Tool for Rapid Assessment of Urban Mobility
- Pilot Test in Nashik City
Prepared by Clean Air Asia and the Institute of Transportation and Development Policy for
UN-Habitat
August 2013
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
©2013 Clean Air Asia and the Institute for Transportation and Development Policy. All rights reserved.
Clean Air Asia Center, 2013. “TOOL FOR RAPID ASSESSMENT OF URBAN MOBILITY IN CITIES WITH DATA
SCARCITY: A USER’S GUIDE”. Pasig City, Philippines.
This publication may be reproduced in whole or in part in any form for educational or non-profit purposes
without special permission from the copyright holder, provided acknowledgment of the source is made. The
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purpose whatsoever, without prior permission in writing from the Clean Air Asia Center.
Disclaimer
The views expressed in this publication are those of Clean Air Asia and ITDP staff, consultants and
management, and do not necessarily reflect the views of the Board of Trustees of the Clean Air Asia Center.
The Clean Air Asia Center does not guarantee the accuracy of the data included in this publication and does
not accept responsibility for consequence of their use.
Acknowledgements
UN-Habitat, Nashik Municipal Corporation, Late Annasaheb Patil’s Nashik Institute of Technology, College of
Architecture and Centre for Design, Saraha Consultants
Contact
Clean Air Asia Center
Unit 3505 Robinsons Equitable Tower
ADB Avenue, Pasig City, 1605
Philippines
Tel +632 631 1042
Fax +63 2 6311390
center@cleanairasia.org
CAA Country Networks in
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Nepal, Pakistan, Philippines,
Sri Lanka, Vietnam
ITDP
1210 18th St NW
Washington, DC 20036
Tel: +1 212 629 8001
Fax: +1 646 380 2360
mobility@itdp.org
ITDP Country Networks
in China, India,
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About Clean Air Asia
www.cleanairasia.org
Clean Air Asia (formerly Clean Air Initiative for Asian Cities) promotes better air quality and livable cities by translating
knowledge to policies and actions that reduce air pollution and greenhouse emissions from transport, energy, and other
sectors. Clean Air Asia was established as the leading air quality management network for Asia by the Asian Development
Bank, World Bank and USAID in 2001, and operates since 2007 as an independent non-profit organization. Clean Air Asia
has offices in Manila, Beijing and Delhi, networks in eight Asian countries (China, India, Indonesia, Nepal, Pakistan,
Philippines, Sri Lanka, and Vietnam) and is a UN recognized partnership of more than 240 organizations in Asia and
worldwide.
About ITDP
www.itdp.org
The Institute for Transportation and Development Policy (ITDP) provides technical transport and planning expertise to local
authorities in cities around the world. We promote transport solutions that reduce greenhouse gas emissions and air
pollution, while improving urban livability and economic opportunity. Our projects inspire cities towards more
environmentally and people-friendly transportation.
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
LIST OF ABBREVIATIONS
ADB
CMP
FGD
Ha
ITDP
JNNURM
Km
Kmpl
MoU
NGO
NMC
PCTR
P-km
RoW
sqkm
TRAM
UMTA
Asian Development Bank
Comprehensive Mobility Plan
Focused Group Discussion
Hectare
Institute for Transport Development and Policy
Jawaharlal Nehru National Urban Renewal Mission
Kilometer
Kilometer per Liter
Memorandum of Understanding
Non Government Organization
Nashik Municipal Corporation
Per Capita Trip Rate
Passenger Kilometer
Right Of Way
Square kilometer
Tool For Rapid Assessment of Urban Mobility
Urban Metropolitan Transport Authority
3
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
CONTENTS
1.
INTRODUCTION ..................................................................................................................................... 5
2.
APPROACH ............................................................................................................................................ 6
3. PILOT TEST CITY CONTEXT AND EXISTING DATA: NASHIK, INDIA ............................................................. 9
3.1 Current Transport Infrastructure ........................................................................................................ 9
4. PREPARING DATA COLLECTION FOR TRAM ............................................................................................ 13
4.1 Local Survey Support......................................................................................................................... 13
4.2 City Classification .............................................................................................................................. 13
5. FOCUS GROUP DISCUSSION .................................................................................................................... 19
6. HOUSEHOLD SURVEY .............................................................................................................................. 22
7. RESULTS AND FINDINGS FOR TEST CITY.................................................................................................. 29
7.1 Household Characteristics ................................................................................................................ 29
7.2 Transport and Travel Characteristics ................................................................................................ 30
7.3 Summary of Preliminary Findings ..................................................................................................... 39
8. ANALYSIS OF TRANSPORT INTERVENTIONS USING TRAM ...................................................................... 40
9. KEY TAKEAWAYS BASED ON PILOT TESTING ........................................................................................... 44
ANNEXES ..................................................................................................................................................... 47
Annex A. List of Stakeholders ................................................................................................................. 47
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
1. INTRODUCTION
The Tool for the Rapid Assessment of Urban Mobility (TRAM) was developed with the main objective of
orienting key municipal stakeholders, including city mayors, municipal authorities and decision makers on
time-effective ways to tackle pressing mobility issues. It is intended to be a benchmarking tool for urban
mobility and includes both participatory and analytical components that enable local stakeholders to share,
enhance and analyze their knowledge of mobility conditions. The knowledge gained will serve as a basis for
transport and land use interventions. This report is a part of series of reports on “Rapid Assessment Toolkit
for Urban Mobility in cities with scarce data”. A more detailed description of the TRAM methodology is
provided in the TRAM User’s Guide
This report explains the pilot testing procedure in Nashik, India, a city with scarce data. The analysis of the
data is carried out with the TRAM tool to understand the present mobility patterns in Nashik and assess the
impacts of potential interventions based on the priorities of local residents. This report highlights and
describes the activities carried out in Nashik city which include a scoping visit, stakeholder meetings, surveyor
orientation, focus group discussion, household surveys, assessment of overall city characteristics, and
analysis of interventions using the modified version of the Transportation Emissions Evaluation Model for
Projects (TEEMP) City tool. It also presents an analysis of several options for transportation improvements
and the likely impact they will have on the city.
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
2. APPROACH
The figure below shows the step by step approach to the TRAM methodology. These are further elaborated
in the TRAM User’s Guide, and are also discussed in greater detail later on in the report.
Step 1: Meeting with the city
government/stakeholders
•Establish early coordination with the city
•Collect city-level data
Step 2: Data collection at the
selected neighbourhoods
•Identify areas where detailed data collection will
be conducted
•Gather detailed data in the selected
neighbourhoods through focus group discussions
and household interviews
Step 3: Survey Data encoding
•Input and collate the data gathered from the
surveys and focus group into an organized,
electronic form through a data input file
•Transform data to represent entire city through
sketch citywide analysis
Step 4: Evaluation of current state
of mobility
•Summary statistics and knowledge gained from
the FGDs and city meetings will be used to
provide a picture of the current state of mobility in
the city
Step 5: Rapid assessment of
intervention impacts
•Use data and knowledge gathered from the data
collection activities in order to rapidly assess the
potential impacts of transportation interventions
(e.g. emissions, fuel consumption, time spent,
income spent on transport, safety)
Figure 1: Steps involved in the TRAM
Step 1: Meeting with the city government/stakeholders
The objectives of this step are the following:
1. Select an appropriate City
2. Coordinate with the city government to plan assessment activities and to collect available
city-level baseline information such as the following:
 city-level accident statistics
 socio-economic statistics
 public transit routes and fares
 fuel price
 current transport policies
 mobility plans
3. Classify the entire city based on centrality, income, and access to transit
Step 2: Data collection at the selected neighborhoods
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
This step is divided into the Focus Group Discussion (FGD) and the household surveys and helps capture the
following information:









mobility issues and potential solutions
basic socio-economic data
main trip destinations
trips by mode
travel time
income spent on transport
ownership of motorized and non-motorized vehicles
perception on the acceptability/quality/safety of public transit modes
perception on priorities for transportation improvements
The data is collected through a scientific sampling procedure explained in the TRAM User’s Guide.
Step 3: Survey data encoding
The purpose of this step is to store and collate the data from the survey in an organized electronic form. The
data gathered through the interviews is transformed into electronic form using an excel-based survey data
input file that was developed under this project. The input file is based on the format of the interview survey
form, producing summary statistics (e.g. travel activity and mode share) for different categories, including
income, gender, age, and occupation.
