planning a bus rapid transit system for tiruchirappali city
TRANSCRIPT
2nd Conference on Transportation Systems Engineering and Management
NIT Tiruchirappalli, India, May 1-2, 2015.
Paper Id: 216
PLANNING A BUS RAPID TRANSIT SYSTEM
FOR TIRUCHIRAPPALI CITY
Korukonda Vinay1., Samson Mathew
2.
1Post Graduate student, Department of Civil Engineering, NIT Tiruchirapalli, 620015
2 Professor, Department of Civil Engineering, NIT Tiruchirapalli, 620015
Abstract
One of the major critics on the existing urban transportation system is the mobility inside the
city. The mobility can be greatly improved by proper utilization of available road space and BRT
is regarded as such system that provides sustainable, economical and environmental friendly
transport mode by reducing the role of private vehicles. This project aims to study the existing
transport system in Tiruchirappalli and to propose a Bus Rapid Transit system, to be introduced
in the city. Potential route is identified by carrying out feasibility analysis (Road Inventory
Analysis, Demand Analysis) across the selected corridors in the city. Apart from that a Stated
preference survey is being conducted to study the willingness of commuters to shift from their
current mode towards the newly proposed BRTS. Mode shift analysis was done by constructing
a discrete choice model, which helps to estimate the potential shift towards the BRTS. The
results of this study revealed that a corridor connecting the central bus stand to K.K.Nagar (via
Simco meter) is the potential corridor that can be recommended for implementing BRTS in
Tiruchirappalli city and also shown that the factors that are significantly affecting the mode
choice for stated preference are travel time, proportionate travel cost with Income, Age,
Ownership and distance. It can be concluded that BRTS can be regarded as a step towards a
sustainable transport system in terms of cost-effective mass transit solutions with less
environmental impact.
Keywords: Sustainable transport modes, Bus rapid transit system, Corridor assessment,
Commuter preference survey, Stated preference survey
1. INTRODUCTION
With rapid growing economy and population in the cities, transport demand has been
substantially increasing on the city roads. Bus is the main urban transit system used in most
Indian cities and gradually, its level of service is declining due to inadequate capacity, time
management and other financial related issues. In the absence of adequate and efficient bus
transit system, the potential bus users are shifting towards own transport namely Motorized 2-
wheeler or cars whereas, some of them may resort to use para-transit modes available in that
locality. Thus, the rapid multiplication of private vehicles leads to substantial reduction of
available road space at any instant of time, and thus it is nearly impossible to impose lane
discipline resulting in enormous delay and uncertainty in the bus schedules. So, Indian cities
desperately needs Sustainable transport development plans.
Sustainable transport development plans are considered as the replacement of routine
approach of building more roads to alleviate congestion with an integrated transport system
which is affordable, space and resource efficient, and minimizes environmental impacts.
Sustainable transportation approach improves the mobility on urban network by improving
existing mode for its best, means greater reliance on non-motorized mode for local travel,
increased use of public transit in urban areas, a reduction of personal vehicle use. As Bus is
regarded as main urban transit system, the provision of separate bus lanes is regarded as much
affordable and sustainable mobility option.
Tiruchirappalli, the fourth largest city of Tamilnadu State, currently experiencing a fast
growth rate of 2.6% p.a traffic volume and urban sprawl has raised to 167.23 sq.km from 146.9
sq.km in the past decade, but the travel demand of private vehicles raised to 40% as per the
ITDP report. Inorder to improve the attention of passengers towards sustainable public transport
BRTS is regarded as an effective and economical solution.
Along these lines, the objectives of the present paper is to contribute to the literature in
two ways. First, selection of the corridor for the proposed BRTS and Secondly, the analysis of
modal shift from private vehicle to proposed BRTS by using an appropriate mode-choice
modelling technique.
2. LITERATURE REVIEW
Tuhin subra maparu and Debapartion pandit (2010) explained a methodology for the
selection of bus rapid transit corridors with a case study of Kolkata. The main criteria for
selecting a BRTS corridor in a city helps to improve the bus transit time as well as ridership .
The route has been selected based on demand available and feasibility. The data collected was
Buses O-D matrix, ridership, V/C ratio and available land width. The collected data is analysed
by dividing study area into zones based on administrative wards and later found the O-D matrix
between each zone and sorted out the bus routes which are provided with more number of buses
and mapped all the routes in GIS and found the ridership along these routes based on the
frequency and occupancy. After estimating individual ridership, the total ridership of
overlapping routes are calculated and assigned scores based on 100. Similarly scores are
assigned to V/C and ROW of the routes to check the feasibility. Finally they have selected a best
corridor based on the demand and feasibility in implementation.
