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Clothing the Emperor?: Transport modelling and decision-making in Australian cities

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In no field of planning is there more reliance on technical-rational decision-making processes than transportation planning. In Australian cities transport planners still heavily rely upon complex, quantitative transport models, especially the four-step model (FSM) and its variants, used at the regional, metropolitan and corridor levels of analysis. While it is beyond the scope of this paper to provide a detailed critique of each stage of the FSM, there are numerous problems with its use that need to be addressed. This paper examines the empirical shortfalls of the technical-rational process, highlighting the reliance on a select few experts, limited public participation in modelling processes, and decision-makers who have little understanding of the methodological limitations inherent in transport modelling advice. Model deficiencies do not allow for, and may actually impede consideration of many of the most important emerging issues within cities, including road pricing, climate change and oil vulnerability, as well as long-held concerns such as land use changes, induced travel, the environment and sustainability. This paper identifies numerous inter-related concerns about the broader policy and political dimensions of technical-rational decision-making in the transport sector, and recognises the main tools used in technical assessments. Yes Yes
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Clothing the Emperor?: Transport modelling and decision-making
in Australian cities
Rick Evans1, Matthew Burke1 and Jago Dodson1
1 Urban Research Program, Griffith University
Abstract: In no field of planning is there more reliance on technical-rational decision-making
processes than transportation planning. In Australian cities transport planners still heavily rely upon
complex, quantitative transport models, especially the four-step model (FSM) and its variants, used at
the regional, metropolitan and corridor levels of analysis. While it is beyond the scope of this paper to
provide a detailed critique of each stage of the FSM, there are numerous problems with its use that
need to be addressed. This paper examines the empirical shortfalls of the technical-rational process,
highlighting the reliance on a select few experts, limited public participation in modelling processes,
and decision-makers who have little understanding of the methodological limitations inherent in
transport modelling advice. Model deficiencies do not allow for, and may actually impede
consideration of many of the most important emerging issues within cities, including road pricing,
climate change and oil vulnerability, as well as long-held concerns such as land use changes, induced
travel, the environment and sustainability. This paper identifies numerous inter-related concerns about
the broader policy and political dimensions of technical-rational decision-making in the transport
sector, and recognises the main tools used in technical assessments.
Introduction
The paper explores the limitations of conventional transport evaluation and analysis and its position
within a broader institutional landscape. The paper argues the technical complexity of conventional
transport models is such that understanding of their internal capacities and limitations is, in most
jurisdictions, restricted to a small number of specialists. When coupled with the inherent inadequacies
of transport modelling, this technical complexity may be seen to create a form of institutional risk for
transport planning. This observation has implications for the quality of transport planning in cities.
The paper first considers transport planning and the role of technical-rational evaluation. Issues
pertaining to the broader political and policy dimensions of transport assessments are explored,
highlighting recent research into these issues. The particular problems of transport modelling,
especially the conventional four-step model (FSM), are then discussed, highlighting both the known
and well-understood concerns, such as induced traffic, as well as a range of new and emergent issues
that modelling may not be well suited to appraising. The paper concludes with an outline of further
research possibilities in the Australian context.
Transport planning: Techno-institutional views
Has any policy field relied on technical-rational evaluation methods more than transport planning?
Since the 1950s there has been an intense focus in transport planning on technical appraisal and
modelling to solve problems of movement, often at the expense of other potential influences. And at
the heart have been large city-wide strategic transport models, used to forecast travel flows and to test
project or policy scenarios.
Modelling’s influence on decisions is certainly less than during the excessively pro-roads 1960s, when
land use and transport studies such as the 1965 Brisbane Transportation Study (Wilbur Smith and
Associates, 1965) sought to reshape the inner-cities of Australian cities for urban motorway networks.