Step 4: Evaluation of the Current State of Mobility
The purpose of this step is to evaluate the information collected from government officials, the focus group
discussions, and survey summary statistics to develop a preliminary picture of the current mobility issues in
the city. This process uses the city classification information from Step 1, with a modified TEEMP-City tool to
expand the household survey data to show characteristics of the entire city. The survey data input file will
produce summary statistics for many parameters, including the following:







average number of trips/ capita
mode shares
average trip length
average travel times
average % of income spent on transport
average person-kms
average perception ratings
These indicators by themselves will provide insight to local policy makers regarding the existing availability,
accessibility, affordability and acceptability of transportation in the city. By showing mobility patterns across
many different segments of the society, politicians will gain a more complete picture of transportation in the
city. This process serves as preparation for Step 5.
Step 5: Rapid assessment of intervention impacts
The purpose of this step is to provide a quick assessment of the impacts of different transportation
interventions in the city. This analysis uses the results from the household survey as inputs into a modified
TEEMP-City model. Interventions include, among others:
7
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City






Pedestrian Safety Improvements
Bicycle Safety Improvements
New Metro/Rail
New Bus Rapid Transit (BRT)
More flyovers/limited-access roadways
Bike share systems
These interventions are analyzed based on a number of quantitative criteria, including:




Total number of users benefitting
Income groups benefitting
Project costs
CO2 Emissions Reductions
The projects are also described in terms on the qualitative benefits that each one provides. These include the
following:




Time savings
Safety improvements
Passenger comfort improvements
Access improvements
The results of the analysis should be compared to the issues and priorities identified in the household survey
and FGDs, and with the input of local leaders. This way, the city can make a more informed choice about how
to best address existing and future transportation issues. The results of the analysis provides a clear view of
the effects of different transportation interventions in the city, and how they compare to the priorities of the
city and its people.
8
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
3. PILOT TEST CITY CONTEXT AND EXISTING DATA: NASHIK, INDIA
The City if Nashik was selected as the location for the pilot test of the Tool for the Rapid Assessment of Urban
Mobility (TRAM) because it is growing rapidly, in term of economy, population, and motorization and has an
administration receptive to sustainable transportation ideas. Nashik is the fourth largest city in Maharashtra
state in India. According to the 2011 census, Nashik has a population of 1,486,9731 (1.48 million). With
increasing migration of the population to urban areas, Nashik is fast growing in both city area and population,
which is set to grow to nearly 4 million by 2030. As it grows, the city is witnessing rapid motorization and
increased congestion and pollution. With suitable interventions at this stage, it can avoid the pitfalls that
similar cities have fallen into and can set high standards for other cities to follow. In order to obtain
international expertise and advisory services on sustainable transport, the Nashik Municipal Corporation
(NMC) has signed a Memorandum of Understanding (MoU) with the Institute for Transportation and
Development Policy (ITDP). ITDP held an initial stakeholder meeting which was well attended by both
government and non-government representatives indicating considerable interest in sustainable transport.
Because of its size, growth, and openness to sustainable transportation ideas, Nashik was chosen for the pilot
test of the tool, which will greatly help to develop good data and indicators, the foundation of sustainable
transport planning process.
3.1 Current Transport Infrastructure
In 1985, the development area of the Nashik was 27% of the total area of 7,260 Hectares and the
transportation right-of-way occupied 11% of the developed area. Transportation is expected to increase to
15% of the developed area and the total developed area to 53% of the total area during the plan period
2006-20312. Interestingly, Nashik has a population density of 4,157 persons per square kilometer, which
indicates that there is still a great potential to increase the density and retain Nashik as a compact city. A
Comprehensive Mobility Plan (CMP) was carried out in 2007 for Nashik city to determine the transport
interventions for the future, considering the growth and change in land use. The CMP is prepared with a
perspective of 20 years. The summary of existing conditions, documented in the CMP, was made available by
the authorities, but the detailed data was not available. The results summarize the transport indicators from
the city. The summary of city travel characteristics in 2007 is presented in Table 1.
Table 1: Household Travel Characteristics [CMP, 2007]
1
2
Household size
4.5 people
Average household income
USD $140 per month
Expenditure on transport
4% of the household income
Per Capita Trip Rate (PCTR)
1.68
PCTR excluding walk trips
1.21
Percentage of highest trips
Private vehicle (45%)
Percentage of lowest trips
Public transit
Average trip lengths
4.37 km including walk trips
http://www.census2011.co.in/census/city/361-nashik.html
http://nashikcorporation.gov.in/doc/cdp-ch4_Chapter4.pdf
9
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
5.82 km excluding walk trips
Vehicular trip length
Between 3 and 5 km
Walk trip length
1.01 km
Two wheeler trip length
10.54 km
From the above table, private vehicle transportation (i.e. two wheelers and cars) is more prevalent than
other modes. Vehicle registration data from Nashik City shows a high level of two wheeler ownership than
other vehicles (see Table 2). The data show that Bus is the only public transit mode available, but it is
inadequate to meet the growing transportation demand, accounting for only 4% of all trips3. According to the
CMP, 420 additional buses are required to meet the needs of the city, an increase of the bus fleet size to 650.
100 buses were sanctioned for the city under the JNNURM, India’s national transportation funding
mechanism, which aims to increase the mode share of public transit use to 10%. There is no Urban
Metropolitan Transport Authority (UMTA) or a Special Purpose Vehicle in the city to manage and operate
urban transport. There is also no comprehensive parking policy4. The CMP proposes almost 90km of public
transit corridors on ten routes in the city out of which 55km is for bus rapid transit systems (BRTS) with four
terminals.
Table 2: Vehicle Registration in Nashik City as on 31 March 20115
Vehicle Type
Population
2 Wheeler
300,877
Auto Rickshaw
16,937
Car/Jeep/Taxi
Buses
(includes
stage
carriers,
school
buses,
private services, contract
carriers)
44,208
944
It is noteworthy that the CMP also mentions that pedestrians and cyclists should be encouraged with
continuous and safe paths, especially near public transit access points. However, the implementation
program only mentions the provision of four pedestrian subways or footbridges. The major implementation
work outlined in the CMP is 18 road upgrades and six flyovers. Clearly there is a gap between what the CMP
wants to achieve and how it intends to achieve it for the city. Visual inspection of many areas in the city like
Panchwati, Sharanpur, around Trimbak Road, Canada Corner, Pandit Colony, Lawate Nagar, Savarkar Nagar
and other areas shows a lack of dedicated and continuous footpaths. Major corridors such as the Mumbai –
Agra road, Trimbak Road, Sharanpur Road, Gangapur Road, which are wide or have been widened recently,
lack safe and continuous footpaths and cycling tracks and have lost effective crossing points. Though there
was less need for physically separated footpaths in the recent past, due to low motorization and low speeds,
3
http://jnnurm.nic.in/wp-content/uploads/2012/02/booklet-on-transforming-City-Bus-Transport-in-India.pdf
http://jnnurm.nic.in/wp-content/uploads/2012/02/booklet-on-transforming-City-Bus-Transport-in-India.pdf
5
http://www.mahatranscom.in/pdf/STATISTICAL.BOOK.10-11.pdf
4
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
the city is experiencing rapid growth in vehicular travel and is investing heavily to increase vehicle capacity,
such as road widening, both of which greatly increase the dangers to walking and cycling.
Preliminary Walkability surveys, separate from the tool analysis, were also carried out to determine the
friendliness of the walking environment in Nashik. Based on the index developed by Clean Air Asia four
different land use types were audited: residential, educational, commercial and transport terminals. The
results (Table 3) show an overall poor level of walkability, similar to most Indian cities. With a rating of 35,
the transport terminal scored the lowest of all areas. Residential areas scored better than others due to
lower vehicular volumes and speeds.
