THE POTENTIAL OF TRANSPORTATION DEMAND MANAGEMENT IN BRASILIA Camila de Carvalho Pires Lammers Federal District Government - Brazil 1 [email protected]Summary: Over the last years, Brazil has faced a dramatic rise in the number of private automobile and a decrease of public transport use. In Brasilia, this process is aggravated by the city’s disperse occupation and land use. The research presented in this paper shows that there is an absence of conditions to discourage automobile use and highlights the importance of adopting an integrated approach - spatial and transport planning - in order to reverse the increasing trend of automobile dependence. The objective of this report is to assess how Brasilia’s government can develop a Transport Demand Management (TDM) program to discourage the use of private automobiles and achieve a more efficient and balanced use of transportation infrastructure. Recommendations are offered following the analysis of the current situation in addition to the identification of future perspectives, potentials and constraints. Key Words: Transportation Demand Management, mobility management, automobile dependence, Brasilia, Brazil 1 The analysis and recommendations expressed in this paper are those of the author and do not necessarily reflect the official opinion of the Federal District Government.
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THE POTENTIAL OF TRANSPORTATION DEMAND
MANAGEMENT IN BRASILIA
Camila de Carvalho Pires Lammers Federal District Government - Brazil
1 The analysis and recommendations expressed in this paper are those of the author and do not necessarily reflect the
official opinion of the Federal District Government.
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THE POTENTIAL OF TRANSPORTATION DEMAND
MANAGEMENT IN BRASILIA
I. INTRODUCTION
The process of urban development and its spatial configuration is influenced by people’s needs
and preferences (Berg 1999; Petersen 2004). Equally, the city’s configuration influences
people’s behavior and contributes to automobile dependence, creating a constant demand for
more infrastructure supply that reinforces the cycle of people’s habits and land use patterns
(Squires 2002; Neuman 2005; Gwilliam 2002). In this cycle, Transportation Demand
Management (TDM) is a tool that can affect all three factors – land use, people’s needs and
infrastructure supply - that are related to urban mobility.
International evidence suggests that TDM can be adopted to rebalance the use of existing
infrastructure by different modes of transportation and promote more sustainable mobility
(Goodwin 1995; VTPI 2010; Newman & Kenworthy 1989). It aims to maximize the efficiency
of urban transport systems by discouraging unnecessary private automobile use. For Black &
Schreffler (2010), TDM assumes the implementation of complementary interventions to balance
peoples’ travel needs with the capacity of available services and facilities. It consists of a set of
measures to influence traveler behavior in order to redistribute travel demand (Broaddus, Litman
& Menon 2009).
A broad variety of TDM measures are being implemented mainly in developed countries. TDM
has a special advantage in developing countries because of its low cost compared to the
investment for increasing the capacity of roads and parking facilities. In addition, it can
implement pricing reforms that are particularly useful at improving transport system efficiency,
financing public transport, the improvement of streets, and safety measures for non-motorized
modes (Broaddus, Litman & Menon 2009).
There is a variety of stakeholders that can perform TDM; however, governments have a special
role in developing policies, programs and involving other actors (Litman 2010b; KpVV 2005). A
range of measures and strategies, classified by different categories, are available and can be
tailored according to the reality of local conditions. Careful planning is necessary to elaborate a
comprehensive TDM strategy (Litman 2003; Tight, Site & Meyer-Rühle 2004).
This paper reports on research2 conducted to assess how Brasilia’s government can develop a
Transportation Demand Management (TDM) program to discourage private automobile use.
Case study strategy is used to investigate the current situation (automobile dependence analysis),
future perspective (policies and programs), and to evaluate constraints and potentials for the
application of a TDM program in Brasilia. At the end, recommendations are offered.
The research method is qualitative and based on primary and secondary data. Validity is
accomplished by the triangulation technique of different data collection methods: interviews with
thirteen selected actors from local government, universities and NGOs; observation; content
2 This paper is based on a master degree thesis conducted by the author (Lammers, 2011) in the Institute of Housing
and Urban Development Studies (IHS) under the supervision of Msc. Giuliano Mingardo.