Indeed, in recent decades both transport models and transport planners have receded somewhat from
the public eye, their names generally unknown. But they are still used to inform every major transport
investment or strategic plan. That is not to say that model outputs necessarily dictate transport policy
and project decisions – models have ‘an ambiguous role in the choice of transport plan or policy’
(Talvitie, 2006, p.84). And they may serve to legitimate particular projects that have been selected on
a political rather than technical basis. Most cynically, Abram (2005) suggests that the use of technical
methods in government policy making is simply ‘politics by other means’. There have been relatively
few studies that seek to comprehend transport technical assessment as a broader process involving
technical, social and political dynamics. Vigar’s (2002; 2006) work is perhaps the most developed in
this regard, demonstrating how technical assessments in the UK have been used both to design road
schemes and also to frame debates, focusing discourse on highway capacities, on ‘schemes’ and on
‘hard’ engineering projects (Vigar, 2002, pp.106-107). Mees and Dodson (2007) have also
ISBN 978-0-646-48194-4 SOAC 2007418
demonstrated how technical studies and the assumptions and calibrations underpinning them have
been used to shape and distort political and public preferences in strategic transport analysis.
It remains the case that in Australian cities, the majority of strategic transport plans and project
investment decisions are invariably developed using guidance from complex and highly technical
computer-based models such as the Melbourne Integrated Transport Model (MITM), the Brisbane
Strategic Transport Model (BSTM) and the Strategic Transport Model of Sydney (STM). These
models assist in developing the future transport networks for the metropolitan strategies that now
guide urban growth and investment in each of the Australian mainland capital cities. Models are also
typically used to predict network flows, to develop local transport plans, to appraise specific
investments, to identify ‘corridor’ opportunities, to provide the necessary inputs to environmental
impact assessments of projects, and for many other purposes. The technical-rational processes
inherent in such models mean that by their nature their use must be ‘expert-led’, and typically involve
a narrow range of participants’ using highly quantitative, complex modelling procedures (Vigar, 2006,
p.269). Though the use of models is somewhat inevitable (Ortuzar and Willumsen 1990, p.2) the
technical basis for such modelling processes and the level of understanding necessary to comprehend
their internal functions means that knowledge of how the models work and their capacities, and in turn
their biases and inadequacies, are often restricted to a small number of professional experts. The
technical complexity of transport assessment methodologies imbues these systems with the
appearance of objectivity and universality. Yet the policy context in which transport decisions are
framed and the political circumstances surrounding these decisions also influence the way
assessment is undertaken and the outcomes of that assessment. Traditional views held by decision
makers, may heavily influence the assumptions that drive transport policy when selecting and creating
new infrastructure and transport options (Low 2003).
Even aside from these broader dimensions, there has been much academic and institutional debate
about the merits of conventional transport modelling per se (e.g. see Beimborn, 1995; Bureau of
Transport Economics, 1998; Cervero, 2006; David Simmonds Consultancy et al., 2000; Litman, 1999;
Noland, 1999; Supernak, 1983). Certainly, models have continued to improve with time – thanks to
increases in computing power and model sophistication – though it is not certain that in practice much
is changing (Noland, 2004, p.18). Indeed, the ruinous demand estimates for some recent Australian
transport projects (e.g. Brisbane’s Airtrain, Sydney’s Cross City Tunnel) reinforce the view that
improved precision isn’t resulting. This isn’t solely an Australian problem – technical analyses of
transport projects are often inaccurate or wrong. Flyvbjerg’s studies (Flyvbjerg et al., 2002; Flyvbjerg
et al., 2003) have demonstrated a wide variation exists between the outputs of transport technical
assessment and the eventual transportation outcomes generated by major roads, bridges, tunnels and
rail links. Flyvbjerg et al (2003) have argued that the broader context for transportation decision-
making influences the way technical assessment is performed. And he suggests that the ‘ambitions’
of project proponents may either explicitly or implicitly shape technical assessment processes with
great potential for ‘strategic misrepresentation’ of the viability of projects. Flyvbjerg et al (2006) have
also identified traffic forecasts as particularly susceptible to these strategic problems such that the
reliance on models itself constitutes a form of risk.
The role of transport modelling in policy processes is represented in Figure 1, which illustrates the
typical organisational hierarchy of a conventional transport planning project in the Australian context.
The detailed technical knowledge of the modelling gradually decreases as the project moves up the
institutional chain, with an inversely increasing amount of political influence affecting the outcomes of
the project. Problems may arise for those higher in the chain where methodological concerns are not
necessarily understood, or where limitations may be ignored.