Table 3: Walkability Rating of Nashik
Land-use Type
Commercial
Residential
Educational
Transport Terminal
Index
30
45
40
24
A comparison with other Indian and Asian cities shows that Nashik has scored poorly in walkability. Not only
is it less walkable than large cities like Chennai and Bangalore but also smaller cities like Rajkot and Surat, as
shown in Figure 2. Depending on the range, the scores are provided different colors. Scores below 50, shown
in red, are defined as ‘walk at your own risk’, scores between 50 and 70, in yellow, are defined as ‘waiting to
walk’, and 70 and above, in green, are defined as ‘pleasure to walk’. Nashik has much potential to remain
sustainable as majority of the trips are by foot. In the pedestrian preference survey carried out in other cities,
82% of pedestrians wanted to shift to motorized modes if no improvements were carried out in the
pedestrian infrastructure6. This could well happen in Nashik, where pedestrians will shift to private vehicles
when they can afford to, especially if it continues to become more dangerous to walk.
6
http://cleanairinitiative.org/portal/projects/India-walkability
11
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 2: Comparison of Walkability Scores with other Indian and Asian Cities
Intermediate Public transit (IPT) such as auto rickshaws are the most ubiquitous form of transport and are
available at almost all places of the city, based on observations. The CMP calls for regulation of auto
rickshaws in the form of dedicated parking spaces and the usage of fare meters, which will require
enforcement from the traffic police and the transport department. The CMP study identifies that activity is
concentrated in the centre of the city and argues that it should be spread out through the implementation of
ring roads, which would also reduce traffic congestion. There are proposals for Special Economic Zone (SEZ),
Proposed Townships (which will host large number of housing complexes, commercial establishments) and
industrial corridors linking Mumbai, Delhi and Pune. Other mass transit options such as metro rail are also
being considered and a Metro feasibility study is planned by the NMC.7
7
http://articles.timesofindia.indiatimes.com/2013-03-17/nashik/37786208_1_metro-rail-nashik-municipalcorporation-private-firm
12
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
4. PREPARING DATA COLLECTION FOR TRAM
4.1 Local Survey Support
The success of a participatory project hinges on the active involvement and support of the local
administration and organizations. The Municipal Corporation’s engineers and local officials provided much
support for the smooth conduct of all activities. Their assistance included approving activities for the
orientation program, issuing official letters, and connecting CAA and ITDP with other stakeholders in the city.
During the initial stakeholder visit, Nashik First, a local NGO, provided assistance in creating a long list of the
neighborhoods based on the survey requirements. The volunteers for the survey were provided by Nashik
Institute of Technology and College of Architecture and Centre for Design. Saraha Consultancy provided office
space for survey support and meetings while carrying out the surveys.
4.2 City Classification
The first step in collecting data with TRAM is to effectively choose survey neighborhoods and then scale them
up to represent the city as a whole, the city should be classified before any further data is collected. This
classification should be on three characteristics: income level (low, medium, and high), centrality (central or
peripheral) and transit access (good or poor). This way, decisions regarding the boundaries of the central city,
the local definition of good transit access, and the level of income for different groups can be decided ahead
of time. The rest of the survey, including the selection of neighborhoods to survey and the scaling up of the
results, will flow from this work.
In Nashik, this was not the case, as the TRAM methodology was not completely finalized. The neighborhoods
were initially selected, based on the 12 typologies by a partial survey team and local officials familiar with the
area. Afterwards, the full survey team arrived in the city, and the selection of neighborhoods was reviewed
and altered to best represent a broad range of income levels and a better definition of centrality and good
transit access.
The classification of the rest of the city occurred after the household survey and focus group discussion were
completed. This presented a challenge, as the definitions for income, centrality, and transit access were
confined by the neighborhoods that were surveyed, which were already assigned an income, access, and
centrality classification. For example, the definition of the areas with good transit access needed to include
the survey locations classified as having good access and exclude the survey areas classified as having poor
access. This was challenging and made it more difficult to objectively classify the city.
Centrality
Central neighborhoods were defined as those within 4km of the oldest part of the city. This was done in a
fairly straightforward by drawing a 4km circle around the center of the city. The areas within than circle were
considered central, while area outside it were considered peripheral. A map of this designation is shown
below.
13
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 3: Map of Nashik Centrality
Transit Access
Neighborhoods with good transit access were defined as those within walking distance of a bus stop and near
a frequent route of auto rickshaws. Areas farther from the city center with lower-frequency bus service were
not included as areas with good transit access, even if they were close to a bus stop. Information about the
frequencies of bus routes and the prevalence of auto rickshaws along a corridor was not available. Therefore,
most of the assessments of transit frequency and the prevalence of auto rickshaw are based on observation
and local knowledge, which are highly subjective. This process should be revisited in future iterations of the
tool to improve accuracy. A map of the areas with good transit access is shown below.
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 4: Map of Nashik Transit Access
Income Level
The recommended methodology in the TRAM Guide is to gather a team of local experts to examine a map
and divide the city into income sectors. However, the ITDP team was not able to gather a team of experts
with enough knowledge to do this effectively across the city. In lieu of this expertise, an alternate
methodology was developed, in which an ITDP staff member procured a vehicle and a GPS device and drove
to a wide variety of locations around the city. A total of 2,014 Data points were recorded every 100-400
meters across the entire city. At each location, the housing stock was classified into the following categories,
which are illustrated in the figures that follow:
 Low-Income Housing:
o Slums
o Low-income government housing
o Low-income tenements
 Middle-Income Housing:
o Apartments, government-built flats, and private flats
o Middle-income tenements and row houses
 High-Income Housing:
o High-income apartments
o High-income bungalows
15
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 5: Examples of Low-Income Housing
Figure 6: Examples of Middle-Income Housing
Figure 7: Examples of High-Income Housing
16
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
The administrative divisions with a point within then were assigned the income category and building height
of the nearest point to the shape. Figure 8 shows the resulting map of income in Nashik.
Figure 8: Map of Nashik Income
Density
The recommended methodology for classifying the density of each part of the city is also to use a panel of
experts. As described above, a panel could not be procured, so an alternative methodology was used. In the
same data collection process that measured income level, density was also recorded at each data point,
according to the height of the buildings in the area. The following categories were recorded: 1-2 stories, 3-5
stories, and 6 or more stories. Based on the results of the centrality, transit access, and income
categorizations, each administrative district will be assigned one of the 12 typologies. Since each shape has a
typology and building height, the typologies were then analyzed to determine which building height was
prevalent in the greatest amount of area. Then, densities were assigned based on the average building
heights in the area as well as the following assumptions about density:
 Lower income areas > middle-income areas > high-income areas
 Areas with good transit access > Areas with poor transit access
 Central areas > peripheral areas
Each typology’s densities was then multiplied by the total land area of the typology to calculate the total
population in that typology. All 12 typologies were summed. If the sum was within 10,000 people of the
population of Nashik (1.48 million) the process was stopped. If the population was not within that range, the
densities were adjusted accordingly until the sum of the population in all typologies was within the desired
range. The resulting densities are listed below:
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Core - Low - Connected:
Core - Middle - Connected:
Core - High - Connected:
Core - Low - Not Connected:
Core - Middle - Not Connected:
Core - High - Not Connected:
Periphery - Low - Connected:
Periphery - Middle - Connected:
Periphery - High - Connected:
Periphery - Low - Not Connected:
Periphery - Middle - Not Connected:
Periphery - High - Not Connected:
32,000 people / km2
28,000 people / km2
26,000 people / km2
32,000 people / km2
28,000 people / km2
26,000 people / km2
30,000 people / km2
16,000 people / km2
11,000 people / km2
30,000 people / km2
14,000 people / km2
9,000 people / km2
18
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
5. FOCUS GROUP DISCUSSION
As part of the pilot test of the tool, a focus group discussion (FGD) with selected key stakeholders was held
with the aim to elicit information regarding the transportation infrastructure characteristics, transportation
needs and issues of the city. While a larger number of FGDs is preferred, due to time and logistical
constraints, only one FGD was able to be conducted in Nashik. The major objectives of the FGD were to:





Obtain local experiences and perceptions on the current state of mobility in the city;
Identify factors that facilitate urban mobility in the city;
Identify major challenges to mobility;
Identify the main areas for improvement in urban mobility; and
Gather recommendations as to how (facilitating) factors can be enhanced, challenges addressed, and
identify participants’ (perceived) priorities.
The FGD was divided into a “current issues” and “potential solutions” session. Initially, each participant was
given two minutes to list their problems and the facilitators did not intervene and ensured that all had a fair
say of their opinion. The participants ranged from students, architects, builders, educationist, visually
impaired, physically disabled, media, doctor, businessperson, driver, women’s group representing a cross
section of society. The list of participants is provided in Annex 1.