Rakesh kumar et al. (2014) analyzed the commuter mode choice to proposed BRTS in surat
from private vehicles by examining the behavioral responses of private vehicle users. Spatial and
income differences of individual commuters have significant impact on modal shift were
collected through home-interview survey using Revealed and Stated preference approach. Binary
Logit analysis was carried out in Biogeme environment to model the private users responses
through their stated choices. The model derived a linear utility relation between spatial and
income differences data which is used to predict the mode choice. The results show that low
income people will have an effect of cost of travel whereas high income people have no much
effect on the travel cost.
Rastogi and Rao (2003) studied the characteristics of travel of commuters accessing transit
stations in Mumbai, to identify the policies that can improve the transit access environment.
They conducted a survey on transit access in the households of areas related to two transit
stations using the technique of face-to-face personal interview. The survey was designed to
collect the revealed and stated information, including household and vehicular characteristics,
trip maker characteristics, trip characteristics, new mode acceptability, willingness to shift,
access environment information, and responses under policy options. The micro-level analysis of
the data revealed that a certain relationship exists between the economic status of the commuter
and the vehicle ownership of household and the distance at which they live from the transit
station. The results indicate that commuters with better socio-economic status were found less
accommodative towards walking or bicycling modes, whereas, those at lower or middle
economic level and residing at longer distances from the suburban rail stations were identified as
potential-shifters.
Alvinsyah et al. (2005) tried to observe public transport user attitude due to the
introduction of a new public transport system in Jakarta. A binomial logit model was developed
based on stated preference (SP) data, has been developed as a tool to analyze people attitude
toward the proposed new system. Travel time saving and travel cost saving are considered as the
main variables compared with other collected data for the developed utility function. Data of
public transport user based on SP method was collected along the proposed corridor of Jakarta
Busway system and the utility equation is modelled in Biogeme Environment. Based on utility
values the probability of selecting the proposed system is observed. The analysis of revealed that
eventhough new system with better service is introduced, its probability is still relatively low,
because this system only serves at one corridor at relatively short distance, hence its accessibility
is relatively lower than the existing service and in addition the total travel cost spent by the user
is relatively higher than the existing one. Yet, from the model, it is also shown that not all public
transport users is always shifted to the new and better system due to several reasons.
3. METHODOLOGY
As discussed in the introduction and literature review, this paper identifies potential corridor and
estimates the probable modal shift towards BRTS along the corridor. The study was carried out
in two steps.
In the first step, a potential corridor between two major nodes is identified based on Demand and
feasibility (RoW).
In the second step, descriptive analysis was carried out to find the various variables that affect
the mode share with the introduction of BRTS along the corridor. Questionnaire survey method
was used to collect required data for model development. Binary Logit model was employed to
estimate the modal shift from each vehicle to BRTS.
4. STUDY AREA – CORRIDOR SELECTION The study is conducted in urban area of Trichy city to connect the two important nodes with
BRTS to improve the existing mobility and also to plan the future Institute for Transportation
and Development Policy (ITDP), have identified that K.K.Nagar and Central Bus Stand needs to
be connected through BRTS. There are two routes connecting these important nodes as shown in
fig(i) and fig(ii)
The potential corridor was selected between the two routes by analysing the each and every
corridor with respect to existing demand (Traffic volume survey), connectivity to important
nodes and Availability of road width (Road Inventory survey) and assigning scores to each
corridor proportionately as shown in tables 1 to 4.
Table 1: Average Ridership along the route
Road Stretch Length of
Road(km)
Average Frequency
(buses/hr)
Average Demand
(passengers/hour)
Peak hour
demand
(passengers/hour)
Route-1 5.64 37 1318 2334
Route-2 5.05 10 335 584
Road Inventory survey was conducted using Roadometer to find RoW and important
nodes are also identified parallely and are summarized below:
Fig(i) Route-1 K.K.Nagar – Simco
Road – Central Bus Stand Fig(ii) Route-2 K.K.Nagar – Kajamalai
Road – Central Bus Stand
4%
55%
16%
4%0%
20%
2%0%
29%
46%
2%5%
14%
4%
0%
10%
20%
30%
40%
50%
60%
less than
10m
10.0m to
12.0m
12.0m to
14.0m
14.0m to
16.0m
16.m0 to
18.0m
18.0m to
20.0m
20.0m to
22.0m
% R
oa
d L
en
gth
ROW
Road 2
Road 1
Table 2 : Existing activities/ destinations along the route
Connectivity
to Nodes Destinations Grand
Total
Corridors
Administrative
Centre
Commercial
Centre
Industrial
Centre
Institutional
Centre
Recreational
Centre
Transport
hub
Route-1 5 2 0 11 2 11 32
Route-2 4 3 0 12 3 11 34
Table 3 : Existing RoW along the route
Corridor Length of
Road(km) Existing ROW (m)
Route-1 5.64 10.8-20.2
Route-2 5.05 9.6-20.2
Fig. 3: Distribution of Road Length by ROW
Table 4 : Priority Ranking for Potential BRT Routes
Based on the priority ranking Route-1 is proposed as the feasible corridor for BRTS.
