Synchro 7, Report
Synchro 7, Report
1. INTRODUCTION
2.1.1 Trip Rates. Some evidence is available on the variation with accessibility in
overall trip Rates, in the Rates by various modes and in the Rates for various
purposes. Doubleday (1979) found that the numbers of work and of shopping trips
by women increased as their accessibility to these activities increased. Koenig
(1978) found a good correlation between the non-work trip rates of non-working
people and their accessibility to tertiary employment centres (that is, shops and
services).
2.1.2 Trip lengths. Black (1977) found that for most purposes (school, shopping,
leisure, social, recreational, medical, personal business) people made shorter trips
(in distance and in time) as their accessibility increased; it appeared that in general
they chose the nearest facility available. For work trips this was not so, but high
accessibility to work was found to reduce the proportion of very long work trips.
Several authors have considered the relation between on area's accessibility and
its level of car ownership. Dunphy (1973) found a significant correlation between
accessibility to employment by public transport and car ownership. Shindler and
Ferrari (1967) obtained a significant correlation between car ownership and the
ratio of employment accessibility by public transport to that by private transport.
One of the problems of making sense of the mass of indices to which the term
"accessibility measure“ has been applied is that the underlying definitions of
accessibility vary widely, and these definitions are not always given explicitly.
Therefore, this Section aims to sketch the range of meanings that have been given
to the word accessibility.
1. Some studies have been concerned solely with the spatial separation of one
point from another, or from all other points (de Lannoy, 1978). Typical
definitions are `the accessibility of a point in a system is a function of its
location in space with respect to all other points in the system (Hack, 1976)
and accessibility will imply relative nearness either in the sense of a direct
linkage or a minimum expenditure of travel cost or time.
3. Some studies have been concerned with the opportunity which an individual
or type of person at a given location possesses to take part in a particular
activity or set of activities (Hansen, 1959).
5. Finally, a few studies have identified accessibility with the consumer surplus,
or net benefit, that people achieve from using the transport and land-use
system (Leonardi, 1978). The consumer surplus is the difference between
the amount of money a person pays for a quantity of goods and the total
benefit he obtains from the goods. In this case the goods are trips and the
gross benefit of a trip is the gross benefit obtained at the destination of the
trip.
5. MEASURES OF ACCESSIBILITY
5.1 Introduction
In surveying the range of indices to which the term accessibility measure has been
applied it is possible to identify three main categories of measure. Measures in the
first category are concerned with the spatial separation of points or with the linkages
between points as a result of their relative locations on a network: they are closely
related to the first meaning of accessibility given in Section 4. Measures in the
second category (Section 5.3) are concerned with the amount of travel that takes
place and are related to the second meaning of accessibility given in Section 4.
Measures in the third category (Sections 5.4 and 5.5) are concerned with
consequences of the combined distributions of transport and Land-uses: these
reflect the remaining three meanings described in Section 4. This category can be
divided into those measures that combine the elements of separation and attraction
into a single index (Section 5.4) and those that keep these elements separate within
the measure (Section 5.5).
The term `travel cost' occurs frequently in the following description of the measures
and this expression needs some clarification. It refers to whatever is a deterrent to
travel and is most often measured by time or generalised cost.
Network measures are concerned solely with the transport network and their
approach is based on that of mathematical graph theory. The network is usually a
simplified road network (as used in traffic models) although the techniques are also
applicable to the public transport network.
(1) The associated number of a node: with distance measured by the number
of links, the associated number of a node is the distance between it and
the node furthest away from it in the network
(2) The number of other nodes reachable from a given node within a given
time by travelling on the network
(3) The Shimbel measure: this measure considers the node in relation to all
the other nodes in the network. It measures the accessibility of a node (i,
say) as the total travel cost to all other nodes; that is
Aij = f (cij)
The two Indexes described here are closely related and are concerned with
measuring amounts of travel; that is, they are concerned with on aspect of travel
behaviour. The first is concerned with observed travel, the second with predicted
travel.
(1) The average cost of observed trips leaving a zone has been suggested by
Savigear (1967) as a measure of the inaccessibility of that zone: that is
I =
∑ j
c ij T ij
[3]
∑
i
j
T ij
(2) A similar approach has been to consider the probability of a trip taking place
between each pair of zones. The following has been proposed by Knudsen and
Kanafani (1974) as a measure of inaccessibility:
I i = ∑ j pij cij [4]
lt has been suggested that this probability be calculated using gravity model or
intervening opportunities approaches.
The original idea was formulated by Hansen (1959) who proposed that the
accessibility of zone i measured by:
(
Ai = ∑ j B j d ija ) [5]
Ai = ∑ j B j f (cij ) [6]
where Bj = as before
cij = the travel cost from i to j
f() = some function to represent the deterrent effect of the travel
cost
Thus the original Hansen measure is a particular case of the generalised Hansen
with f(cij) = 1/ cija and cij = distance from i to j. For the sake of simplicity this
generalised Hansen index (which is the form in which it most commonly appears)
will henceforth be referred to simply as the Hansen index.