Figure 9: A view of the FGD (source: Colin Hughes)
The aim of the FGD was initially explained to the participants, which was to understand their transportation
and mobility issues faced by the groups the individuals were representing and to also suggest solutions. It
was also ensured that there would be no domination of any particular group or people questioning other’s
opinion.
19
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Hindi and Marathi (local language) were mostly used and clearly people were more comfortable to discuss in
the vernacular language than in English. Survey moderators, proficient in the three languages, were available
to summarize main points and guide the discussion. The points voiced by the participants were recorded on a
large board, in English, and divided into issues and solutions. This approach made the process simpler for
those joining in late and also gave rise to newer points.
The key points have been summarized into Table 4.
Table 4: Stakeholder Discussion Points
PROBLEMS
POTENTIAL SOLUTIONS
NMT
NMT
1.
2.
3.
Unevenness of footpath surfaces makes them
difficult for disabled people to use.
The footpaths are discontinuous and broken at
many places.
Safety of pedestrians and cyclists is poor.
Public transit
1.
The bus design is not disabled friendly. There
are very high steps which makes ingress and
egress very difficult.
2. The buses are also not friendly for the blind
3. The buses are crowded, which is especially
discouraging for women.
4. There are no seats reserved for women to
encourage them to use the bus.
5. The frequency, routes, network and bus
numbers are not sufficient.
6. Tram services have not been considered.
7. Access to public transit is poor.
8. Students prefer public transit as it is cheap, but
most use private vehicles as they are more
convenient.
9. Buses don’t stop at designated stops.
Amenities
1.
2.
3.
4.
Road signage is poor.
Public toilets are insufficient in number and are
in poor condition.
There are not enough open spaces.
Many plans and studies are never
implemented.
Others
1. The number of private vehicles is increasing.
2. Air and noise pollution are increasing.
3. Traffic enforcement is poor.
1.
2.
Better designs for walking and cycling should be
carried out.
Pilot projects should be created to increase
acceptance by public and government.
Public transit
1.
2.
3.
4.
5.
6.
Bus infrastructure and maintenance and
operations should be streamlined.
Incentives for using public transit should be
provided.
The city should pursue transit oriented
development and planning.
Auto rickshaw stands should be created to
regulate their parking and coordinate pick-ups.
Different agencies should work to better
coordinate their work.
Passenger Information systems should be
brought in to improve the system.
Policies and studies
1.
2.
3.
Traffic studies should be carried out frequently,
as the last one was done in 2007.
Plans and studies should be implemented.
Intelligent Transportation Systems (ITS) could
be brought in for better enforcement.
Others
1. Disincentives for private vehicle use should be
created.
2. Parking should be restricted to curb vehicle
use.
20
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
The FGDs were successful at eliciting the opinions of representatives of a variety of disadvantaged groups.
These opinions will be very helpful moving forwards with planning in the city. However, the FGDs were not
able to foster a conversation among members of the same group to delve into a more detailed analysis of
existing problems. In future iterations of the tool, more focus group discussions should be held, and more
time and resources should be dedicated to planning and conducting the FGDs. This will result in more robust
discussion among members of disadvantaged groups.
21
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
6. HOUSEHOLD SURVEY
The survey was conducted in neighborhoods selected to serve as proxies for the rest of the city. The method
of selecting neighborhoods was based on the neighborhood typologies, including income, distance from the
core, and access to public or informal public transit characteristics, as described in Section 4.2. A group of
public officials and some members of the survey team met and brainstormed a list of neighborhoods that
would likely fit the loose definition of each typology. The list was shortened after discussing the merits of
each neighborhood. Then, the all groups traveled to the neighborhoods to verify whether they met the
typology requirements. After the full survey team arrived, the neighborhoods were revisited and modified as
the definition of the typologies became better defined. Because the typology definitions were not clear
before the neighborhoods were selected, there was some confusion and disagreement about which
neighborhoods should be included to represent the 12 different typologies. The final neighborhoods selected
represented the most typical instances of each typology as possible, with as little variation or ambiguity
about each factor. For example, when selecting a low-income area, preference was given to neighborhoods
that were overwhelmingly low-income over more mixed-income neighborhoods.
To determine the sample size within each neighborhood, time and budget were the constraining factors.
Several methodologies, including the “proportion” and “mean” methods, as well as generally accepted rules
of thumb were considered to determine a final sample size. A more detailed discussion of this process can be
found in the “Quick Guide: Conducting Rapid Household Surveys” methodology. Ultimately, the sample size
was a trade-off between the degree of precision desired and the available budget.
The household surveys were carried out on the 4th, 5th, and 6th of March 2013. Student volunteers from
Nashik Institute of Technology (NIT) and from College of Architecture and Centre for Design (CANS) were
assigned the various neighborhood of the city. The students were divided into groups of 2 and each
neighborhood was assigned many groups with professors supervising each neighborhood.
Before the actual surveys, an orientation/training program was held for all the student volunteers and
professors (supervisors) at the Institution of Engineers. The objective of the orientation was to explain the
background of the project to the volunteers and to train them in the interview process. Sessions on the
walkability survey and the TRAM methodology were presented by CAA and ITDP to introduce the volunteers
to the concepts of sustainable transport, transport planning. Then, a mock interview was held so that each of
the questions and the required answers were understood by both volunteers and supervisors.
22
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 10: Student Volunteers and Other Invitees at the Orientation Program
As mentioned in the methodology report, the neighborhoods were selected based on different combinations
of income levels, location from city centre and connectivity to public transit. A long list of neighborhoods was
prepared during the initial scoping visit in February with the assistance of NMC, ITDP, Clean Air Asia and
Nashik First, a local NGO during a meeting. The selected neighborhoods were also plotted on a map to get an
idea of the spread, with the goal of a somewhat even distribution of surveyed neighborhoods across the city.
During the second visit, a reconnaissance survey was carried out to each of the neighborhoods to assess
whether the neighborhood fit the required typology criteria. Observed criteria for income levels included the
quality of housing, observed automobile ownership, and discussions with local residents and merchants.
Observed criteria for connectivity to public transit were the availability of bus stops, auto rickshaw access,
and resident descriptions of transit access. Location from the city centre was determined through maps of
the city. Based on the neighborhood reconnaissance, the list of neighborhoods was modified as some areas
did not fit the exact category or were more suited to a different category. A total of twelve neighborhoods
were selected, one for each typology. The typologies and corresponding neighborhoods are provided in
Table 5. During the reconnaissance visit, local leaders and/or resident welfare associations were identified
and consulted to seek assistance and cooperation while carrying out surveys.
23
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Table 5: Typologies and Corresponding Neighborhoods
1
2
3
4
5
6
7
8
9
10
11
12
Typology*
Core - Low - Connected
Core - Middle - Connected
Core - High - Connected
Core - Low - not connected
Core - Middle - not connected
Neighborhood
Malar Khan
Dwarka
Near Navsha Ganpathi Temple
Rajiv Nagar and Wadala Gaon
Govind Nagar
Core - High - Not connected
Periphery - Low - connected
Periphery - middle - connected
Periphery - high - connected
Periphery - low - not connected
Periphery - middle - not connected
NA* (No suitable neighborhood)
Utkarsh Nagar
CIDCO & Untwadi
Savarkar Nagar
Sant kabir Nagar
Hanuman Nagar & Satpur Road behind Anuradha Theatre
Periphery - high - not connected
Lawate Nagar
*High, middle, low is based on income category. Core and Periphery is based on distance from CBD. Connected and not connected is based on
public transit accessibility.
24
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 11: Map of survey locations8
8
Blue – High Income, Maroon – Middle, Red – Low income
25
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 12: Survey at Rajiv Nagar
The surveys were conducted from 10 AM to 4 PM each day. Volunteers arrived at the survey neighborhoods
and spread themselves to cover all parts of the area. Each household survey took approximately 20 to 30
minutes to complete, depending on the level of cooperation from the members. Low income households
were usually the most cooperative in providing details of their incomes and travel details of all household
members, as they felt that by sharing information the NMC would implement some improvements. The highincome and middle-income households were more reluctant to provide such information, as they felt that it
might be misused. Most became more cooperative when shown a letter from the NMC and/or student ID
cards, but some households still refused to answer some questions especially those requesting information
about women and daughters attending college.
