urban form, transport infrastructure and individual travel patterns

Paul Melenhorst © 2012 1

2 3571115

Introduction Consideration

Urban FormTransport Networks

Psychosocial DemographicsConclusion

2012paul melenhorst

IndividualTravel Patterns


Factors effecting individual travel patterns

Paul Melenhorst

Australia’s current travel patterns are largely the result of

land use and transport planning decisions that were made

in the heady days of post World War II prosperity (Laird and

Newman, 2001, 14) and founded on building road capacity

to meet the demands of a growing car population (Curtis,

2005, 448). Without the benefit of any serious discourse

on the relative merits of compact versus dispersed urban

structure, an auto-centric urban society was seen as a fait

accompli and accepted without question (Kelly, 2011, 11).

This default position has meant that automobiles now

account for about 70% of travel in Australia’s urban

centres (Mees, Sorupia and Stone, 2007, 3) - even

higher, at almost 90% (City of Casey, 2011, 2) in the City

of Casey, the area under scrutiny in this paper. Given

this background, an analysis of factors influencing travel

patterns must be made in the context of a society heavily

biased in favour of car mobility.

Decisions that people make about how they will travel are

based on accessibility – the relationship between land use

and transport networks and the capacity of these networks

to fulfil activities and opportunities (Francis and Ramsay,

2011, 3). However, spatial variables, a person’s cultural

heritage, health, social status, gender and age will also

impact on individual travel patterns, perhaps even more

This essay investigates the literature around factors that influence individual travel behavior. It considers variables in the research, before considering aspects of urban form, transport infrastructure and psychosocial demographics with reference to different areas in the City of Casey. In conclusion, the relative importance of each factor is considered.

INTRODUCTION


so. Factors relating to psycho-social demographics, whilst

less tangible than lack of a bicycle path or the promise of a

new bypass, also contribute to the decision to use horse-

power, pedal power or otherwise and, therefore these

must also be considered.

This travel pattern analysis refers to a 15 km2 area in

the City of Casey that includes Berwick Village (from the

original precinct analysis), the super regional shopping

centre Fountain Gate, and two residential neighbourhoods

in Harkaway and Berwick South. Urban form and transport

networks vary across these precincts from formal grid

layouts in Berwick Village to organic and ‘non-leaking’ cul-

de-sacs (Cozens and Hillier, 2008, 5) in Berwick South.

Whilst spatial factors vary across the area, psychosocial

demographics are more constant.

CONSIDERATIONS

Deconstructing factors that influence travel behaviour is

potentially a ‘wicked’ process with problems of shared

and unstructured jurisdiction, nebulous interrelationships

and potentially a result where there is no agreed position.

Causation is an issue. Ascertaining what actually

influences travel behaviour is an innately difficult

exercise. Rutherford, McCormack and Wilkinson (1996)

conclude in a comparative analysis that whilst evidence

indicates that people travel differently in different mixed-

use neighbourhoods, it does not follow that these

neighbourhood characteristics are necessarily responsible.

And Crane (2000, 8) notes that it is not possible to

determine the relative importance of differences between

individual and group travel behaviour, therefore ‘identifying

how much of the observed behavior is influenced by the

Above: The study area located in Berwick and Metropolitan Melbourne.source: P. Melenhorst. Adapted from Googlemaps

Fountain Gate

Berwick South Berwick Village

Harkaway


street configuration or any specific design feature alone is

also impossible.’

As well, most current research has a narrow focus,

concentrating on the white majority populace (Curtis and

Perkins, 2006, 14), whereas there are subgroups outside

of this demographic, whose language and semiotics,

religious doctrine will impact differently on how and why

they choose transportation.

And this is a contested area with researchers sometimes

disagreeing over key factors (Lewis, 1999; Crane, 2000;

Crane and Chatman, 2003; Mees, 2010; Gordon and

Richardson, 2001). This is still an area that requires further

research in developing a sufficient understanding of the

relationship of urban and transport infrastructure and

demographics to travel patterns.