Corridor Connectivity to
Nodes Score Demand Score Trip Length Score ROW score Total Score Rank
Route-1 94.2% 100% 83.5% 100% 377.7% 1
Route-2 100% 25.1% 100.0% 66.2% 291.3% 2
No
vehicle,
9%
1vehicle,
20%
2vehicles
, 38%
3vehicles
, 21%
4vehicles
, 12%
5. DATA COLLECTION: The proposed corridor connects the central bus stand and passes through Railway station.
Therefore, this corridor is strategically very complex with respect to modal shift analysis. With
the identified variables from the literature, the data was collected with the help of a
questionnaire. Using RP and SP approach, household survey is conducted along the proposed
BRTS corridor and response of 289 individuals has been recorded. The responses are collected
from Government and Private employees, students.
6. DATA ANALYSIS:
Among the total respondents, 62% are males and 38% are females. The data is mainly
collected from workers and students as those trips are considered to be major trips contributing
for modal shift. Fig.(iv) and Fig.(v) shows the age distribution and income distribution of the
sample.
age<10 yrs
5%
10 to 25 yrs
35%
26 to 40 yrs
21%
41 to 60 yrs
32%
61 to 75 yrs
6%
>75 yrs
1%
<10000
11%
10000 to
25000
43%
25000 to
50000
31%
>50000
9%
missing
6%
Fig.(iv) Age distribution of the sample Fig.(v) Income distribution of the sample
Cycle, 16%
2W, 46%
Car, 29%
Auto,
9%
Others, 0%
Fig.(vii) Household vehicle availability of Bus users Fig.(vi) Vehicle Ownership of all income groups
Fig.(vi) and Fig.(vii) shows the vehicle ownership of all income groups and household vehicle
availability of bus users. About 46% of the sample households own 2-Wheelers and from the
analysis it is found that bus has the highest average trip length of 12.13 kms and the average trip
length distribution of each mode for all type of trips are shown in the fig.(viii)
Based on the SP approach the statistics obtained show an overall willing to shift of about 38.8
percent passengers towards BRTS. The statistics are further analysed with respect to current
mode and income and are presented in fig.(ix) and fig.(x). The analysis in terms of current mode
revealed that 2-Wheelers group show greater shift when compared to other modes whereas in
terms of income, middle income group show greater shift when compared to low and high
income groups.
1.72
7.41
3
12.13
8.13
0
2
4
6
8
10
12
14
Walking 2W Auto Rickshaw Bus Car
Av
g.
trip
le
ng
th in
km
s
Fig.(viii) Average trip length per mode
2747
266
31
137
4
54
179
3
87
0
30
60
90
120
150
180
210
240
No
of
pe
rso
ns
Cases willing to shift to
BRT
Cases not willing to shift
to BRT
Fig.(ix) Percentage of people willing to shift towards BRTS
7. CHOICE MODELLING: The second part of the study focuses on analyzing commuters travel preferences/ behavior towards
the attributes of the proposed BRTS, a binary choice model was constructed where an individual had
to choose between two alternate set of attribute options of the hypothetical mode. The choice
attributes used for modelling are out-vehicle travel time, In-vehicle travel time, Travel Fare, Travel
distance, Occupation and H.H.Income which were all varied over individual level. The model was
used to derive polynomial linear utility function and an estimation of the relative importance of
the proposed BRTS attributes and the correlation of these attributes were analysed using SPSS.
According to random utility theory, each individual tries to maximize their utility or they prefer
the mode which is having maximum utility among the available alternatives. For the study a
binary choice models were constructed based on their choice of willingness to shift from current
private mode to BRTS. Probability of choosing a particular mode is given by:
�������� = �� ���
��������� + �� ���
Where,
P(Mbrts) = Probability of choosing brts mode; Mcar M2wheeler Mauto-rickshaw
Ubrts = Deterministic part of brts mode utility.
