If you'll permit me stepping into the discussion of space syntax and
transport modelling, as a transport modeller / planner with a mere
inkling of space syntax.
In essence, transport models are *pivot* models. A transport model's
utility is in reliably forecasting the *change* from a current
situation that a policy or scheme would have, rather than in
describing the status quo.
So a model that explains 80% of the traffic flows in Central London
(before congestion charging), based on an axial map, will predict no
changes after such road pricing is introduced, as the axial map does
not change. Similarly with bus lanes, traffic light phasing, traffic
calming: all the standard tools of urban traffic management. But
flows have changed significantly ... and a useful transport model
would predict those changes reliably.
> If we combine the Nantes results ...
> we won't be has puzzled than the
> transport engineer/planner seems to be in
> their conclusions.
There's little new in the Boston conclusions in the document that was
linked to, earlier. I'd say that it seems to be somewhat behind the
times IMHO. The transport planning profession has known about the
linkages between land use mixture, density and travel demand for over
40 years (not that it's been reflected in policy and action, but
nevertheless the knowledge has been there), and there's been lots of
very good work done in the last 4 decades on describing those
linkages.
Total mobility is driven by relative and absolute accessibility of
individual modes, of course, and so a useful network model needs to
have coded within it which modes can use which links.
As traffic (or more usefully, general transport) models use
origin/destination matrices, I can't see how one would implement Alan
Penn's suggestion of: "using space syntax measures ... in the matrix
estimation phase of the construction of traffic models", but am
willing to be enlightened. I'm often agnostic as to the usefulness of
models based on such O/D matrices, but they do have lots of
advantages in terms of being able to inform policy decisions on land
use and transport.
Andrew Smith
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