With these considerations in mind, two major groups of

factors are associated with transportation patterns; the

spatial variables of urban form and transport infrastructure;

and community variables defined as psychosocial

demographics.

factors effecting

travel patterns

psycho-social

factors

urbanform

factors

transportnetworkfactors

safety

sustain-ability

status & income`

gender

age

autonomy

socio-economics

household composition

status quo

locationstructure & layout

land use mix

physical features

develop-ment

density

road hierarchy &

networkparking

road &fuel

pricing

active transit

structures

publictransit

structures

technology advances

Above: Cognitive map of major variables influencing travel patterns.source: P. Melenhorst


URBAN FORM

The urban form and design of a city – its location, land use

mix, size and morphology, density and physical features –

all impact on the decisions people make when travelling

and commuting. Cervaro and Kockelman (1997, 199)

have referred to these as the ‘three Ds’ of density, diversity

and design, with the more recent addition of destination

accessibility and distance to transit (City of New York,

2010, 22) being used to analyse travel patterns. Casey’s

urban form is mostly conventional low density, single

use urban infrastructure with areas like Fountain Gate,

Harkaway and Berwick South located beyond any local

walkable catchments.

Location

Casey demonstrates a strong correlation between location

and vehicle dependence. As a sprawling suburb, particularly

Harkaway and Berwick South tend to be removed from

activity centres, therefore more dependent on motorised

transport. Curtis and Perkins (2006, 9), referring to a

study by Soltani and Primerano (2005) note sparse low-

density communities, away from local shopping and other

activities, restrict the capacity of residents ‘to walk or cycle

for their daily travel requirements’. This is in contrast to

residents who are close to activity and transit nodes where

higher rates of walking or cycling are observed (Naess and

Jensen, 2004).

Marchetti (1994), quantifies this by establishes a maximum

‘budget time’ of approximately one hour that people

will travel in order to get to work. When a destination is

more than one hour from the origin – the ‘Marchetti wall’ -

people will tend to move to a faster transportation mode.

Casey is 45km from Melbourne’s monocentric CAD with

no transport mode falling inside this theoretical wall.

Land Use Mix and Density

Land use diversity also influences individual travel patterns

through the accessibility of facilities and services such

as ‘employment, education, health and other services’

(Francis and Ramsay, 2011, 3). Sixty percent of car trip

from within Casey are to destinations outside of the City

(ABS, 2006a), which suggests land use mix is poor,

Right. TOD (transport oriented design) guidelines suggest a walking catchment of five minutes (400 metres) from a railway node. Marchetti (1994) suggests that an average travel time budget is about one hour wide. This is the event horizon at which people are hesitant to travel much further. Presuming that journeys terminate at a concentric hub, people will stop walking at about 8km which is about average walking speed; stop using public transit at about 30km which is the average speed of a train; and stop driving at about 50km which is the average speed of a car.

Commuting distances from the precincts under question to Melbourne’s CAD are about 45km, placing the City of Casey outside this theoretical wall.source: P. Melenhorst. Data from Newman and Kenworthy (2011)

8km

50km

30km

Paul Melenhorst © 2012 6Residential streets without active transport infrastructure

Top: Cul-de-sac strreet in Berwick south (source: P. Melenhorst)

Centre: Residential streets surrounding Fountain Gate(source: realestate.com.au)

Bottom: Low density residential zoning in Harkaway(source: P. Melenhorst)


limiting opportunities for active transport. Fountain Gate,

as a Principal Activity Centre, is particularly poor, forcing

users to use motorized transport because of the lack of

residential and public realm uses. (PDP 2009)

As well as an accessible mix, the positioning of services is

important. Blom (1992) notes, for example, that a labour-

intensive office development is better placed at a destination

transport node, than, say, an equivalent residential urban

development. This is because egress travel supports short

car or bicycle trips to the point of departure (parking at a

railway station or locking a bicycle), whereas these are not

options at the destination, such as an office building. Casey’s

transit points are origin nodes for travel to Melbourne’s CAD.