As a pilot test, there were some problems encountered in the data collection. Some of the volunteers did not
collect the travel information of all members of each household. Housewives were most commonly omitted,
as they and other non-working members were not considered “active” commuters by respondents. Clean Air
Asia and ITDP staff visited the survey areas to inspect completed surveys, provide suggestions for
improvement, and clarify any questions. The observations during the day were discussed with the supervisors
at a meeting in the camp office at the end of the day. The meetings and survey inspections resulted in
dramatic improvements in survey quality for the rest of the survey.
Since the surveys were conducted between 10 AM and 4 PM on weekdays, in many households only a
housewife or retired people were at home. Sometimes these household members could not provide accurate
trip distances for other members of the household. Thus, it may be useful to conduct the survey in the early
26
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
evenings when all members are at home. In some cases, especially in middle- and high-income areas, the
residents did not like being disturbed in the afternoons, when it is common for many people to rest.
The students’ knowledge of both English and Marathi helped in the smooth conduct of the survey in the
different parts of the city.
About 739 households and 2800 members were surveyed. Travel details of over 2000 people were collected.
The surveys as well as the FGD and orientation events were captured in the media by both the Marathi and
English newspapers (Figure 14).9 10
Figure 13: Survey in Sant Kabir Nagar (Source: Colin Hughes)
9
http://articles.timesofindia.indiatimes.com/2013-03-03/nashik/37409983_1_transportation-ngos-city-engineer
http://m.timesofindia.com/city/nashik/Nashik-Municipal-Corporation-signs-MoU-with-NGO-for-better-publictransport/articleshow/18804176.cms
10
27
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 14: News of the survey in the media
28
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
7. RESULTS AND FINDINGS FOR TEST CITY
From the pilot test of the data collection component of the tool, the following results were obtained about
mobility patterns in the City of Nashik. It is important to note that the methodology aims to provide a sketch
analysis of mobility patterns and is not a fine-grained study.
7.1 Household Characteristics
The average household expenses in low-, middle-, and high-income neighborhoods were around USD $155,
$217, and $372 respectively. One of the drawbacks in this data was that many people, especially in middleand high-income households, were not willing to share information related to their expenses as they felt that
it might be misused. Each neighborhood, however, was identified as low-, middle-, or high-income, based on
local information and finalized during the reconnaissance survey, including the type of structure (buildings)
that were present. From this, it was assumed that the households within the neighborhood largely fall into
that income category, somewhat compensating for missing or incorrect household expense information. The
distribution of surveyed households across the income level is shown in Table 6.
Table 6: Break up of number of households based on income levels
Neighborhood
Income Group
No of households
(% of Survey)
Low Income
325 (44%)
Middle Income
287 (39%)
High Income
124 (17%)
The cost per inhabitant was determined based on stated costs for transit and paratransit trips. Based on this
analysis, the average expenditure on transport is around 2% in the surveyed areas, but there is wide variation
in low-income transit expenses (Table 7). Of the expenses, the average cost per capita per month is USD
$3.10. This is slightly lower than the CMP estimate of 4% of total income spent on transit. In general, transit
expenses account for 2-10% of total household income in developing countries11. It should be noted that for
both low and middle-income households, the mode share for walking and cycling trips, made at no cost to
the household, is above 60%.
11
http://cleanairinitiative.org/portal/sites/default/files/Framework_for_Achieving_Sustainable_Urban_Mobility_in_
Asia_-_CAI-Asia_2010_0.pdf, http://www.chinadailyapac.com/article/food-costs-half-poor-families-earnings and
http://siteresources.worldbank.org/EXTOGMC/Resources/336929-1266963339030/eifd16_expenditure.pdf
29
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Table 7: Range of Expenses on Transport
Income group
Expenses Range
Low Income
1% - 7%
Middle Income
1% - 3%
High Income
1% - 2%
It is interesting to compare the travel costs in terms of time spent on transportation. Table 8 shows the
following breakdown. The higher trip times for the lower and middle income groups is likely due to a
much larger number of walking trips than for high-income groups.
Table 8: Average Time Spent on Transport per trip
Income group
Minutes per Trip
Low Income
24
Middle Income
25
High Income
17
7.2 Transport and Travel Characteristics
The household surveys revealed a clear picture of the mobility patterns of people, including trip rates, trip
lengths, mode of travel, amount spent on transit, and travel and waiting times. The survey also captured local
preferences for walking and cycling infrastructure and the environment surrounding those modes. The
environment for public transit (bus) and auto rickshaws use as well as travel characteristics were also
captured in the survey. Additional information collected includes the number of vehicles owned and
accidents suffered in each household.
The results are juxtaposed with the Comprehensive Mobility Plan indicators to understand how the TRAM
survey data compares to previous, more lengthy and costly data collection efforts. Other unique
characteristics that are usually not captured by the CMP are also discussed. An attempt is made to
understand how each factor (e.g. income levels, location and connectivity) affects mobility.
Trip Rate
A trip is defined as the travel undertaken between a single origin and a single destination. A journey from
home to the store and back would count as two trips. The average trip rate for the surveyed area is 2.7,
meaning that the average person makes 2.7 trips per day. This rate increased as income increased, with the
trip rates for low-, middle and high-income families equaling 2.45, 2.69, and 2.92 respectively, indicating a
greater ability for higher income people to travel more. Since the average household in the surveyed area
included 3.7 people, this equals around 10 trips per household per day. Based on this information, the total
number of trips generated per day for the entire city is likely around 4.5 million passenger trips per day.
30
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Table 9: Range of Trip Rate across Income, Age and Gender
0-21 Years
Male
21-60 Years
Female
Male
61+ Years
Female
Male
Female
High Income
2.7-3.3
2.2-3.2
2.5-3.2
2.5-3.4
2.1-4
2-2.3
Middle Income
2.6-3
2.2-2.9
2.3-2.8
2.1-2.7
1.9-3.7
2-7
Low Income
2.4-3
1.9-2.5
2.4-2.6
2.3-2.4
2.4-2.7
1.8-2
Surveyed Area
2.76
2.46
2.62
2.54
2.64
2.52
Table 10: Trip Rates based on Typology and Gender
Typology
Core - Low - Connected
Core - Middle - Connected
Core - High - Connected
Core - Low - not connected
Core - Middle - not connected
Periphery - Low - connected
Periphery - middle - connected
Periphery - high - connected
Periphery - low - not connected
Periphery - middle - not
connected
Periphery - high - not connected
Male
2.58
2.83
3.09
2.45
2.90
2.65
2.85
2.52
2.47
Female
2.28
2.76
2.90
2.36
2.66
2.37
2.45
2.44
2.28
Average
2.45
2.80
3.00
2.43
2.83
2.54
2.69
2.48
2.40
2.63
3.04
2.59
3.36
2.62
3.19
At the city level, males aged 21 and below are found to have the highest trip rate, 2.76, while females in the
same age bracket have the lowest, 2.46. Across income levels, the higher income neighborhoods generated
more trips than middle and low-income neighborhoods. Interestingly, the Comprehensive Mobility Plan
provides a much lower estimate of the per capita trip rate (1.68). This may be mainly due to neglecting
walking trips and other shorter trips. The CMP also suggests that the walking trip mode share is only 28%
while the TRAM surveys indicate 50% walking trip mode share, when evaluated by trip segment. This may be
due to difference in how the mode share was calculated. If data is collected by primary mode, many walk
trips that are segments of other trips would not be included in the results. If data was collected by kilometer
traveled, the shorter length of walking trips would result in a lower percentage of total trip length.
Mode Share by Trip Segment
The TRAM calculates the mode share in a different manner than many traditional approaches. This
methodology evaluates all trip segments, door-to-door, instead of just the primary segment, with all
segments weighted equally. For example, a trip that involves a 10 minute walk, a 20 minute bus ride, and a 5
minute auto rickshaw ride will count as one walk segment, one bus segment, and one auto rickshaw
segment. This method places a greater emphasis on walking and other non-motorized transport modes than
31
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
traditional mode share calculations, which tend to under represent these modes, as they are almost never
consider the “primary” mode. While a relatively small number of trips occur solely by walking, walking
accounts for a large portion of travel, especially for lower-income communities and women. This method
attempts to better accounts for those trips.
