly in the suburbs more than 3 km from the CBD.

The following animated map shows the change in volume relative to the first two weeks of March, for each site, each week since the beginning of March. Note that there are anomalous sites for various reasons (eg faults, roadworks) – I’ve tried to filter out some sites with unusual data, but it’s difficult to get all of them.

If you ignore individual sites that look like outliers you can see some clear patterns:

  • Volumes didn’t reduce as much in industrial areas, as freight and logistics largely kept operating, and factory workers continued to go to work.
  • Volumes haven’t recovered in the central city as they have in the suburbs, which makes sense with so many office workers have continued to work from home.
  • Melbourne Airport volumes are still significantly below normal, obviously due to national and international travel restrictions.
  • Volumes have been slower to recover in the Clayton employment area – probably related to working from home, and Monash University not having on-campus teaching.
  • Volumes reduced in the week of 29 June, a mix of the school holiday impact, an increase in travel restrictions, and probably general fear about a second wave of infections.

Again, I must apologise to the those with colour-blindness, it’s much more difficult to show the changes with only two-three colours.

Traffic signal data comes out daily, and so I will try to update this analysis at least once a week during the recovery period. There may be more frequent updates on Twitter.

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.