However, all three stations are located in retail/commercial

rather than residential areas so distance to transit measures

are more than 600 metres, discouraging walking.

As well as land use mix, population and development

density is a common yardstick for calculating travel

usage. The City of Casey’s urban density is relatively

uniform averaging 10 dwellings per hectare (Buxton and

Scheurer 2007, 15) with Harkaway less than one dwelling

per hectare. Such low density means that services are

fragmented and often only within reach by motorized

transport. Increasing land use density would improve

accessibility as services and infrastructure are clustered

into more concentrated areas. With this higher degree of

access, there tends to be shorter trips, which, it is argued,

may incentivise people to shift travel mode to walking.

Newman and Kenworthy (2011) cite increases in urban

density as one reason why the modal split is changing

from motorized transport to active and public transport.

This corresponds to Casey where densities are low and

motorized transport usage high.

There are various authors such as Kockelman (1991, 12)

and Crane (2000, 6) however who note that density as a

single variable, is a simplistic algorithm that fails to capture

complex interrelationships between urban form factors.

Crane explains that density, land use mix and location will

decrease the distance between trip origin and destination,

as they are physically closer together, however, whilst the

amount people drive (VMT) will decrease, it does not also

follow that travel modes will change or the number of trips

decrease.

And McLoughlin (1991) and Lewis (1999) have argued

that, for outer urban areas, such as Berwick South and

Harkaway, increases in density will have little impact on

urban sprawl issues like car usage as infrastructure and

services such as roads remain almost constant. To reduce

such an allocation would “make a direct assault on those

qualities that make Melbourne liveable” (Lewis, 1999, 117).

Furthermore, Mees (2010, 41) indicates that there is little

evidence tying urban density and sustainable transport

share together with cities from across North America and

Australia showing no correlation between density and

public/active transport percentages. What in fact maybe

occurring is what Curtis and Perkins (2006, 6) refer to

as ‘locational self-selection’ where suburbs with higher

densities, mixed use and good permeability attract like-

minded residents, who already walk, cycle and use public

transport, rather than changing individual travel patterns to

more sustainable modes.

TRANSPORT NETWORKS

The transport networks of a city – the road hierarchy,

the type of road network, pricing, sustainable transport

networks, and advances in technology – all impact on the


decisions people make when traveling and commuting.

Road Hierarchy and Network

A comprehensive matrix of arterial roads, local streets

and laneways, and off-road cycle and pedestrian tracks

will cater for multi-modal transit and encourage a mix of

motorized and sustainable travel.

As one of Australia’s fastest growing municipalities,

Casey’s road networks are acknowledged as congested

with arterial road usage increasing travel times, (thereby

reducing productive and social time), increasing operating

costs and user uncertainty (Curtin, 2012, 13) and negatively

impacting on adjacent local communities by encouraging

inappropriate through traffic. Efficient and comprehensive

road infrastructure, however, improves service as volume-

capacity ratios are decreased, which will impact on an

individual’s road mobility and therefore travel patterns.

This is a double-edged sword, though, as increased road

capacity also has the function of increasing traffic volumes –

additional roads attract additional drivers – which ultimately

contributes to congestion (Hansen et al, 1999).

As well as the road hierarchy, the type of road network in

a precinct will influence vehicle and sustainable transport

behaviour with a gridded network, as opposed to organic

networks and leaking and non-leaking cul-de-sacs more

able to ‘facilitate walking, cycling and the use of public

transport… and enable relatively direct local vehicle trips’

(WAPC, 2009, 34).

Gridded networks also potentially reduce local trips in a

community. Kulash (1990) has established a reduction of

43% (expressed in VMT – vehicle miles travelled) due to the

higher degree of accessibility provided by such a network,

and McNally and Ryan (1993) suggest a reduction of

10.6% in VMT when a conventional network becomes a

‘highly interconnected street system’.

