Public Transport Development Strategies forEmerging Metropolis- A Case of NOIDA

- RAMYA SITHARA.G Dr. SANJAY GUPTASchool of Planning and Architecture, New Delhi

Christchurch tramway routesSydney transit routesCopenhagen transit routes

Contents

Importance of Public Transport in urban areas.

Methodological Approach

Performance Evaluation indicators for Public Transport

Case Study area Profile and Data base

Public Transport travel pattern and demand assessment

Alternative scenarios of PT network Development

Salient Research Findings

IMPORTANCE OF PUBLIC TRANSPORT

Mobility is a major concern in urban

areas.

Attention to PT in JnNURM (2006) &

NUTP.

Land use activities change rapidly which

will have a direct impact on change in

travel characteristics.

Private vehicles are growing rapidly to

cater the increase travel needs, resulting

increase congestion levels in the cities.

PT share increase not in line with the

growing population.

Need for transit network to decongest

the roads and increase the connectivity

in cities

0

200

400

1-5Lakh

5-10Lakh

10-20Lakh

20-40Lakh

>40Lakh

372

43 34 10 9No.

of C

ities

Population Size

Distribution of Indian citiesaccording to population

Increase in city size is having direct impact on the PT

share.

RESEARCH NEED

Configuration of a transit network greatly influenced by

configuration of city’s roadway networks.

Current practice of network planning is normative and

policy based in nature.

No significant scientific effort in evolving an optimal &

rational Public Transport network strategy.

Very little research reported in the efficiency of alternate

Public Transport network forms on overall performance in

Indian Cities.

AHD City network

Boston transit network

Istanbul transit network

AIM & OBJECTIVES OF THE STUDY

AIM: To evolve and evaluate alternate public transport network development strategies

for emerging metropolitan cities

1. To appreciate various Public Transport network forms/structures and their impact on

PT efficiency.

2. To review global best practices on evolving efficient PT networks for various urban

structures.

3. To assess mobility characteristics in case city and identify issues related to Public

Transport systems.

4. To evolve and evaluate alternate Public Transport network forms for the case city and

assess its likely impact on Public Transport performance.

5. To recommend policy guidelines for Public Transport network development strategies

for case study area

APPROACH METHODOLOGYSt

age

-1St

age

-2St

age

-3St

age

-4

PUBLIC TRANSPORT PERFORMANCE EVALUATION INDICATORS

Financial• Operating Ratio• Earnings/Km• Earnings/Seat km• Earnings/Buses• Earnings/Pax. km• Bus Staff Ratio• Dead Mileage

Performance measures for PhysicalPlanning• PT Network Density• Service Coverage• Network Density• Walking Distances ( Accessibility)• Terminal Location• Bus Supply Index (% of Fleet as per

Urban Bus Specification)• No. of Interchanges

At route level• Route network Density• Route Overlapping• Avg. Bus stop spacing• Operating Speeds on route network

Operational• % Fleet Utilization• Vehicle Utilization• Load Factor• Average Distance Travelled/

Passenger• Breakdown rate• Vehicle Efficiency

PUBLIC TRANSPORT SUPPLY LEVELS – GLOBAL AND INDIAN SCENE

Popn. range

PT Network (KM) Availabilityper 1 lac Population % of Bus Share Bus Supply Index/ 1 Lac

PopnIndian

Scenario Global Scenario IndianScenario

GlobalScenario

IndianScenario

GlobalScenario

20 - 40 lakh 7.16 34.62 22% 38% NA 92

40 -60 lakh 11.23 26.42 16% 35% 17.3 79

y = 0.0003x - 0.8019R² = 0.7797

0.00

0.50

1.00

1.50

2.00

2.50

0 2000 4000 6000 8000 10000

PT d

ensi

ty

Popn density

Popn density and PT density Pop. Densitypersons/sq.km

PT density (KM/Sq.KM)UK

(Optimistic)India

(PessimisticAdopted

(Realistic)<750 0.3 - 0.3

750-1500 0.6 - 0.61500-2300 1.0 - 1.02300-3000 1.25 0.10 0.73000-3900 1.65 0.37 1.03900-4600 2.0 0.58 1.1