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analysis of planning documents and a literature review of Brasilia. To ensure that reliability is
achieved, more than one research tool was used to allow for cross-validation of information.
Moreover, interviews were held with different actors of relevant organizations about the same
subject and information.
1. Transport pattern in Brazil
Over the last years, a dramatic rise in the number of private automobiles has been reported in
Brazil. Between 2001 and 2010, while the population growth rate in the majority of the Brazilian
metropolitan areas was of 10.7%, the increase in the number of automobiles was of 66%. If this
tendency continues the same, it is predicted that the national automobile fleet will be doubled by
2025 (IPEA 2010).
The increase in automobile and motorcycle fleet has occurred especially as consequence of the
rise of the population average income (growing representativeness of the middle class), the
higher national government support for private vehicles by taxes incentives, and the growing
inefficiency of public transport.
There is a cycle of high prioritization of the private automobile that causes a loss on demand and
revenue to the public transport system, which impacts the tariff and generates a higher loss in
demand, decreasing the productivity and attractiveness of public transport. In this context, the
transport demand is attracted to individual modes: Lowest income groups travel by bicycle or by
foot even for large and inappropriate distances; there is an increase in the use of motorcycles;
and middle and high income groups do not consider using public transport.
As consequence, it is perceived a decrease in public transport use (from 68% in 1977 to 51% in
2005) and a rise in the use of automobiles (from 32% in 1977 to 49% in 2005) (IPEA 2010), see
Graph 1, considering the total of motorized trips. This change in travel modes generates higher
user costs, a higher consumption of energy and exacerbates the externalities, such as pollution,
congestion and accidents.
Graph 1: Estimation of public transport share in total trips(motorized trips) for Brazilian
Metropolitan Regrions
Source: ANTP in IPEA 2010
Public Transp.
Private Transp.
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2. Brasilia spatial configuration
In Brasilia3, the long distances traveled are a consequence of the city’s physical configuration:
separation of functions in sectors connected by highways, generous surface parking lots and
green spaces that separate isolated buildings, see Figure 1 Figure 2. This pattern is controlled by
rigorous spatial plans and building codes that aim to protect the characteristics and principals of
the original plan (Costa, 1957), responsible for nominating Brasilia the first modern city included
in the world heritage list of UNESCO.
Figure 1: Main north-south axe road in the central
part of Brasilia
Figure 2: Roadway system in the center of
Brasilia
Source: Correio Braziliense 2007
It results in one of the most dispersed cities in the world (Bertaud & Malpezzi 2003), with low
density in the city center and relative higher density around it. Consequently, there is a great
pressure towards the center, which cannot accommodate natural market forces and therefore
drives the development and new housing demands to the periphery. Considerable distances
separate different activities and also the planned satellite cities that still depend on the main core
as the principal place for work and services. The center accommodates 82% of the formal jobs
and 44% of total jobs, while just 15% of the households live in the 10 km radius around it
(Tenorio & Júnior 2009), aggravating social inequality.
Although Brasilia has a configuration that favors automobile use and car ownership is increasing,
approximately 61% of the population still uses public transport and non-motorized modes
because of their inability to afford a car. In other words, the use of more sustainable modes of
transport is not a choice, but the only option available for a significant portion of the population.
In effect, public transport is seen as inadequate, inefficient, uncomfortable and unsafe, being
therefore, unattractive for middle and high income groups that do not consider shifting from car
to other ways of transport.
3. Key Problems
In Brasilia, increasing automobile ownership contributes to congestion and creates pressure for
the adoption of road extension and new parking areas as solution for traffic problems. In
addition, the use of transport infrastructure is not efficient, since its capacity is full and congested
during peak hours and empty during other periods of the day. Also, the importance and space
provided for the different modes of transport is not balanced, with clear preference given to
private automobiles.