However, gridded networks, with their connectivity

and permeability, are more prone to safety issues for

pedestrians than cul-de-sac networks where it is less easy

to transit through (Town et al., 2003 ; Poyner and Webb,

1991). Cozens and Hillier (2008, 11) note that ‘permeable

street layouts are subject to higher levels of crime than

less permeable layouts, such as non-leaking cul-de-sacs’

which may be a factor in people choosing to drive over

walking, particularly at night.

Parking and Road Pricing

Parking levies and increased pricing aims to reduce

congestion in inner city areas by discouraging commuters

from driving. These ‘push’ techniques - are aimed at making

car usage less appealing and includes increased taxes

on fuel, tolls on roads, decreased parking and increased

parking prices. For example, the Victorian Government’s

introduction of a levy in Melbourne’s CAD has seen ‘a

significant increase in the number of people coming to the

city by public transport (Hamer, Currie and Young, 2011,

13). And studies by Hensher and King (2001), and Handy

et al (2005) have found that the cost of parking in inner city

areas to be the most significant determinant in transport

modal switch to public transit.

Outside of central activity districts, such as the City

of Casey, where there is competition between activity

centres, this may not be the case. Clark (2005, 3) notes

that ‘market mechanisms that seek to price people out of

their cars may have the contrary effect of increasing car

use, at least in the short term, as people opt to drive to

destinations that have free parking’.


Clockwise from top: People queing at the Fountain Gate bus stop. There are 5200 car parking spaces at Fountain Gate, Victoria’s second largest shopping centre, yet no seating and weather cover at this bus stop.(source: Public Transport Users Association)

Fountain Gate is enclosed on three sides by arterial roads, cutting the precinct off from active transport.(source: fitzroys.com.au)

Residential streets, however no active transport access – on the Casey line.(source: railpage.com.au)

Narre Warren railway station, as a transit node cannot cope with vehicle traffic volumes.(source: railpage.com.au)


This would certainly be the case in Berwick Village and

Fountain Gate, where currently parking is free. Parking

deterrents would drive, quite literally, people to competing

strip shops and shopping malls that have free peak parking

demand facilities.

Sustainable Transport Infrastructure

A complex of public transport routes and services allow

people to choose transport options that best align with

their travel requirements. Casey’s transport infrastructure

polarizes users through limited sustainable transport

infrastructure with its railways stations located in low-

density commercial/retail areas, rather than dense, mixed

use precincts. There is the only one dedicated cycling route,

the Hallam Bypass Trail (City of Casey, n. d.), However this

does not connect to any transit nodes, limiting its use for

commuting. Footpaths are comprehensive in Berwick

Village but the cul-de-sacs of Berwick South are not

comprehensive and Harkaway and Fountain Gate are very

limited PTUA (Public Transport Users Association statistics

(2010). The Fountain Gate precinct is particularly difficult

for active transport users to navigate, being surrounded on

three sides by primary and district distributor roads, and

access through vehicle access. And it is not located on a

railway line with the nearest station 1.5km away.

Mess and Dodson (2011, 2) note that the way a public

transport network is structured is integral as to how it will

be used describing good public transport as being reliable

and fast, and having a diversity of line haul, cross town and

local feeder services (Curtin University, 2012b). As well,

‘pull’ techniques (Van Wee and van der Hoorn, 1996, 82)

such as a logical ticketing system, end of journey bicycle

facilities, legible wayfinding, sufficient cover from weather,

adequate parking and a good general amenity can

mitigate travel behaviour. (Queensland Transport, 2008).

This ‘transit leverage’ effect is confirmed by Newman and

Kenworthy (2011), indicating an inverse proportionality

between car use and public transport use. And Holtzclaw

(1994) notes that a doubling of transit accessibility (the

number of bus and rails seats per hour) can reduce VMT

per household by eight percent.