One of the major findings of the survey was very high share of the pedestrian segments in the city. Over 50%
of trip segments are made by walking, as shown in Table 11. It should be noted again that this includes
walking trip segments, even when they are part of a larger trip made by other modes. The walking trip
segments differ based on the income category of the neighborhood. However, due to a mixture of land uses
throughout all parts of the city there was no significant walking segment mode share difference between
core area and periphery.
In terms of passenger kilometer travel (PKM), the 50% walking mode share by segment translates to only 14%
of PKM (almost certainly due to shorter walking trip lengths). Interestingly, 12% of bus mode share by trip
segment translates to 32% of PKM mode share (due to longer bus trip lengths)
Table 11: Mode Share of Passenger Trip Segments by Location, Income and Connectivity
Typology
Core - Low - Connected
Core - Low - Not Connected
Core - Middle - Connected
Core - Middle - Not Connected
Core - High - Connected
Periphery - Low - Connected
Periphery - Low - Not Connected
Periphery - Middle - Connected
Periphery - Middle - Not Connected
Periphery - High - Connected
Periphery - High - Not Connected
Surveyed Area
Bus
16%
11%
14%
13%
2%
20%
5%
14%
19%
7%
9%
13%
Car
3%
3%
4%
10%
42%
0%
6%
6%
4%
11%
37%
8%
2
Wheeler
12%
21%
6%
19%
24%
12%
9%
20%
17%
23%
24%
14%
Auto
Rickshaw
17%
20%
9%
4%
9%
15%
15%
10%
8%
9%
7%
11%
Walk
47%
42%
67%
51%
21%
50%
63%
45%
51%
48%
21%
52%
Cycle
5%
3%
1%
3%
2%
3%
3%
4%
1%
2%
3%
2%
32
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
cycle
Auto Rickshaw
2 Wheeler
walk
Taxi
male
f emale
male
f emale
male
f emale
car
Bus
below 21
21-60
61 and above
Figure 15: Trip Mode Share by Segment for Surveyed Areas
For poorly connected low-income areas, such as Wadala Gaon and Rajiv Nagar, two wheelers and auto
rickshaws are a significant source of mobility, accounting for 47% and 30% of trips, respectively. Walking is
also dominant mode among the middle-income areas, ranging from 45%-67% of trips. In Dwarka, a middleincome area in the central city, 67% of trip segments were made by walking, 14% by bus, and 6% by twowheeler. Peripheral and poorly connected areas (Satpur Road, CIDCO, Govind Nagar, Untwadi) have a high
percentage of two-wheeler and three-wheeler trip segments. Hanuman Nagar, another middle-income
peripheral neighborhood, has a high percentage of trip segments by bus (21%). In general, high-income
neighborhoods have lower percentages of walking trips than middle- and low-income areas.
Cycling trips accounted for a significant percentage of trip segments (7%) in the young age group (below 21
years). With increasing age, the popularity of cycling diminishes, accounting for only 3% of trip segments for
the 21-60 age group.
33
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Auto
Rickshaw,
12%
Cycle, 2%
Bus, 32%
2
Wheeler,
26%
Car, 13%
Walk, 14%
Figure 16: Mode Share by Passenger-km
Vehicle Ownership
The city has motorization index of 300 -- 300 vehicles for every 1000 people. The survey corroborates this;
75% of households own a motorized vehicle in the city. Average vehicle ownership per household is 1.24
vehicles. The ownership varies with income category and public transit accessibility, as seen in Table 12.
Neighborhoods well connected by public transit appear to have lower vehicle ownership rates across income
profile. This is a significant finding from the survey and it supports the idea that improvements to transit
access in neighborhoods will reduce motor vehicle ownership and use, regardless of income levels.
Table 12: Percent of Households Owning Vehicles by Neighborhood Typology
Typology
Core - Low - Connected
Core - Low - not connected
Core - Middle - Connected
Core - Middle - not connected
Core - High - Connected
Periphery - Low - connected
Periphery - Low - not connected
Periphery - Middle - connected
Periphery - Middle - not connected
Periphery - High - connected
Periphery - High - not connected
Car
7%
11%
24%
38%
91%
4%
5%
29%
38%
48%
91%
cycle
21%
13%
18%
25%
18%
17%
20%
26%
25%
14%
28%
2 Wheeler
33%
70%
56%
78%
94%
50%
54%
83%
78%
72%
72%
34
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Interestingly, while 19% of the households own a cycle (non-motorized), cycling constitutes only 3% of all trip
segments. Thus there may be a latent demand for better cycling infrastructure to make use of these cycles. In
addition, nearly 50% of households did not have dedicated motorized vehicle parking space, indicating a
reliance on informal vehicle storage solutions.
80%
67%
70%
60%
50%
40%
30%
26%
19%
20%
10%
4%
0%
Car
cycle
2 Wheeler
Auto Rickshaw
Figure 17: Citywide Vehicle Ownership
In low-income neighborhoods, over 50% of households own motorized two wheelers, with even higher
percentages in areas of poor connectivity such as Rajiv Nagar (70%) and Wadala Gaon (67%). However, in
well-connected core areas like Malhar Khan the ownership is much lower (33%), again indicating that with
availability of good public transit people may be less likely to own and use personal vehicles.
In the high-income neighborhoods such as Lawate Nagar and near Navsha Ganpati Temple, car ownership is
as high as 90%. Two wheeler ownership is also above 70% in all 3 high-income neighborhoods. Savarkar
Nagar, better connected than other high-income areas, has lower car ownership rates (48%).
Middle-income areas register higher ownership of two wheelers. Poorly connected areas (Govind Nagar,
Satpur Road, near Anuradha Theater) and peripheral areas (Hanuman Nagar, CIDCO, Untwadi) have very high
ownership of two wheelers (over 75%) and higher than average car ownership (over 25% in most areas).
Dwarka, which is within the core area and is well-connected, has the lowest level of two wheelers ownership
(56%), and higher percentages of walking (67%) and bus (14%) trips.
Average Speed
Average speeds were determined from survey respondent estimates of travel times and distances. Some
of this data was removed as it was beyond physical possibility. The remaining data is also less reliable, as
respondent recollection of distances and times are rarely accurate. Many respondents also estimated
these results for other members of the household. Figure 18 provides the average speeds for different
modes. Core areas of the city had lower speeds compared to the peripheral areas. Also the bus speeds were
35
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
lower than the car. The current speed of public transit buses is comparative to larger, more congested Indian
cities like Bangalore.
Cycle
9
Auto Rickshaw
12
2 Wheeler
18
Walk
5
Taxi
20
Car
22
Bus
17
0
5
10
15
20
25
Figure 18: Average Speeds (kmph) of Different Modes
Trip Lengths
The average trip length in the surveyed areas is around 5km. Nearly 80% of the passenger trips in the city are
under 5km, a reasonable distance to travel by bicycle. The CMP results show a 4.3km average trip length
including walk trips and 5.8km length excluding walk trips. People in the age group of 21 to 60 have the
longest trip lengths, with males travelling longer than females. Core areas have comparatively lower trip
lengths than the peripheral areas. Figure 19 shows the average trip lengths in the city.
36
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Cycle
3.1
Auto Rickshaw
4.1
2 Wheeler
5.7
Walk
1
Taxi
5
Car
7.2
Bus
8.8
0
1
2
3
4
5
6
7
8
9
10
Figure 19: Average Trip Length (km) by Mode in Surveyed Areas
Below
61 and
21 21-60 Above
Lower income members range from 3.7 to 6.5km across gender and location, while middle-income members
range from 4.3 to 6.9km and high-income from 4 to 6.4 km.
Female
Male
Female
Male
Female
Male
3.26
2.64
3.70
6.29
4.10
4.84
-
1
2
3
4
5
6
7
Figure 20: Average Trip length (km) of City Travel by Age and Gender
Average Fuel Efficiency
The average fuel efficiency values for different vehicles based on the surveys are shown in Figure 21 below.
The results of the study correspond to the results of other studies on vehicles fuel efficiency in India,
indicating that the fuel efficiency values are well known to vehicle users.
37
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
60
48
50
40
28
30
20
16
10
0
Car
Auto Rickshaw
2 Wheeler
Figure 21: Average Fuel Efficiency in kmpl
Other Insights
a) Over 3% of households include persons with disability.
b) 18% of interviewed households have one or more member involved in recent traffic accidents.
c) Nearly 15% of residences are more than 30 years old (with 5% more than 60 years old). Older houses
are generally located the low-income areas.
d) Cost per passenger kilometer travel for two wheeler is comparable to bus travel
Priorities
During the survey, residents were asked to rank the top priorities for transportation improvements from a list
of options provided in the questionnaire. The top 3 most priorities for each mode are listed in Table 13.