>4600 2.5 0.85 1.7

PT density (Km/ Sq.Km) = PT network length (Km)/ City area (Sq.Km)

It defines Pt network (Km) per Sq.Km area

ATTRIBUTES OF VARIOUS PUBLIC TRANSPORT NETWORK FORMS

Bengaluru

Grid Iron Network

(+) Minimum Transfers(+) Adds Vitality to CBD(+)Exploits Potential for aDense(+) DevelopmentCorridors(-) Potential congestionin core(-) Uneven coverage(-) Peripheral areas arenot served

Radial Network

(+) Connectivity withoutpassing through CBD.(+) Uniform Coverage.(+) Easy to understandfor user.(-) Min. one transferrequired(-) High frequencyrequired(-) Increased waitingtimes

Hub & Spoke

Chandigarh

Hyderabad

(+) Reduction in waitingtime.(+) Pulse concept can beapply.(+) Enhance the PT shareby not increasing thefleet size.(-) Increase in no oftransfers .(-) coordination betweenvarious transportsystems

CASE STUDY PROFILE OF NOIDA

• Presently an industrial and residential suburb of Delhi will grow into

a metropolis by 2021

• Part of evolving conurbation extending from Delhi to Faridabad,

Greater NOIDA, Bulandshahr, Meerut and Ghaziabad

• Major Transport nodes are Atta Market, Great India Place, Sec-15,

Sec-16, Sec-62.

02468

1012141618

FY1981

FY1991

FY2001

FY2011

FY2015

FY2021

FY2025

Popu

latio

n

Year

Population( In Lakhs) City Profile

Population 8.24 lakhs

Area 203 sq.km

PopulationDensity

3152persons/sq

.km

Workforce 35%

NOIDA Master plan - 2021

Existing PT Network inNOIDA

LAND USE AND SPATIAL GROWTH PATTERNS OF NOIDA

• Direction of growth in the

east and south side of the

city.

• As the eastern side of the

area is almost had an

compact development.

LANDUSE-1991 LANDUSE-2010 LANDUSE-2013 PROPOSEDLANDUSE-2031

Land use type 1995 2001 2011 2021Residential 42.15 36.21 41.12 43.71Commercial 4.92 0.83 3.68 3.82Industrial 30.23 24.28 22.6 16.30Institutional 5.67 12.22 8.96 8.61Transport 13.6 22.45 15.04 17.42Recreational/ Public space 3.43 4.01 8.64 10.14Total 100.0 100.0 100.0 100.0Total area (Sq.Km) 46.80 79.20 92.30

TRANSPORT PROFILE OF NOIDA

City Transport Profile

Road Network Length 250 km

Road network Density 1.23 km/sq.km

PCTR 0.90

PT Share (in %) 23%

Average Trip Length 5 km

Metro length 10 Km (approx.)

No. of Metro stations 4

Bus Transport Profile

No of Routes 16

Operators DTC & UPSRTC

Fleet Size 279

No of bus trips 733

Maximum route length 16.1 Km

Minimum route length 3.7 KM

Car

2W

IPT

Bus

Others

Mode Share

Work69%

Education8%

Others23%

Trip Purpose

Inference:• The share of personalized modes is double that of bus transport which is very alarming.

0

25

50

75

100

125

< 1 km 1-3 km 3-5 km 5-10 km >10 km

% o

f trip

s

Distance( In Km)

Cumulative TLFD (in distance)

DATA BASE & DEMAND ESTIMATION METHODOLOGY

On Board User Survey Boarding & Alighting Survey

Sample OD Matrix

Expanded OD per route perBus Trip

OD Matrix of each Route/Day No. of Bus Trips

Route wiseFrequency

Secondary Data

Combined PT OD Matrix

Zonal PT Demand

Type ofSurvey

No ofRoutes

Samplecovered

OD survey 16 370

Boarding /Alighting 16 All bus stops

ZONING CRITERIA

PT Demand Estimation

• Based upon the availability of PT network.