Transit leverage extends to good pedestrian infrastructure

that encourages walking as a component of commuting

(Cervero, 2002), however it is questionable whether

improved bicycle infrastructure reduces car usage. Mees,

Sorupia and Stone (2007, 3) argue that cycling, as a transit

mode does not appear to effect car use, rather impacting

on the share of walking and public transport users. This is

because there is a disconnect between a bicycle’s average

commuting length and people’s actual average commute

lengths. Ironically, Gordon and Richardson (1998, 10) note

that there is stronger correlation between cycling and car

use than between cycling and transit, giving the example

of the cyclist who drives 30 miles in order to ride along a

beach promenade!

Advances in Technology

Continued advances in fuel technologies (Parbo, 1997,

108), engine efficiency and power trains (Granovskii,

Dincer and Rosen, 2006, 411) have already made

cars less environmentally damaging. However, these

incremental changes will not substantially change mode

share away from cars (and, in fact, may encourage driving,

if environmental issues become less critical).

What is more significant are long term waves of

innovation (known as Kondratiev Cycles (Nogrady, 2010)

corresponding with major technological innovations that

include transportation. Marchetti (1993, 88) notes how

dominant transportation modes, based on increased


speed, have changed with each new innovation cycle

(e.g. horse to carriage to automobile) and predicts the

introduction of a new form of transportation, such as the

Maglev (magnetic levitation vehicle) replacing trains and

cars. Obviously this is speculative, however the underlying

position that innovation impels changes in transportation

usage is an important factor to consider.

PSYCHOSOCIAL DEMOGRAPHICS

Much of the research suggests the decisions people make

when choosing transportation are not so much guided by

urban networks, but grounded in cultural predispositions,

political bias and a person’s age, gender and heritage.

This factor is expressed in issues of safety, income and

household composition, gender and age, status and

status quo.

Transport and Safety

Perceptions of safety or risk will influence personal travel

choice. Despite the inherent dangers of higher speed

motorized travel, cars are often seen as offering the safety

of a ‘comfortable cocoon’ (Hiscock et al (2002, 119), and

an ‘ontological security’ that is not available with public

transport. Obversely, public travel is perceived as riskier,

particularly at night. A national police survey (Victoria

Police, 2011) found that only 35.7% of people felt safe

using public transport at night compared with 82.6% of

people during the day.

Some of this reticence is however justified, particularly in

Victoria (and well represented by the City of Casey) where

transit crime is double that for NSW (More danger on

trains in Melbourne than in London or New York, 2008).