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Figure 1: Typical organisation of a transport planning project and the influences upon it
Given the influence that transport projects and schemes can have on the shape and function of cities
and the prominence of technical-rational decision-making, the models and the assessment methods
used can have an enormous bearing on urban trajectories. This influence extends to the investment
cost of transport decisions, which can impose heavy burdens on both governments and private
businesses (Flyvbjerg 2003). These issues suggest there are important aspects of transport technical
assessment that deserve scholarly attention.
While the Flyvbjerg et al. (2003; 2002), Vigar (2002) and Mees and Dodson (2007) studies shed some
light on the techno-political nexus of strategic transport assessment, more research is needed to fully
comprehend these processes. An Australian perspective in particular is desperately needed. There is
a further important task to extend inquiry beyond simply the analytical frame of scholarly investigation.
Part of this task involves identifying the capacities and limitations of transport technical assessment
and reporting these to planning and transport policy decision makers to assist with their selection of
strategic and project alternatives.
The remainder of this paper commences this work, examining the technical capacities and
weaknesses of conventional transport modelling, summarising known methodological concerns, and
highlighting emergent issues for transport assessment.
Transport modelling and technical transport planning processes
The predominant methodology used internationally in the technical assessment of urban transport
networks is the ‘Four Step Transport Model’ (FSM), of which the Melbourne, Sydney and Brisbane
models mentioned above are examples. Transport planners have ‘traditionally considered the
relationship between urban structure and travel patterns at the aggregate level’ (Schwanen et al.,
2005, p.17). The FSM uses this approach, seeking to identify future travel demand and predicting the
measures needed to cater for it (Hensher and Button, 2000). The FSM has dominated transport
modelling since the 1960s, and still resides in most comprehensive transport models in various
modified forms (McNally, 2000). The FSM also typically supports cost-benefit analysis for the
Policy
Makers
Professional
Advisors
Steering
Committees
Project
Committee
Project
Manager
Project
Consultant
Political Influence
Technical-rational influence
Decision making
power / reduction
in amount of
consultation
Understanding of
methodological
concerns
420
purposes of making assessments and obtaining justification for policy decisions (Hensher & Button,
2000).
The operational sequence for the FSM is: 1) trip generation, 2) trip distribution, 3) modal split/choice,
and, 4) route/traffic assignment (see Figure 2). It is beyond the scope of this paper to give an
authoritative overview of the process, or to discuss the considerable issues of input data and network
representation, or the use of model outputs for economic or environmental appraisal, important as
those issues are. However a brief outline of the FSM is provided to identify the influence each may
have on transport assessments.
Figure 2: Traditional four-step transport model (adapted from Button, 1977, p.117)
Trip generation
The trip generation step uses population and employment forecasting plus land use planning inputs to
identify the magnitude of future total daily travel, calculated at either the household or zonal level
(McNally, 2000). There are several different methods for calculating total daily travel within the FSM.
These include linear and multiple regression analysis (multiple regression tending to be the most
popular method), and cross-classification or category analysis (Ortuzar & Willumsen, 1990). Variables
used to calculate the number of trips usually includes the number of jobs within zones, the number of
residents, and sometimes other gross activity measures such as tertiary education attractors (Cervero,
2006).
Methodological concerns of trip generation models are many. Travel is grossly simplified into only few
trip types (often only 4 or 5), with often no discrimination between pedestrian-likely trips and motor
vehicle trips (Beimborn, 1995; Beimborn et al. 1996). Trip-chaining behaviours, whereby persons
combine multiple destinations such as work and shopping into their travel from home, are ignored due
to the complex nature of such trips (Beimborn, 1996, p.16; Lee and McNally, 2006, p.554). Spatial
environmental variables known to influence travel behaviour, such as resident and employment
density, land use mixing, and ease of non-motorised accessibility, are rarely considered (Cervero,
2006). Trip zones are often large, limiting any potential to consider short distance walking and cycling
trips (Cervero, 2006). These concerns limit the predictive capacity of the FSM in general, but are of
especial concern for modelling of contemporary land use and transport interventions, such as transit-
oriented development, with which the FSM struggles.
Trip distribution
Trip distribution takes the outputs from the trip generation stage of the FSM and allocates them to
routes on a transportation network to develop a region-wide origin-destination matrix, better known as
a ‘destination choice model’ (McNally, 2000). The most used method of allocation is the ‘gravity’
model, which assigns travel to various land uses based on their population or employment size and
the separation (usually expressed as travel time) between them.