3 In this paper, Brasilia refers to all Federal District unity.
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Therefore, the following problems can be identified: First, the use of automobiles is stimulated
by the city’s physical configuration. Second, the tendency of growth in private automobile use
cannot be reversed if the same public policies and projects that favor the private car by road
expansions continue. Finally, no importance has been given to the management of mobility and
its demand, only to the provision of extra infrastructure.
II. FINDINGS
1. Present : Automobile dependency analysis
Studies about the implications of Brasilia’s spatial configuration and its development are in
place, but there is little focus about its relationship with automobile use, its causes and
consequences. A study with global cities conducted by Newman & Kenworthy (2001) revealed
that the patterns of automobile dependence, based on infrastructure, transportation and land-use,
follow a consistent path with the same pattern of economic and environmental costs; while cities
committed with sustainable transportation are doing better at reducing direct and indirect costs of
transportation. Moreover, Sakamoto, Dalkmann & Palmer (2010) stress the necessity to reverse
the urban sprawl paradigm trend, whereby developing countries shall cultivate a sustainable
transport system with enhanced accessibility without requiring the same level of motorization
seen in developed countries.
Hence, this section analyzes the spatial structure of Brasilia and the automobile use. The present
situation was studied considering the attributes that influence car dependence level, according to
the classification suggested by the Victoria Transport Policy Institute (2010)4. It used primary
data from interviews with local actors, and secondary data: academic researches and papers,
reports, official documents, and transport surveys.
1.1. Vehicle ownership
The first indicator analyzed was vehicle ownership, measured by per capita motor vehicle
ownership (per 1000 population). For Brasilia, the number of 355.52 is classified as medium
automobile dependent - multi-modal, see Table 1.
Table 1: Vehicle ownership per 1,000 pop. – classification of automobile dependence
Results Low Medium High Data Source
355.52 (2010) Less than 250 250-450 450+ DETRAN/DF & IBGE
Nevertheless, the tendency is that this index rises, since in the last decade, the number of cars
increased 86.6% while the population grew 20.4% in the metropolitan region (Ribeiro &
Rodrigues 2011). The Graph 2 shows the growth in fleet in comparison with the population.
4 The “Vehicle Travel” indicator was excluded as not data was found for it.
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Graph 2: Fleet, population, and motorization index for the Federal District, 2000 to 2009
Source: DETRAN/DF in Secretariat for Transport of the Federal District 2010a
1.2. Vehicle Trip
Vehicle trip is measured by the portion of automobile trips in relation to total personal trips. In
Brasilia, automobiles represent 39.05% of total trips and 50.98% of motorized trips
(ALTRAN/TCBR 2009), being classified as low automobile dependent, see Table 2.
Nevertheless, this indicator does not reflect directly automobile dependence in Brasilia since the
portion of automobile trips is related to income. In fact, the Technical Report nº3
(ALTRAN/TCBR 2009) based on the Origin Destiny Survey of 2009 mentions that the
percentage of automobile trips increases according to the income increment, while the number of
public transport trips decrease. It is suggested that there has been a substitution of public
transport for automobiles, with the values getting stable above the higher income levels.
Table 2: Vehicle trips in relation to total personal trips – classification of automobile dependence Results Low Medium High Data Source
- 39.05% of total trips - 50.98% of motorized trips
Less than 50%
50-80% 80%+ OD 2009 (ALTRAN/TCBR 2009) - +80% of total trips in the central area
- 78% of trips in high income neighborhoods - Less than 10% in the poorest neighborhoods
1.3. Quality of Transportation Alternatives
‘Quality of transportation alternatives’ is evaluated according to convenience, speed, comfort,
affordability and prestige of walking, cycling and public transit relative to driving. The
alternative modes were classified as very inferior compared to automobile based on the reports
evaluation (TCDF 2009; Secretaria de Transporte 2008, 2010, 2010b; CNI 2011); and the
opinion of interviewed (none considered the alternative modes competitive and 8 of 13
considered them very inferior). The results are shown on Table 3.