Bus transit has similar problems with Loukaitou-Sideris

Uniting

No Religion

Catholic

Presbyterian

R E L I G I O U S A F F I L I A T I O N I N C A S E Y

Anglican

EnglandNew ZealandSri LankaScotland

Australia

India

C O U N T R Y O F B I R T H I N C A S E Y

0-4

25-54

55-64

65+

A G E D I S T R I B U T I O N I N C A S E Y

5-14

15-24

males

females

indigenous

P E R S O N A L C H A R A C T E R I S T I C S I N C A S E Y

hours not stated

part-time

full-time

unemployed

L A B O U R F O R C E E M P L O Y M E N T I N C A S E Y

away from work Clerical/

administrative

Technicians/trades

Community

Labourers

Managers

Machineryoperators

O C C U P A T I O N I N B E R W I C K

ProfessionalsSales

Not stated

Being purchased

Fully owned

O C C U P I E D P R I V A T E D W E L L I N G S I N C A S E Y

Other tenure

Rented

Separated/divorced

Married Widowed

M A R I T A L S T A T U S I N C A S E Y

Never /married

Uniting

No Religion

Catholic

Presbyterian


Anglican


Australia

India


0-4

25-54

55-64

65+


5-14

15-24

males

females

indigenous


hours not stated

part-time

full-time

unemployed



administrative

Technicians/trades

Community

Labourers

Managers

Machineryoperators


ProfessionalsSales

Not stated

Being purchased

Fully owned


Other tenure

Rented

Separated/divorced

Married Widowed


Never /married

Uniting

No Religion

Catholic

Presbyterian


Anglican


Australia

India


0-4

25-54

55-64

65+


5-14

15-24

males

females

indigenous


hours not stated

part-time

full-time

unemployed



administrative

Technicians/trades

Community

Labourers

Managers

Machineryoperators


ProfessionalsSales

Not stated

Being purchased

Fully owned


Other tenure

Rented

Separated/divorced

Married Widowed


Never /married

Uniting

No Religion

Catholic

Presbyterian


Anglican


Australia

India


0-4

25-54

55-64

65+


5-14

15-24

males

females

indigenous


hours not stated

part-time

full-time

unemployed



administrative

Technicians/trades

Community

Labourers

Managers

Machineryoperators


ProfessionalsSales

Not stated

Being purchased

Fully owned


Other tenure

Rented

Separated/divorced

Married Widowed


Never /married

Above: Census data indicates that Casey is a homogenous demographic (source: P. Melenhorst Data from ABS 2006 Census QuickStats)


(1999) noting that most serious crimes committed at bus

stops occur late at night when passive surveillance is at

its lowest.

Household Income and Composition

Individual travel patterns are also influenced by household

income and composition. Income dictates housing and

rental decisions that impact on the transport decisions

people make. This trade off is particularly salient in newly

established outer suburbs, such as Berwick South,

where housing costs are less but sustainable transport

infrastructure is limited (Crane and Chatman, 2003). The

Vampire Index (Vulnerability Assessment for Mortgage,

Petrol and Inflation Risks and Expenditure) (Dodson

and Snipe, 2006, 21) indicates that parts of the City of

Casey are prone to pressures from fluctuations in housing

mortgage rates and fuel prices, particularly with such high

VMT numbers.

The addition of children and students with the requirements

of childcare and school also impact on personal transport

decisions. Casey’s median age is 33 years (compared with

an Australian average of 37 years), therefore a greater

reliance on motorized transport is expected. Casey also

has lower than average levels of unemployment at 3.6%

and part time work at 26.8% (ABS, 2006b), which are two

groups more likely to use non-motorized transport. (Ryley,

2005)

Status and Lifestyle

Another factor driving the attachment to the car is the

lifestyle associations of ownership. Curtis (2005, 444)

notes the burgeoning popularity of the car in the 1950s

was not just a transport phenomenon but intimately tied to

ideas of prosperity and modernity, with ‘public-transport

provision seen as serving only a social welfare function’.

This is largely still the attitude with Mees, Sorupia and

Stone (2007, 19) citing places such as Hobart where even

policy-makers see buses as ‘a social service for people

with no alternative’ rather than as a viable transit option.

This message of inadequacy and deficiency – public

transport’s perception as slow, infrequent and unreliable

(Hamilton et al, 1991) – makes it unable to meet people’s

desire to determine their own travel patterns. This is unlike

the automobile, which has perceived benefits of autonomy

and prestige (Hiscock et al, 2002, 119) and, ironically,

notions of mass-produced individuality and escape from a

car-induced congestion (Cullinane, 2002).

Gender and Age

Individual travel patterns are also influenced by gender and

age, with women and retirees more likely to demonstrate

sustainable travel behaviour, but for different reasons.

Women are more prepared to make changes to their travel

patterns for environmental reasons (Curtis and Perkins,

2006, 13), which is borne out by ABS statistics from 1976-

2006 (Mees Sorupia and Stone, 2007) that indicate both

driving and cycling mode shares are disproportionately

represented by males. And the elderly also make changes,

however this is a function of the ‘empty nester’ syndrome

where retirees migrate from outer suburbs back into higher

density inner suburbs and as a result drive less (Leinberger,

2007; Puentes and Tomer, 2009). This could also be

because they are now not commuting. Berwick Village has

a number of retirement villages in close proximity to both

transit and activity nodes, which aligns with this trend.