Land Use Inputs/
Forecasting
Trip Generation
Trip Distribution
Modal Split/Choice
Route Assignment
Planning
Inputs
Road and Public
Transport Networks
Trips arranged by
modal choice
Trips sorted by origin/
destination zones
Trips assigned to links
on a network
421
Methodological concerns include the singular focus on travel times to represent the ‘friction’ of
separation and distance, and the failure to consider socio-cultural factors in destination choice, such
as locality avoidance due to class preferences or crime (Beimborn, 1995). There is typically little
consideration of congestion or other feedback effects when modelling distribution (Beimborn et al.,
1996, p.19). Comparisons with observed data generally find significant errors in the predictions of
gravity models (Ortuzar and Willumsen, 1990, pp.157-158). Intra-zonal trips are also poorly handled,
with households and jobs either modelled as being at one centralised point in each zone, or ignored
(Cervero, 2006). These issues further reduce the precision of the FSM – particularly in regards to the
desired directions and destinations of travel, and considerably affect short trips made via walking and
cycling.
Modal assignment
The modal assignment step assigns the trip numbers derived from the results of the trip distribution
analysis to mode-specific journeys (McNally, 2000). Mode choice models can be aggregate, if they
are based on zonal information, or disaggregate, if based on household or individual data (Ortuzar and
Willumsen, 1990, p.162). Most models today use behaviour-oriented approaches, the most common
of which is the ‘nested logit’ model, that use complex probabilistic mathematical calculations to impute
individual travel mode choices (McNally, 2000). Public transport, due its greater complexity (different
stops, routes, possible interchanges, arrival and departure times of services, etc.) than car travel, is
aggregated to simple networks and average journey and waiting times (Freidrich, 1998, p.12). Most
modal assignment models use relative travel times for public transport modes, representing the time
spent in accessing public transport, waiting time (including at interchanges) and time spent in-vehicle.
Methodological concerns include the naivety of most models to many qualitative features of public
transport services (Beimborn, 1995), and the exclusion or very limited consideration of non-motorised
trips. Most models are insensitive to travel options such as carpooling (Beimborn et al., 1996, p.28).
The focus on interchanges and waiting times, rather than the quality of nodes, to predict the mode
travellers will use is questionable (Cervero, 2006, p.286). The approach is generally seen as
favouring the use of private motor vehicles over alternative modes, despite growing literature that
suggests higher mode shares for public transport and non-motorised travel will result in cities which
have designed quality public transport, walking and cycling infrastructure and systems (Newman and
Kenworthy, 1999, pp.154-159, 162-164).
Route/traffic assignment
The route assignment step assigns the zonal mode trips to specific transport network routes using
complex mathematical operations (McNally, 2000). Performed separately for road and public transport
trips (non-motorised trips are generally ignored) methods are used to assign traffic to specific routes,
usually with capacity constraints modelled, relating the volume of flow to the costs (in travel time) of
each link. Assignment processes generally seek to assign traffic flows to approximate an equilibrium
condition whereby all travellers have minimised their travel costs within the network, such that no one
traveller may further reduce their travel costs by switching routes (Ortuzar and Willumsen, 1990,
p.254).
Methodological concerns include assignment methods generally focusing on link travel times, ignoring
or placing less emphasis on intersection delays. Capacities are often over simplified, neglecting to
allow for such things as heavy vehicle movements or highway geometry. Intra-zonal travel is ignored.
Travel made at different times of day is often readjusted into the peak hour by applying an hour
adjustment factor, and peak hour travel is overemphasised (Beimborn et al., 1996).
Other acknowledged problems of the FSM include poor trip generation assessments due to weak
land-use projections, and limited (or more commonly nil) feedback between transport and land-use
systems. Yet few of these limitations are given much attention in the reporting of transport
assessments. There are both well-known and emergent issues with which transport planners have
been confronted, and with which convention assessment and the FSM have thus far generally failed to
accommodate, to which we now turn.
Further Challenges in Transport Technical Assessment
Beyond the technical problems with the various steps in the FSM identified above, a number of
additional issues have proven difficult for modelling to overcome. And new issues have emerged to
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further confound the transport planning profession. This section briefly outlines some of these
technical and empirical problems.
