Bill mentioned the results using the traffic engineer's data on Nantes. What is interesting with the data set is that most of the data counts used are beyond the confine of what is usually categorised as dense urbanized or suburb areas. This is the far suburbs what in the French literature they call metaphorically the archipelago city, the strings of "bourgs" that surround a city spread within the green belt - if we were to compare with London it would mainly be data counts on road including the M25 and beyond and the main radial trunk roads in and out of London M25 edge.
Nantes Urban Community is a 650 000 inhabitants conurbation. The city has a radio concentric organisation with an inner half ring of boulevards and a full outer orbital that is a 2x2 lanes motorway. The orbital diameter is about 11-12 km, the Space Syntax model extend 7-10 km beyond the orbital (London orbital diameter is about 50 km, the equivalent model would be 35-40km beyond the M25 a rather daunting task - lets not even think of the Tokyo equivalent model). I believe this is a space Syntax first (Bill, Alan correct me if this is too much of a claim), a fairly large complete conurbation and beyond is extensively modelled.
The model is what we called a spatial model, it does not distinguish pedestrian only from car only, it includes most country lanes, path etc, this is for very pragmatic reasons just because most of the time it is very difficult from a map and aerial photo point of view to know if this is car only or pedestrian only and there are no way to check that out systematically, should that car path leading to these cluster of farms be included or not etc. The first go was to be all-inclusive.
The way I conceptualise this spatial model is that from an holistic point of view all mobility modes combined are organising human activities and so their organisation as a whole may have some sort of consistencies instead of viewing it as a set of marketing life style slices (the cyclist, the pedestrian, the car driver, the commuter etc) which probably as they are modelled as such and reified through project end up fragmenting the all mobility mode networks. Yet, as the discussion that just took place highlighted it, the best is to do them all and see what difference it makes. So we are in the process of remodelling the conurbation as car only network versus pedestrian only network.
If we combine the Nantes results, Alan alternative explanation, Bill's explanations and now look at what happened to the Greater Boston conurbation over the last 50 years in term of spatial accessibility; i.e. road building in relationship to land uses, demographics, car ownership spread and land use shifts see http://www.ctps.org/bostonmpo/resources/demographic.pdf we won't be has puzzled than the transport engineer/planner seems to be in their conclusions.
You may wonder about public transportation network; the Boston network on a simple visual analysis seems to be in synchrony with the most spatially accessible route. Is this a surprise not quite, the business case for public transport network is made from a demand side, if the demand side is driven by spatial accessibility it should be no surprise that we should find some synchrony between spatial accessibility and public transport network. So far this is a visual analysis only, we now need the number that back it up or bin it.
_______________________________
Alain Chiaradia
Associate Director
SPACE SYNTAX
_______________________________
-----Original Message-----
From: Alan Penn
Sent: 07 May 2004 14:44
To: [log in to unmask]
Subject: Re: What streets to include in axman
Sanjay,
Can I suggest that you take a look at the papers first - they are all
about trying to explain what on the face of it is an unexpectedly strong
correlation... One answer is that it is obvious. The configuration of
the route network affects people's choice of routes with the result that
when one looks at the results of ALL choices - ie. the average flows in
the network - they turn out to be strongly correlated with
configurational measures. Since origins and destinations of trips are
pretty liberally distributed everywhere perhaps one would not expect
these to have a particularly strong effect on aggregate flows.
Alternatively - and this is in fact what I think - the processes of land
use allocation to urban parcels in cities that have evolved, leads to
those land uses that value accessibility by people locating in greater
densities in more accessible locations in the configuration. These land
uses are those that 'attract' the largest volume of trips. There is
therefore a process by which land uses and development densities
(origins and destinations for trips) evolve over time to correlate with
spatial configuration.
One key question is why people have not found effects of configuration
of the network to be important before. This I believe is the result of
our selection of the axial line as the basic element of the network.
Axial lines give rise to non-planar graphs, whilst the selection of
intersections as nodes and road segments as links in conventional
traffic models give rise to planar graphs. Planarity coupled to metric
distance based 'costs' lead to measures of configuration in the
conventional traffic modellers network representation being almost
entirely dependent on the selection of the boundary to the area mapped -
the accessible location is in the middle of whatever patch of the
surface of the world one has mapped. This means that configurational
measures in these representations are essentially arbitrary. This is not
the case with measures of configuration based on axial graphs. Here the
centre of the map can be (and often is) segregated and the edges
integrated. More importantly though, if you select a patch of a
continuous urban system mapped axially and analyse it, and then move the
boundary of the patch a bit and analyse again, and so forth, the pattern
of integration remains remarkably stable regardless of boundary. For a
node map the integrated centre moves with the bondary. The stability of
the axial map regardless of choice of boundary results from its being
non-planar.
There is a another element to the 'explanation' of why the axial line
should be a sensible representational element. One answer to this is
that it represents something close to what people moving through a
system of space experience as the locally stable elements of space. The
argument is that it is linear elements that are subject to least change
(in visual flow terms) as the observer moves. Changes of direction
conversely involve a high degree of change in local information from the
visual field. I have discussed this 'cognitive' argument and the
empirical evidence for it in:
Space syntax and spatial cognition: or why the axial line?
(Penn, A.) Environment and Behaviour, (2003) 35 (1) 30-64, Sage
Publications, ISSN:0013-9165.
Alan
>
> >I understand your suggestion, but perhaps the key might be the other
way
> >round. How about using space syntax measures - which already explain
> >over 80% of the variance in traffic flows in the London network - in
the
> >matrix estimation phase of the construction of traffic models? This
> >would allow those models to use the other factors you mention to help
> >explain the 20% of variance remaining unexplained by the
configuration
> >of the network.
>
> thanks for the paper references.
> 80% confidence in variance prediction is an excellent result. could
you
> please briefly discuss the reasons/characteristics that lead to such
> excellent outputs?
>
> thank,
> sanjay.
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