Territoriality and the Status Quo

A socio-demographic factor not as often considered is

the underlying territoriality of humans. Lee et al. (2006,

18) argues that current transportation patterns and the

intransigence of consumer preference for the car are


Left. The VAMPIRE (Vulnerability

Risks and Expenditure) index provides valuable information for considering the overall stress on a household. This map of Melbourne has green representing the lowest level of vulnerability and red indicating the highest. Source: Dodson and Sipe (2006)

Casey has a heterogenous spread with disproportionate representation under the highest levels of stress.The percentage of families paying off high mortgages in the south of Berwick is a key factor contributing to this situation. Source: P. Melenhorst

City of CaseyVampire index

19 -22

17 - 19

15 - 17

10 -15

1 - 10

Paul Melenhorst © 2012 14Top: An insightful bumper sticker that makes the connection between the current economic paradigm and the requirements of auto-consumption.(source: Joost, www. flickr.com)

Middle, bottom: Current car marketing offers consumers perceived benefits of autonomy prestige and escape over sustainable transit alternatives.(source: mitsubishi.com.au, nissan.comau, toyota.com.au)


simply a reflection of people’s preference for dispersed

auto-driven socialization, rather than the New Urbanist

argument for a compact, intimate community. Gordon

(Moore and Henderson, 1998, 3) from the University

of Southern California, referring to US Department of

Transportation statistics that count 60 percent of trips by

car for social reasons (church, family, sport, recreation),

asserts that we don’t actually want the community

intimacy that is required for active transport. Rather,

‘people are getting the neighbourhoods they want’ where

the automobile or even the Internet are used to meet the

demand for community.

CONCLUSION

Current knowledge indicates that spatial factors such as

urban form and transport networks, and psychosocial

variables such as economic status, gender, ethnicity, and

identification with a peer group contribute to moulding

individual travel behaviour.

Whilst these factors have been identified, evidence is still

emerging and often contested, such as ‘the relationship

between design and physical activity’ (City of New York,

2010, 24), the component influences of density compared

to land use diversity, or urban design compared to

distance to transit nodes. This also includes the impact

of variables such as sprawl, bicycle infrastructure and

parking, and planning typologies such as New Urbanism

and Smart Growth.

Despite disputed terrain, however, it would seem that

psychosocial demographics are more significant in

moulding travel patterns than the urban structure of a city.

Stead et al. (2000) suggest this, concluding that ‘about

half the variation in travel patterns (is) explained by socio-

economic patterns and around a third explained by land

use characteristics’. This fits with observations and ABS

data for the City of Casey that finds individual transport

patterns to be fairly uniform across precincts despite the

variation in urban form and transport networks. Regardless

of the ranking of importance, however, all of these factors

shape a city’s accessibility and influence the travel patterns

of its residents.


– More danger on trains in Melbourne than in London or New York, 2008. http://www.news.com.au/heraldsun/story/0,21985,24327935-661,00.html (accessed July 20, 2012)

ABS (Australian Bureau of Statistics) 2006a. State Suburb (SSC) by Sex Male/Female (SEXP) and Individual Income (weekly) (INCP). 2006. Berwick (State Suburb) by Census Collection District. http://www.abs.gov.au (accessed July 29, 2012)

ABS (Australian Bureau of Statistics). 2006b. People who travelled to work by Car. As a percentage of all employed people. Based on Place of Usual Residence, 2006 Berwick (State Suburb) by Census Collection District. http://www.abs.gov.au (accessed July 29, 2012)

Blom, J.A. 1982. ‘Werkgelenheidslokaties en vervoerwijzekeuze’ (Employment locations and modal split), Ministerie van verker enwaterstaat/Projectbureau lntegrale Verkeers-n Vervoersstudies, Den Haag. Quoted in Van Wee and van der Hoorn (1996, 85).

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urban form, transport infrastructure and individual travel patterns

Documents

van der hoorn

census collection

sustainable

transportation

decisions

travel behaviour

victoria police

active transport