Induced traffic and travel
The existence of induced traffic and travel has been debated for many years (Noland, 2001).
However the SACTRA (1994) report on the generation of traffic through road construction led to the
general acceptance of induced travel as an irrefutable problem of capacity expansion. Induced traffic
refers to the phenomenon of additional road capacity generating new and generally unpredicted travel,
additional to persons switching times and routes within the system (Luk and Chung, 1997; Litman,
1999; Ramsey, 2005, p.41). Induced travel comes in a variety of forms including new travel due to
changes in land uses caused by shifts in transport network accessibility, mode shifts due to declining
public transport services or increased car ownership as a city becomes more auto-focused, or driving
substituting for other activities (Litman, 1999, p.5). Where the benefits of transport projects are
calculated in terms of travel time savings, lower emissions and decreased road trauma, these benefits
may be ‘illusory’ due to induced traffic effects (Newman and Kenworthy, 1999, p.297).
The FSM is often able to model changes in route and mode behaviour in the short term due to
changes in transport networks, and some changes in scheduling or distribution of trips. But most
models assume a linear relationship between population, land-use concentrations and transport
demand in the longer term, and few are capable of adjusting trip frequencies, or to factor in longer
term affects of automobility. In turn, models are also typically insensitive to the feedback effects
identified by Mogridge (1997) in which rising congestion on roads increases travel times and shifts
travel demand towards alternative travel modes. The failure of FSMs to account for induced traffic
weakens their capacity to inform policy makers about the broader economic value and environmental
impact of major transport projects.
Land use and transport interactions
Changes to urban form alter the number, mode, and distribution of trips within a region. And
regardless of assumptions that land uses are set by metropolitan strategies or other land use plans,
the reality is that transport network changes are fundamental in shifting demand for land as
accessibility increases (Ramsey 2005, p.40). Low (2003, p.7) argues that ‘increasing transport
infrastructure feeds back into more spatially dispersed patterns of land use’.
Most transport models in Australia have no land use feedback loops and thereby fail to consider the
impacts of land use changes on travel. As a result, their outputs may inadvertently promote greater
use of private motor vehicles (Beimborn et al., 1996). In addition, most models fail to identify any
benefits of improved land use mixing, public transport quality (beyond travel and waiting times) or
improved conditions for walking or cycling (Beimborn et al., 1996; Cervero, 2006).
Australian metropolitan strategies (e.g. OUM - QLD Government, 2005) generally seek to reduce land
use separation and distance, to promote walking, cycling, and public transport, and to reduce the use
of the private motor vehicles. The use of models unable to assess land use/transport interactions in
order to determine and prioritise transport project investments within these strategies is therefore
questionable.
Socio-economic status and transport
Inability to access, afford or operate private transport imposes significant costs on many urban
households especially the less socio-economically affluent (Kenyon et al., 2003). A lack of alternative
modes such as public transport may limit household access to employment, education or community
services (Herala, 2003; SEU, 2003). As we have seen, conventional transport models focus on urban
mobility in ways that may bias towards car travel at the expense of public transport, walking and
cycling. This may contribute to transport policies that fail to address the travel demands of socio-
economically disadvantaged households, especially those without access to a motor vehicle.
Air quality, noise and transport systems
Vehicle emissions are a major contributor to overall air pollution, with trends in transport indicating that
emissions will continue to rise due to the increases in vehicle trips. And noise effects of transport
vehicles are a major problem for health and well-being (Chapman, 2007; Lenzen et al., 2003; Lidskog
423
et al., 2003; Romilly, 1999). Many technical assessments use the outputs of transport models to
assess the effects of increase motor vehicle use on air quality and noise. Typically travel time savings
are used as the singular cost measure in transport assessment of this type. However, Affum et al.
(2003, p.2) argue that ‘much transport network planning still fails to consider environmental impacts at
the time future road network scenarios are modelled and evaluated’. Evaluative methods are needed
both at the link and at the system level, work that is rapidly progressing. Further, the costs of pollution
should be considered during strategic network planning exercises, and not only within the confines of
environmental impact statements for particular projects to which an agency has committed. Public
transport (particularly using electric power) should be factored as a low-emission option for developing
a sustainable transport system (Low, 2003; Yee, 2003).