There are two fairly common variations of the Hansen measure that are often,
rather confusingly, referred to simply as Hansen measures. In order to clarify the
position these are described here and are given the names ’normalised Hansen'
and ’population weighted' Hansens. The ’normalised Hansen' is
Ai =
∑ j
B j f (cij )
[7]
∑ j
Bj
Thus, instead of using the absolute number of opportunities Bj in zone j, it uses the
proportion of the opportunities in the entire study area which zone j possesses,
B j
namely .The other is the `population weighted Hansen':
∑ jB j
Ai = Pi ∑ j B j f (cij ) [8]
Thus this type of measure identifies accessibility with the opportunity which the
residents of the study area possess to take part in a particular activity or set of
activities (that is, the fourth definition given in Section 4).
5.4.3 Rents, salaries and accessibility. Tanners used consumer surplus approach
to the locations of homes and jobs and the ways in which they are linked to give a
pattern of journeys to work and suggested that rent and salary differentials (where all
other factors are equal) can be regarded as accessibility measures.
Whitbread (1972) described some work done for West Midlands Regional Study on
identifying a measure of access to employment. A Hansen index was used with a
negative exponential deterrence function and with a zone's attraction measured by
the number of jobs it contained. A multiple linear regression was carried out of the
residential Land value of a zone on its access to employment and other variables
unrelated to employment accessibility. On the basis of this the value of the
coefficient b in the Hansen Index ( ∑ j B j e ij ) was calculated together with the
− bc
5.4.4 Travel behaviour and consumer surplus. Most of the measures that have
been described in this Section were developed using largely intuitive arguments.
There have been several attempts to put accessibility on a sounder theoretical
footing by using the concept, taken from economic theory, of consumer surplus and
it has been shown that a form of the Hansen accessibility Index is essentially a
measure of consumer surplus.
The underlying principle of the approach is that the benefits that people derive from
changes in the transport or Land-use facilities provided for them may be deduced
from the way they behave. Consumer surplus is defined as the difference between
the rum people have to pay for a quantity of goods and the rum they would be
prepared to pay or equivalently as the difference between the cost of the goods and
the total (or gross) benefits people obtain from them. The Marshellian measure of
the change in consumer surplus accompanying a fall from c1 to c2 in the cost of a
good is
c2
S = − ∫ D(c)dc [9]
c1
The goods to be considered here are trips. As was described in Section 4, the gross
benefit associated with a trip is the benefit available at its destination and its cost is
simply the cost of travel. The change Sij in the consumer surplus of trip makers
accompanying a fall from cij(1) to cij( 2 ) in the cost of travel from zone i to zone j,
assuming all other costs are constant, is given by
(2)
c ij
S ij = − ∫ Tij ( c ) dc
(1 )
[10]
c ij
where Tij (c) = number of trips from i to j when the cost of a trip from i to j is c
Sij = travel demand function
Provided that the negative exponential form of the deterrence function is used, the
gravity model formulation of the travel demand function has been shown (See
Cochrane, 1975) to be derivable (if certain assumptions are made) by considering
people as making trips which maximise their consumer surplus. Thus the gravity
model is on appropriate demand function to use to evaluate consumer surplus.
5.5.1 Contour measures. These are the most common family of disaggregate
measures of the combined transport and land-use System. For each zone a series
of travel cost (usually, but not necessarily, travel time) contours are drawn and the
numbers of relevant opportunities within each is counted. This is shown in figures 2,
3 and 4.
Figure 2.Graph of relation between number of jobs reachable and travel time,
from fig.3
Figure 3.Relation of jobs to travel time contours in a hypothetical town
This measure can take either of the following forms:
(a) the number of opportunities reachable within a given cost, or the numbers
within various costs
(b) the cost required to reach a given number (or various numbers) of
opportunities
∑ j
B j h(cij ) [11]
h (cij) = 1 if cij ≤ C
0 if cij > C
∑ j
B j f (cij ) [12]
(2) An analysis of how to use the type (a) contour measures has been made by
Breheny (1978) who identified three versions according to which elements
(population, opportunities or costs) were varying and which constant:
(3) Another analysis was made by Wytconsult (1977) for the West Yorkshire
Transport Study. They identified the following as possible measures
depending on the type of activity being accessed:
(4) Population weighted forms of contour measures have been suggested: for
example, Breheny (1978) proposed the average (over the population) travel
cost to reach a given level of opportunities. Wachs and Kumagai (1972)
used the average (over the population) number of opportunities reachable
within a given travel cost. The West Yorkshire Transport Studies (1979)
calculated on average travel time for on area by weighting the travel times
for different modes and activities by the number of people using each mode
and the activity needs of different types of people.