22
5839
13
132
3
38
31
7
79
0
20
40
60
80
100
120
140
160
180
200
220
<10000 10000
to
25000
25000
to
50000
>50000 Overall
No
of
pe
rso
ns
Cases willing to shift
to BRT
Cases not willing to
shift to BRT
Fig.(x) Percentage of people willing to shift based on Income groups
The variables such as income, occupation, gender and trip length, representing individual attribute,
which have same values for both options, are put into only one of the utility equation whereas, the
variables dependent on the alternative mode, such as travel time, travel cost appear in both equations.
�������� = �� + �� � + �! ! + �" " + �# # + �$ $ + �% %
Where x1 =Occupation (Students-1, Workers-0); x2 = Income; x3 = Trip length in kms; x4 =
Gender (Female-1, Male-0); x5 = Travel time in mins; x6 = Travel cost/ Income;
a0, a1, a2, a3, a4, a5, a6.. = regression coefficients.
����� = �$ $ + �% %
The household data is analysed using SPSS and the regression output summary of all the models
were shown in Table 5.
Table 5 : Regression Analysis Output of SPSS
Parameter M2wheeler Mcar Mauto-rickshaw
Value T Sig Value T Sig Value T Sig
a0 -0.861 -1.76 0.08 12.86 2.01 0.05 1.59 2.5 0.02
a1 0.569 1.95 0.05 0.41 1.09 0.28 0.82 1.28 0.21
a2 0.0000674 2.77 0.01 -0.00065 -2.29 0.02 0.0009 1.4 0.17
a3 -0.56 1.98 0.05 -0.67 -1.44 0.15 -0.59 -1.52 0.14
a4 0.149 2.01 0.04 -3.34 -2.42 0.02 -1.32 -1.68 0.11
a5 -0.0858 -4.39 0.00 -0.178 -1.51 0.13 -0.0342 -1.44 0.16
a6 -369.00 -2.12 0.04 -1114 -4.19 0.00 -3370 -2.31 0.03
Rho-
square 0.248 0.482 0.153
The inclusion and exclusion of the variables is dependent on their significance test. If the parameter
of a variable is giving very low significance test results, they are excluded from utility equation and
they are represented by yellow background in the table
8. CONCLUSIONS:
1. K.K.Nagar to CBS via simconagar is a feasible corridor for BRTS.
2. Majority of the people in sample belongs to Middle Income groups.
3. Motorcycles have highest share of modal split indicates more people attracted to this
mode.
4. Public transport is predominant mode used by students.
5. Bus and motorcycle has higher avg. trip length compared to other modes.
6. Majority of people are willing to shift from 2Wheelers to BRTS.
7. In terms of occupation, the positive coefficient value indicates that workers are more likely to
use the motorcycle than the students and it is expected to have shifts to the BRT from the
students side.
8. Higher income groups are more likely to use own vehicles as suggested by the positive
coefficient and thus less likely to shift towards BRTS. In contrast to trend model predicted
negatively for car.
9. REFERENCES:
1. Geetam Tiwari and Deepty Jain (2012), Accessibility and safety indicators for all road
users: case study Delhi BRT, Journal of Transport Geography Vol-22, pp. 87–95
2. M.Shafiq-Ur Rahmana, Paul Timms and Francis Montgomery (2012), Integrating BRT
Systems with Rickshaws in Developing Cities to Promote Energy Efficient Travel,
Journal of Social and Behavioural Sciences, pp. 261-274
3. CRRI (2012), Evaluating Bus Rapid Transit (BRT) Corridor Performance from
Ambedkar Nagar to Mool Chand, Delhi
4. Tuhin Subhra Maparu and Debapratim Pandit (2010), A Methodology for Selection of
Bus Rapid Transit Corridors: A Case Study of Kolkata, Institute of town planners journal
5. Hubbli-Dharwad Municipal Corporation (2013), Detailed Project Report of Hubbli-
Dharwad BRTS
6. Vimal Gahlot and B.L.Swami (2012), User oriented planning of bus rapid transit corridor
in GIS environment, International Journal of Sustainable Transportation, pp. 102-109
7. Nivesh Chaudary (2007), Modal Shift analysis of BRTS, Jaipur, Journal of the
Transportation Research Board
8. Debrapratim Pandita and Shreya Das (2013), A Framework for Determining Commuter
Preference along a Proposed Bus Rapid Transit Corridor, Journal of Social and
Behavioral Sciences, pp. 894-903
9. Suxia Liu and Xuan Zhu (2003), An Integrated GIS Tool for Accessibility Analysis in
Urban Bus Transport Planning, Environment and Planning B: Planning and Design, pp.
105-124.