Climate change/Greenhouse gas emissions
Similarly, the transport sector generates 26% of global CO2 emissions (Chapman, 2007) and a shift
from cars to alternative modes may have a significant impact on transport CO2 emissions (Chapman,
2007; Lenzen et al., 2003; Waterson et al., 2003). Further reductions could be achieved through
walking and cycling, which are seen as ‘zero carbon’ alternatives (Chapman, 2007).
Means to incorporate carbon within technical assessments are many, including the UK approach of
costing carbon emissions at a specific level. But this approach has yet to be incorporated into
Australian project or plan assessments. There are further questions as to what may occur should
government intervention be used to price carbon, increasing transport fuel costs, but this issue may
pale in comparison to the issue of oil vulnerability.
Oil vulnerability and energy security risk
Dependence on private automobiles for urban transport implies increasing dependence on petroleum.
The global price of petroleum has more than doubled since early-2004, rising from around US$25 per
barrel to approximately US$70 in mid-2007. Rising fuel costs have impacted on travel behaviour and
have stimulated greater demand for public transport and changing composition of motor vehicle fleets
toward smaller vehicles. Assessments of future petroleum prices suggest rising fuel costs over the
long term as global petroleum demand exceeds global supplies.
Most technical assessments of transport systems are naïve to the issue of petroleum risk. Indeed,
conventional transport modelling exercises typically involve linear projection of transport demand over
the long term, assuming growth in travel will continue without interruption. Nor has there been much
investigation in Australia to assess the likely travel demand patterns under higher fuel prices. Such
petroleum risk evaluations should extend to comprehending the way in which rising fuel costs will
impact not only on transport, but on housing and employment preferences, and on the communities at
most risk. Assessment frameworks are needed to deal with travel demand volatility.
Where to for transport technical assessment?
This paper has identified numerous inter-related concerns about the broader policy and political
dimensions of technical-rational decision-making in the transport sector. It also recognises the main
tools used in technical assessments, especially the FSM, and has identified continuing and emergent
issues that cause further complications. These concerns open numerous opportunities for further
research. Best-practice approaches developed elsewhere that in part address these concerns are not
appreciably utilised in Australia, possibly due to inertia within the profession, resource constraints, and
the use of proprietary products.
Whilst there have been a number of attempts in other jurisdictions to create either a superior land use
and transport models or modelling frameworks (e.g. Hunt and Abraham, 2004; Lautso et al., 2004) or
to create tools to address specific concerns, such as air quality or noise emissions (e.g. Brown et al.,
2004), there is urgent need for research to inform and assist practitioners to improve technical
assessments here in Australia.
A case study approach is suggested, taking one representative Australian city and exploring the use of
technical assessments and main modelling tools in practice. This work may explore the overall
technical assessment framework as used to assist transport policy decision-making, establish linkages
between the various component land use and transport models, and identify specific methodological
concerns, and possible means to address them. Brisbane is suggested for this work, primarily as the
city (through state and local government agreement) has moved to standardise transport modelling
424
with the Brisbane Strategic Transport Model (BSTM), and there is strong institutional interest in both
broadening the capacity of transport assessments, to explore new questions such as land use
interventions, and also in improving the precision of such work. Further, Brisbane City Council
recently made both the BSTM, and its necessary land use inputs, available for academic purposes –
for which it should be commended. This work has commenced.
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Transportation policy in the United States has travelled a road of top-down decision-making in which federal policy was set without participation from local communities. Government’s failure to create a process that addresses community needs through local and regional funding has resulted in a car-dominated transportation system that is not sustainable. A sustainable transportation system should provide people with affordable transportation options to get to work, play, school, shopping, and health care among other transportation needs. At the same time, the system should not have detrimental environmental impacts. However, transportation policies set by government at the state and federal level have focused on the suburban commuter travelling to work during the peak hours at the expense of other users of the system, and the environment. The needs of low income communities, youth and the elderly have often been left out of the policymaking process. This policy framework for transportation has skewed priorities to meet the needs of the middle-class suburban commuter at the expense of urban communities, especially low income communities and communities of color (Yee, 1999).