(5) The contour measures have also been reversed, with the concern being the
number or percentage of the population rather than the number or
percentage of opportunities; for example, the percentage of the population
within a given travel cost of important metropolitan activities or the
percentage of a rural population within a given travel cost of a town with
larger than a stated population (see Sherman et al.,1974).
One example of an individual's life path for a particular 24 hour period is given in
Figure 5. If only the fixed constraints on a person's time are considered then it is
possible to draw a `time-space prism' to indicate where it is feasible for him to be
at other times.
• Actual time taken, by mode used to reach the destination usually used for a
given activity. This type of measure is used in questionnaire-based studies
• Measure of centrality. The measure is the travel cost to the centre of the
urban area (in urban areas) or the nearest urban area (in rural areas). Thus
this measure could be viewed as a contour measure of the second type
with the simplifying assumption that the only destination to which access is
required is the urban centre.
6. COMPONENTS OF MEASURES
This Section considers the various ways that have been proposed of measuring
the several components involved in most accessibility measures. The First section
considers ways of measuring travel cost, the second looks at the functions that
have been used to represent the deterrent effect on travel of this travel cost and
the third describes ways of measuring the attractiveness of destinations for
various activities. The fourth section considers ways in which the effect of
competition has been incorporated into accessibility measures.
The measurement of travel cost falls into two categories. Some studies have
identified it with physical separation and have used measures such as:
On the other side travel cost can be interpreted in a more widely way as:
• Travel time
• the number of links weighted by length,
• cost of travel and road quality;
• generalised travel cost (that is a combination of money cost, time and other
factors such as comfort;
• (for public transport) travel time plus the mean Service interval.
These measures allow a particular mode or route to be studied or the best from
several to be identified and used. Travel time and generalised cost are the most
commonly used measures of travel cost.
The purpose of taking a function of travel cost rather than using travel cost
unaltered is to represent better the deterrent effect of the difficulty of reaching a
facility on its use. Only some of the measures that have been described include
such a function. Of the main types of combined measure, the time-space
geographic measures do not include it, the contour measures include it to a limited
extent (this is discussed further below) and the most general use is in Hansen
measures and the consumer surplus approach
Ai = ∑ j B j f (cij ) [13]
The function f most commonly used is the negative exponential, that is f(c) = e -bc
for some constant. The only other function used more than occasionally is the
negative power, that is f(c) = c -a for some constant. A modified version of the
Gaussian function f(c) = e-c2/u for some constant u has also been proposed but has
rarely been used. All three types of curves are illustrated in Figure 7. Ingram gave
three requirements for a deterrence function:
7.1 Introduction
The aim of this Section is to discuss, in fairly general terms, the indices
described in Section 5 in terms of their usefulness as measures of accessibility. As
a starting point for this, six criteria will be set down which it seems reasonable to
ask on accessibility measure to satisfy. Several of the indices will be discussed
further, taking into consideration their theoretical backgrounds and the ease with
which they can be used in practice
And the measure of accessibility should behave in accordance with these three
criteria:
Measures of travel were described in Section 5.3. These can be viewed in two
slightly different ways. One is that they define accessibility as the observed (or
predicted) amount of travel and the other is that they define accessibility in some
other way but feel that this is best measured by the observed (or predicted)
amount of travel. They have the advantage of using data that are often readily
available but they do not satisfy some of the criteria, as can be seen by
considering the following examples. If a new sports centre is built in a town, some
people may change the destination of some of their trips to the new centre from a
more local playing field and other people may be inspired to take up a sport for the
first time. Thus existing travellers may make longer trips and new trips may be
generated. Both of these events would be classified by a measure of travel as a
worsening of accessibility which conflicts with criterion 4. Criterion 5 also can be
seen to be violated by considering the similar effects on travel of the provision of a
new bus service to on existing Sports centre. Although other problems with this
type of measure could be identified, the crucial one is their assumption that
existing levels of travel are the desired levels of travel; in other words that travel is
not constrained by the existing transport and land-use system.
The aggregate and disaggregate approaches described in Sections 5.4 and 5.5
remain to be considered. In their basic form all these measures satisfy all six
criteria. However none are completely satisfactory. They were developed to
measure several different aspects of accessibility in response to the identification
of a number of different problems, and are useful measures provided they are
used in on appropriate way for the appropriate type of problem.
There are three quite common variants of several of these measures and it is
useful here to describe their consequences. The first is the population weighted
measure; that is, the accessibilities of the various categories of people have been
added together with Each accessibility weighted by the number of people in that
category. It is the approach of this master thesis that accessibility is fundamentally
a characteristic of on area, a category of person and on activity or set of activities.