Motorization index
Population
Fleet
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Table 3: Quality of Transportation Alternatives – classification of automobile dependence Results Low Medium High Data Source
- Bus system: Full coverage, but with bad results on waiting time, reliability, travel time, tariff, and users evaluation.
- Metro system: Well evaluated, but small coverage and representativeness.
- Bicycle: Small coverage, poor infrastructure facilities, no priority, and no integration.
- Walking: Bad evaluated on distances, continuity of infrastructure, safety, comfort, and prestige.
- Driving: Full coverage, good infrastructure, and well evaluated by users.
Alternative modes are of competitive quality.
Alternative modes are somewhat inferior.
Alternative modes are very inferior.
- Reports - Satisfaction
surveys - Interview
1.4. Relative mobility of non-drivers
Relative mobility of non-drivers is evaluated by mobility of personal travel of non-drivers
compared with drivers. Considering the mobility index5, see Table 4, public transport users were
considered as moderately disadvantaged compared to drivers, while non-motorized modes were
evaluated as severely disadvantaged. Secondly, considering the interviews, the majority (9 of 13)
evaluated non-drivers in general as severely disadvantaged compared to drivers, while no one
considered them in equal or superior conditions. Therefore, the relative mobility of non-drivers
was classified as severely disadvantaged.
Table 4: Relative Mobility of Non-Drivers – classification of automobile dependence Results Low Medium High Data Source
Personal Mobility: - Auto: 0.59 - Public Transport: 0.48 - Pedestrian: 0.32 - Bicycle: 0.03 - Most interviewed evaluated non-
drivers as severely disadvantaged.
Non-drivers are not severely disadvantaged.
Non-drivers are moderately disadvantaged.
Non-drivers are severely disadvantaged.
OD 2009 (ALTRAN/
TCBR 2009) Interview
1.5. Land Use Patterns
‘Land Use Patterns’ is evaluated by land use density (residents and jobs per acre) and mix
(proximity of different land use types). The result was classified as dispersed and homogeneous -
high automobile dependent, Table 5, because of the results regarding to low density (Holanda
2010) and inverse profile that cause long transport distances and commuting trips (Bertaud
2010); the imbalance between jobs concentration and housing places (ALTRAN/TCBR 2009);
the discontinuity of urban fabric and the restrict zone use (Holanda 2010); the low accessibility
(Holanda 2010) and very high dispersion index6 (Bertaud & Malpezzi 2003); as well as the
evaluation of the majority of the interviewed (9 of 13).
5 Mobility index is the average number of trips made in relation to the number of inhabitants.
6 Bertaud & Malpezzi (2003) calculate the dispersion index by the ratio between the average distance per person to
the CBD.
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Table 5: Land use patterns - land use mix and density – classification of automobile dependence Results Low Medium High Data Source
- Concentration of jobs; - Low density; - Inverse profile; - Discontinuous occupation; - Very dispersed; - Fragmented; - Most interviewed evaluated as dispersed.
Very compact and mixed.
Moderately compact and mixed
Dispersed and homogenous
- Papers - Report - Interview
1.6. Transport System
‘Transport System’ is evaluated by type of transportation facilities and services available. The
research showed that although there is a range of transportation facilities available – roads, bus,
metro, bicycle paths and sidewalks – the alternative modes lack extension (Secretaria de
Transporte 2010a, 2010b), improvement and integration (Pontes 2010; Correio Braziliense
2011), while the automobile facilities are dominant, as also evaluated by all the actors
interviewed. Therefore, the transport system was classified as mainly for automobile. Results are
shown on Table 6.
Table 6: Transport system (facilities and services available) – classification of automobile dependence Results Low Medium High Data Source
- Mainly automobile – complete coverage of the road system and provision of public parking;
- No public transport integration; - Few bus corridors; - Poor bus’ terminal maintenance; - Low extension of the metro system; - Incomplete implementation of the bicycle system
(less than 35%); - Discontinuity of sidewalks and bad maintenance; - All interviewed evaluated as mainly automobile.
Mainly non-motorized and public transit
Very mixed: non-motorized, public transit and automobile.