Table 13: Top Priorities of Citizens
Mode
Pedestrians
Auto rickshaw
Cyclists
Top Priorities
Separate footpaths for walking
Clean and clear street edges
More trees and greenery
Greater safety
Less waiting time
Lower fare
Separate tracks for cycling
Secure cycle parking
Cycles available for short-term (30 minutes) borrowing
38
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Public transit
Greater safety
Less waiting time
More seating
Interestingly, there is not much of the difference between the priorities among the gender groups. However,
the priorities differ by income level and neighborhoods but no clear trend could be established using income
and area differentiation.
7.3 Summary of Preliminary Findings
The following is a summary of preliminary findings about the city of Nashik, based on the results from the
areas that were surveyed. These findings will provide the base point from which proposals for improvements
to the city’s transportation system can viewed. It should be repeated that the survey only covered a selection
of neighborhood typologies that together will represent all other areas of the city. Therefore, while the
results for each typology are final, the citywide conclusions drawn here will vary depending on the
distribution of typologies across the city.
a) Transport expenditure of low-income groups varies from 1 to 7% of total monthly expenses.
b) Neighborhoods that are well-connected by public transit have lower vehicle ownership rates across all
income levels.
c) 50% of trip segments are made by walking, with a citywide average walk trip length of 1km. Peripheral
areas include high rates of walking trips despite poor walkability.
d) Nearly 80% of the passenger trips in the city are less than 5km.
e) The current speed of public transit buses in Nashik is comparable to more congested Indian cities like
Bangalore.
f) The average household among those surveyed generates around 10-12 trips per day.
g) Nearly 50% of households do not have a dedicated parking space.
39
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
8. ANALYSIS OF TRANSPORT INTERVENTIONS USING TRAM
TRAM allows users to evaluate the impacts of several different scenarios for future transport sector
investments based on data from the household surveys and the TEEMP City tool, specifically modified to
work with the TRAM methodology. The following section describes the analysis of several interventions into
the transportation system. The findings of citywide transportation characteristics, described in Section 7.3,
show that the city has high rates of walking, good transit access, slow transit speeds, and low levels of car
ownership, especially along transit corridors. Based on these results, the following three different
intervention scenarios were developed and analyzed:
1. Business-As-Usual Scenario – The represents the types of investments that have been taking place
recently in the city. Most of this investment focuses on reducing motor vehicle congestion through
flyovers and other road expansions and improvements.
2. Metro-Focused scenario – This represents a proposed scenario to invest heavily in metro systems for
Nashik. Most money is invested in Metro systems, with some additional money invested in
pedestrian walkways, mainly in areas surrounding metro stations.
3. Sustainable Transport Scenario – This scenario represents an investment scenario that focuses on
developing a comprehensive BRT network, with a complementary bicycle network and pedestrian
network providing access to short distance destination and BRT stations. If feasible, additional funds
would go to a bike share system.
The results of the intervention analysis are shown in Figure 22. The Business-As-Usual Scenario may
contribute to move more people, but it has very little effect on CO2 emissions and is skewed towards higher
income populations. The Metro-Focused Scenario can benefit many poor residents, but it has a high cost, and
will likely take the longest to implement. It also produces a significant reduction in CO2 emissions by 2030.
The Sustainable Transport Scenario produces the largest benefits, which skew towards low-income
populations. The Sustainable Transport Scenario also has significantly lower costs than the Metro-Focused
Scenario and produces much higher levels of CO2 emissions reductions than the other scenarios. Each
scenario is described in greater detail below.
Project characteristics
Type of Project
Scenario 1: BAU
Flyover
Scenario 2: Metro- Metro/Rail
Focused
Pedestrian Walkway
Scenario 3:
Sustainable
Transport
BRT
Pedestrian Walkway
Bicycle Network
Opening
Year
value
Unit
Cost
(million
USD)
Beneficiaries (No. of people)
Low
Income
Middle
Income
High
Income
CO2 Savings
Cost
Cost
Savings
per ton CO2
per
Annual Savings
TOTAL
through 2030
Savings
Beneficiary (tons / year)
(tons)
($ / ton)
750,000
80
n/a
2018
100 lanes
60
153,426
467,196
129,378
2024
2014
10 km
300 km
TOTAL
370
12
382
46,379
136,771
183,150
158,151
355,917
514,068
5,470
36,282
41,753
210,000
528,970
738,970
2017
2015
2016
50 km
600 km
120 km
TOTAL
120
24
18
162
154,596
273,542
294,913
723,051
527,169
711,834
663,746
1,902,750
18,234
72,564
145,978
236,777
700,000
1,057,940
1,104,637
2,862,578
517
62,000.00
0.02
62,000.02
434,000.00
0.41
434,000.41
880
57
250,000.00
0.05
30,000.00
280,000.05
3,500,000.00
0.77
450,000.00
3,950,000.77
41
Figure 22: Results of Intervention Analysis
40
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
Figure 23: Results of Intervention Analysis
Business as usual scenario
In the Business as Usual scenario a total of 25 four-lane flyovers would be built at an estimated cost of
approximately 60 million US Dollars. The total project would benefit an estimated 750,000 people with access
to motor vehicles, most of whom would be vehicle owners in the middle or upper income bracket. This
comes at a cost of $80 per person benefitting, the second lowest of the three scenarios. While nearly all highincome residents could benefit (97% own motor vehicles), a much smaller proportion of low-income
residents (55% own motor vehicles) could benefit.
41
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
The construction of new flyovers would likely lead to slightly shorter trip times for each motor vehicle trip.
However, these benefits would likely be limited to the short term, as this approach would encourage
increased automobile use which would quickly occupy the additional capacity of the new facilities, reducing
the amount of time-savings they provide. While the separation of some motor vehicle trips from pedestrian
and cyclist trips might improve safety in the short term, the overall trend towards increased motor vehicle
use would likely reduce safety in the medium and long term.
The scenario has very few benefits to the population that does not own motor vehicles. These populations
might experience decreased mobility from the construction of roadway improvements that limit the number
of places where it is possible to cross a roadway on foot or by cycle. As the construction of road
improvements will likely induce more driving, the emissions reductions from decreased congestion would be
offset by more vehicle trips, results in no overall reduction in CO2 emissions.
Metro-focused scenario
The Metro-focused scenario would include the construction of a 10km metro system, at a cost of 370 million
US Dollars. This project would move over 210,000 people per day, most of whom currently use public transit
or auto rickshaws. The benefits come at a cost of nearly $517 per person benefitting, by far the highest cost
of the three scenarios. The system would provide large time savings for many trips along the metro corridor,
as well as shorter wait times, and more reliable trip times. However, the time to plan and complete a metro
system would likely stretch at least 10 years, for an opening date of 2024 at the earliest. The scenario also
includes 300km of new pedestrian footpaths to provide better access to metro stations at a cost of 12 million
US Dollars. With a total of over 3,000 km of streets in Nashik, this would be equivalent to new footpaths on
10% of city streets. The footpaths would benefit an estimated 530,000 residents in the city, who would
experience a more comfortable and safer walking environment.
These benefits from these two interventions would likely continue over many years, as the footpaths
continue to allow improved pedestrian access to the metro. With a cost of $390 million, this is the most
expensive scenario. The yearly CO2 savings under this scenario are 3.5 million tons of CO2 by 2030, at a cost
of $880 dollars per ton mitigated by 2030. This is significantly less cost-effective than the Sustainable
Transport Scenario, partly due to the long time period required to design and construct a metro system.
Sustainable Transport Scenario
The Sustainable Transport Scenario would include the construction of a 50km bus rapid transit system, at a
cost of 120 million US Dollars. The BRT component of this project would move over 700,000 people per day,
most of whom currently use public transit or auto rickshaws. The system would provide large time savings for
many trips along the BRT network, as well as shorter wait times and more reliable trip times. The scenario
also includes 600 km of new pedestrian footpaths to provide better access to BRT stations and destination
between, at a cost of 24 million US Dollars. With a total of over 3,000 km of streets in Nashik, this would be
equivalent to new footpaths on 20% of city streets. The footpaths could benefit up to 1,000,000 residents in
the city, who would experience a more comfortable and safer walking environment. Finally, the scenario
includes a 120km bicycle network, at a cost of $18 million. This would also benefit approximately 1,000,000
residents, providing bicycle access on 4% of the city’s streets. The pedestrian and bicycle improvements
benefit a wide cross-section of the city’s population, including those with walking trips, and those with short
42
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
bus and auto-rickshaw trips. The projects would improve safety and comfort and provide an additional choice
in mobility. The benefits come at a cost of approximately $57 per person benefitting, the lowest cost of the
three scenarios.
