The first shows average household VKT. This is estimated in the following way:
1) I estimate a simple household travel model that predicts household VKT based on household type, income, and location.
2) I take data from the 2006 census (which tells us where households are living) and estimate how far they will drive per annum
The model is pretty simple, but the trend is clear.
The above map is interesting, but there is a lot going on -- vehicle use changes with income and household type and location, and these all vary spatially.
Another way of looking at it is to think about the independent effect of location, so, what happens if you take the same household and move that household around. How does their vehicle use vary?
I cant do this exactly, for technical reasons I wont bore you with, but the map below is an attempt to get close. The actual method used to obtain this estimate is a little involved, and involves some guesswork, so dont take it as gospel, but it is at attempt to estimate the independent effect of location. In this instance, I take households from a wealthy area (but not stinking rich, i.e. not Vaucluse/Mosman) that has lots of 'couples with kids' households, and 'move' those households around (en-masse). The following map shows average household VKT when you hold income and household type constant, and change location only. I hope that explanation is comprehensible.
The last map (below) shows average commute time (by origin) in Sydney. This one is compiled as follows:
1) Take ABS journey to work data (They have origin -> destination trip counts by travelzone, which are the spatial regions shown here)
2) Take NSW Transport Data Centre zone->zone travel times (at peak hour).
3) From (1) and (2), calculate average commute per zone.
Again, nothing so surprising here.
Note that the commute time shown here is the average commute for all modes (i.e. car and walk and publilc transport and.. well... everything).
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