One way of assigning the relative importance of the person categories is to weight
each by the number of people in that category. However this is not the only way; it
may be that only one category is of interest, or that accessibility is seen as having
a stronger effect on the lives of some people than on others. Thus it is preferable
to calculate accessibility indices for each person-type without regard initially to the
characteristics of the population of the study area and then, if it is necessary to
amalgamate the indices, to do this by whatever scheme of priorities is deemed
most appropriate. However the limitations of the available data may mean that this
disaggregate approach is not possible. The second variant is the use of the actual
numbers or proportions of people using the different modes or travelling to
different destinations or travelling for different purposes. Similar comments to
those made on population weighting apply here also. The third common variant is
the use of the proportions of the activities of the entire study area in a zone rather
than the absolute number. This goes against criterion 4 as can be seen by
considering the effect of the introduction of a number of opportunities far from the
origin zone. Thus this variation is inappropriate if land-use changes are to be
included in the study.
7.5.2 Contour measures. These measures aim to describe the transport and
Land-use system from the user's point of view. They incorporate, in a
disaggregate way, two important elements of the transport and land-use System;
namely the difficulty of travel between places and the location of facilities. Their
approach is disaggregate in that no attempt is made to evaluate the combined
effect of the competing influences of the attraction of destinations and the
deterrence of travelling to them due to their separation. Furthermore, they do not
attempt to evaluate the benefit people attach to being able to reach a destination,
nor do they evaluate the deterrence attached by people to the travelling required
to reach the activity. Consequently the parameters for the contours must be
chosen realistically. For example it would be unrealistic to calculate travel time
contours of the number of grocers' shops within two hours but it might be
reasonable to calculate the number within 10 and 20 minutes. The data required
for these measures are comparatively readily available.
The first such method, described in Section 5.4.3, aims to do this by looking at
property values or rents. The approach is limited to those types of accessibility
(such as access to employment) which may affect property values sufficiently for
the effect to be measurable. The accurate identification and measurement of the
other factors affecting property values is required in order to measure the
accessibility element of property values.
The consumer Surplus approach (see Section 5.4.4) is orientated more towards
the transport System than the previous approach and has developed from travel
demand model. It aims to measure the total net benefit or consumer surplus (i.e.
gross benefit less cost of travel) obtained by travellers from the transport and
Land-use System. The-principle is that a person will travel to a particular
destination only if the net benefit he achieves is positive. If a change is made to
either or both of the transport and Land-use systems, changes will be made to the
consumer Surplus which some people can achieve and this will be reflected in the
trips they make. Thus by studying the changes in trip making as a result of
transport or Land-use changes it is possible to measure the associated change in
consumer surplus. This method cannot measure the total benefit that travellers
achieve from any particular transport and Land-use system, only the change in
benefit they achieve when a change is made in either or both of the transport and
land-use elements of the system. It can say little about those who use the System
neither before nor after the changes.
7.5.4 Hansen measures. Hansen's original index was developed using intuitive
arguments about the relation between the attractiveness of destinations and the
reduction of this attraction due to the difficulty of travelling to them. The result is a
measure of ’equivalent attraction'; that is the number of units of attraction which, if
located at the origin, would be equivalent to the attractiveness of the spatially
distributed activities.
The Hansen measure for a particular activity is concerned with access to all
the relevant opportunities in the study area. This may be appropriate for some
activities (jobs, for example) but is less satisfactory for activities (such as hospital,
post office) for which the only one of interest is the nearest, or for shops where
the nearest few shops may be the only relevant ones.
The general form of the singly constrained gravity model is thus similar to that
of the Hansen index in that the basis of each is a product of the opportunities
available in each zone and a function of the cost of reaching the zone. Their aims,
however, are different and thus the detailed forms differ. In particular the aims of
the travel cost functions differ. In the gravity model the aim of this function is to
represent the decay in the amount of travel as the cost of travel increases. The
function is usually a negative exponential, e -bc, where c is travel cost and b is a
constant whose value is determined by calibration with the observed distribution of
travel in the study area. In the Hansen index, however, this function aims to
represent the decline in a person's perception of the attractiveness of on
opportunity as the cost of reaching it increases. It is likely that there is some
connection between these two concepts but they are nevertheless distinct. The
travel decay function from a travel demand model is sometimes used as the decay
function in a Hansen index. This would be valid only if the observed distribution of
travel were unconstrained and thus the same as the desired distribution, which is
generally not so. It is not clear how the Hansen decay function can best be
determined.
In summary, the Hansen index uses intuitive ideas about the ’equivalent
attractiveness' of spatially separated activities, it is more appropriate to some
activities than to others and in practice it tends to be used with variables and
functions taken from data collected for travel demand modelling and from the
calibration of the model to the observed data.