By reducing the need for a private automobile, the benefits from these interventions would likely compound
over the years by limiting the increase in congestion and pollution. By 2030, the scenario is estimated to
reduce CO2 emissions by 3.9 million tons, which at a price of $41 per ton of CO2 mitigated, is the most costeffective of the three. With a total scenario cost of $162 million, this is the second most expensive scenario,
but the one with the highest cost-benefit. This scenario will benefit more citizens of Nashik – and, notably,
more poor citizens of Nashik – over a much longer period of time and reduce more greenhouse gases all at a
lower price
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
9. KEY TAKEAWAYS BASED ON PILOT TESTING
The pilot test of the TRAM tool provided a number of lessons about the tool. This section first provides a
detailed summary of the lessons learned from the test. Then, a general overview of the main successes,
shortcoming, and opportunities for improvement is provided.
Detailed Takeaways
The following section summarizes the details of specific takeaways from the pilot test of the data collection
portion of the TRAM tool.
a) The analysis of the city’s income distribution was difficult to complete, as no group of experts
knowledgeable in the entire city was available. A separate data collection methodology was used
instead.
b) The citywide analysis to classify the city into different typologies should be conducted before
selecting the neighborhoods to survey. This way, neighborhoods can be selected from the typologies
in the city that have already been agreed upon making the process quicker, more consistent, and
more transparent.
c) A greater number of focus group discussions should be conducted to produce a wider range of
responses. Also, the focus groups should be better segregated to ensure that members of different
groups feel free to discuss their thoughts and elaborate on the thoughts of other participants.
d) The Survey Form could be simplified to enable people to understand the questions better and
complete it faster. In general, the survey form should replace fill-in-the-blank questions with multiple
choice answers wherever possible and provide greater detail on the type of data requested. This
would make data collection and entry faster and more accurate. It will also reduce the burden of
researcher to clean up the data. Form 3, particularly need revision as it was time consuming and
confusing to many people. Some data on the form was redundant and can be removed.
e) The survey form could also be revised to produce better results for income. The income field was
changed to a range to seem less probing of specific details about the family. In future versions, the
question could be moved to the end of the survey, where the information is more likely to be
provided.
f) Surveyors could be better trained to recognize errors during the survey, such as 1 km trip that takes
20min in a two-wheeler. Volunteers could probably request again for realistic answers. Finally,
expense and income data can be collected in ranges to account for privacy concerns.
g) The survey could start early in the day or on a holiday, times when the key decision maker in the
family is more likely to be at home. Members of middle- and high-income households did not like to
be disturbed in the afternoon as they were resting at that time.
h) Involving students was a good initiative as they not only understood the importance of the survey
but were also educated and trained in sustainable transportation.
i) The scoping visit to finalize neighborhoods was essential. Reconnaissance of neighborhoods should
be carried out to verify if the neighborhoods fall under the required typology. It would be ideal not
to have areas with mixed income groups; but if it cannot be avoided, the volunteers and supervisors
should be explained carefully on the type of household to approach. While income can often be
estimated based on the type of structure, it can become very difficult to differentiate, for example,
between a (upper end) low-income and (lower end) middle-income house.
j) Support of the local administration is obligatory. This will bring in other stakeholders and garner
greater acceptance from the citizens.
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Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
k) Meeting with local representatives for access to households is very important, especially in middleand high-income areas, where people are wary of giving out personal data such as travel routes, time
and income, especially data concerning women and daughters in college.
l) A good grasp of local language is very important. The focus group discussions should be ideally
carried out in the local language to help lower income groups and other marginalized people feel
comfortable to speak freely. The survey forms should also be translated into the local language for
greater ease.
m) Data collected and analyzed using TRAM tool provided valuable results in the mobility pattern of the
pilot city. The TEEMP-City tool should be modified so that more results from the survey are scaled up
to represent the entire city.
n) The detailed reports of Comprehensive Mobility Plan from Nashik can be collected and analyzed
using the CMP component of TEEMP-City tool to evaluate the mobility plan impact and suggest
necessary alternatives based on current data collection efforts.
o) The analysis of the transport intervention scenarios requires careful scaling to ensure that a plausible
scenario is proposed. The current methodology assesses project impacts on a linear scale. However,
for most projects the scale of impacts grows along an S curve. For smaller project sizes, each
additional unit of project produces more benefit that the unit before it. For example, 5km metro
system will move more people per km than a 2km metro system, by providing access to more
destinations. For larger project sizes, projects may reach a saturation point, where fewer people
benefit from additional unit of project. For example, if a 40km metro system already covers most of a
city, a 50km system will move fewer people per km than the 40km system. A future revision could
address this shortcoming.
p) The intervention analysis does not provide much quantitative detail about the cost, time savings, and
safety impacts of various projects. These factors could be added to future revisions of the tool.
q) The intervention analysis is limited to only six types of intervention, omitting some frequently-used
project types. More interventions could be added in a future revision of the tool.
r) The intervention analysis is limited to short-term impacts. It does not account for the changes to the
physical structure of the city that typically occur based on transportation interventions. BRT and
Metro tend to drive up housing demand near stations, leading to a more compact city, whereas
highways and flyovers tend to encourage lower-density development at the outer edges of a city.
These developments, in turn, change the overall mobility patterns of the city. A future revision of the
tool could address these long term impacts of various intervention scenarios.
Overall Assessment
Generally, the survey was quite successful at providing useful and detailed data about travel patterns for a
carefully selected, diverse group of neighborhoods and people in Nashik. The household surveys and focus
group discussions were conducted with relatively few problems. The problems that were encountered helped
the team to revise and improve the tool for future applications. The neighborhoods that were surveyed
represent a wide range of income groups, levels of transit access, and locations in the city. The data collected
provide an interesting snapshot into mobility patterns in the surveyed areas. The methodology used to
expand the data to represent the entire city also seems to provide a good estimate of citywide trends,
although it is difficult to verify this assessment.
The pilot test experienced some difficulty in the classification of the entire city and the analysis of proposed
interventions. The original methodology for classifying income levels was not possible, and the revised
methodology was much more time and resource intensive than intended. More critically, for the analysis of
intervention scenarios, there was difficulty developing an appropriate scale of intervention scenario, there
was limited range of results, which were at a very low-level of confidence.
45
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
With some modifications, this data collection methodology can be very effective in cities with little capacity
or resources, providing an alternative to the traditional, resource-intensive city-wide mobility surveys. The
citywide expansion methodology could be slightly modified to ensure a smoother collection of data and
selection of survey neighborhoods. The analysis of interventions can also be useful, mainly for cities with very
little direction for future transportation improvements. There are, however, many more shortcomings with
the intervention analysis, and improving them would require a significantly larger amount of resources, and
the resulting tool might still generate limited impact on the process of urban transportation planning in many
cities. Thus, investments to improve the tool will likely provide the best value if directed towards further
developing the data collection methodology.
46
Tool for Rapid Assessment of Urban Mobility – Pilot Test in Nashik City
ANNEXES
Annex A. List of Stakeholders
Name
Ravindra Patny
Hari Raj Pardesi
Ashwini A N
Amrutha Pawar
Anagha Patil
Dhananjay Risodkar
Arun Talekar
P B Chavan
Kuldeep Chaware
Shantanu Autade
Pradeep Kale
Deepal Jhadav
Purshotam Puri
Sanjay Joshi
Manoj Gupta
Nilesh Chavan
Krunal Patil
Shailesh Devi
Dhananjay Shinde
Gurmeet Bagga
Mamta Patel
Occupation/Representative Group
Educationist, Handicapped
Visually handicapped
Private sector
Women's Representative
Architect
Architect
Media
Govt.
Urban Designer
Urban Designer
Architect
Architect
Doctor
Architect
Architect
Architect
Education, Citizen
Architect
Architect
Corporator
Student
47