Mainly automobile (roads and parking facilities).
- Reports - Journals - Interview
1.7. Design Feature of Roads
The evaluation of design feature of roads considers modes prioritization and facilities. The result
was classified as automobile oriented, see Table 7, because most of the roads in the central
region and the planned peripheral neighborhoods are designed to prioritize automobile
circulation and speed. The city structure is based on highway engineering principals (Costa
1957) with elimination of intersections on level, hierarchical division of road system to optimize
speed, and generous quantity of parking places. On the other hand, the road system configuration
limits the accessibility and mobility of pedestrians because of distances, physical barriers and
discontinuation of paths (Kohlsdorf, Kohlsdorf & Holanda 2003). In accordance, most of the
actors interviewed (9 of 13) considered that the features of roads are designed to maximize
automobile traffic speeds and volumes.
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Table 7: Design features of roads – classification of automobile dependence Results Low Medium High Data Source
- City structure based on highway engineering principals;
- wide roads and facilities for cars; - generous quantity of parking places; - poor or inexistent sidewalks; - physical barriers to pedestrians’ movement; - Most interviewed evaluated as favoring car
Highly pedestrian oriented
Mixed
Designed to maximize auto
traffic speeds
and volumes
- Papers - Interview
1.8. Shopping Options
‘Shopping Options’ is evaluated by the location of retail and other public services, if along
public streets, near transit areas, or in private malls along major highways. In Brasilia, it was
identified a mixed situation, with occurrence of local commerce along public streets and a great
number of private malls in the central region and middle income neighborhoods; while there is a
predomination of shops along public streets in the low income areas. Therefore, the result was
classified as being both “mainly along public streets near transit areas” and in “private malls”,
Table 8.
Table 8: Location of retail and other public services – classification of automobile dependence
Results Low Medium High Data Source
Difference between neighborhoods: - Center: mixed - Satellite cities: Along streets - Private condominiums and single houses
neighborhoods: private malls Also influenced by income level, and land use
restrictions. Interviewed evaluated equally as multi-modal and
auto dependent.
Along public streets
Mainly along public streets near transit areas
In private malls, located along major highways
- Maps analysis
- Interview
1.9. Market Distortions Favoring Automobile Use
‘Market Distortions Favoring Automobile Use’ is evaluated by the relative advantage provided
to automobile transportation over other modes in planning, funding, tax policy, etc. Although
there are some incentives to encourage public transport and investments in alternative modes,
there is still a strong bias favoring automobile use, as shown on Table 9. Among the actors
interviewed, the majority (9 of 13) agreed that there is a significant bias favoring automobile,
and no one considered that there is a minimal bias favoring it.
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Table 9: Market distortions favoring automobile use – classification of automobile dependence Results Low Medium High Data Source
Planning: - Plans, regulations and practice give priority to automobile flow and facilities; - New developments overestimate traffic congestion impact, with absence of other modes feasibility studies. Funding: - Similar investments in motorized transport (individual and collective); - Little investment in non-motorized transport; Tax policy: - Public transport subsidy for minority groups; - Reduced taxes for automobile acquisition and registry; - Free parking; Interviewed evaluated that there is significant bias favoring automobile.
Minimal bias favoring automobile travel.
Moderate bias favoring automobile travel.
Significant bias favoring automobile travel.
- Reports - Papers - Journals - Interview
1.10. Automobile commute mode split
‘Automobile commute mode split’ is evaluated by how people travel to work and study places,
measured by the relative share of modes. Considering all commute trips, individual automobile
represents 35% of total, being classified as “medium” regarding to automobile dependence, see
Table 10. Nevertheless, it is important to note that this share can vary significantly according to
each neighborhood and income considered. Higher income neighborhoods located in the central
region have 80% of commute trips done by automobile; while in lower income neighborhoods,
the public transport is dominant and represents more than 60% of all modes (ALTRAN/TCBR
2009). Similarly, around 60% of the students of private schools are driven by automobile, while
70% of public school students’ use buses (Bertazzo & Jacques 2010).