• The sectors which have PT network are made smallerzones & the one which do not have are made largerzones

• No of routes.• Each route

headway inpeak & offpeak.

• Fleet size ineach route.

ASSESSMENT OF ROUTE WISE PUBLIC TRANSPORT DEMAND

S.No RouteNo Origin Destination

TotalRouteLength( in Km)

LengthThrough

Noida( in Km)

% Routein Noida

No. of BusStops

Covered

Avg, StopSpacing( In Km)

Boarding(Sample)

Alighting( Sample)

DailyBoarding

(Estimated)

DailyAlighting

Estimated)

Daily PTDemand

Estimated)Avg.Freq.

1 332 Sec-32KashmereGate ISBT 20 3.7 19% 5 0.74 47 28 15598 9292 24890

26

2 33 Sec-37 Bhajanpura 24 3.8 16% 6 0.63 43 22 12028 6154 18182 19

3 34 Mehrauli Noida sec 32 50 44 1659 1460 3120 3

4 398MayurVihar-II Dhaula Kuan 28 5.8 21% 12 0.48 32 14 8344 3651 11995

12

5 491 Phase-II Nehru Place 28 7.7 28% 8 0.96 33 33 11108 11108 22216 23

6 355 Sec-32 Anand Parbat 27 8.3 31% 9 0.92 18 18 2816 2816 56326

7 8Sec-37 Ph-

II Badarpur 18 8.65 48% 11 0.79 52 33 12820 8136 2095522

8 319 Sector-32 Shahadara 21 9.47 45% 10 0.95 20 14 5215 3651 8866 9

9 300 Sec-34KendriyaTerminal 24 9.7 40% 12 0.81 35 27 5476 4224 9700

10

10 346 Sec-34Shivaji

Stadium 19 9.7 51% 9 1.08 17 31 2499 4556 70557

11 493Mayur

Vihar-III Nehru Place 18 10.2 57% 17 0.60 27 26 7040 6780 1382014

12 492 Sec-62 Nehru Place 28 10.6 38% 21 0.50 47 38 8690 7026 15716 16

13 347 Sec-34KashmereGate ISBT 25 10.77 43% 15 0.72 49 73 16262 24227 40488

42

14 443 Shahadara Badarpur 26 10.85 42% 10 1.09 23 19 3380 2792 61736

15 363 Sec-82 ISBT 27 12.9 48% 15 0.86 39 30 6287 4836 11122 11

16 323 Sec-34 Dhaula Kuan 38 16.11 42% 13 1.24 41 28 6803 4646 11450 12

25 9 12 1 573 478 126025 105355 231380 15

• Total PT demand is 2.31lacs which is 23% of the total trips of Noida.

PUBLIC TRANSPORT USER TRAVEL CHARACTERSTICS

I-E( 17.5%)E-I ( 17.5%)

E-E (2.5%)

I-I (62.5%)• Average bus frequency-15Mins, Minimum bus

frequency -3Mins, Maximum frequency - 42Mins.

ASSESSMENT OF ACCESSIBILITY BASED PUBLIC TRANSPORT DEMAND

y = 10529x + 230.27R² = 0.6316

0

5000

10000

15000

20000

25000

30000

35000

0.00 0.50 1.00 1.50 2.00 2.50

PT R

ider

ship

Accessibility Index

Accessibility Index vs PT Ridership

Key Findings:• A good relation is observed between

accessibility index and PT ridership.

Accessibility Index = ∑Ni-j/Aj

Ni-j = Off Peak Frequency of route “I” passingthrough zone “j”.Ai = Area of that particular Zone.

Zone wise Accessibility map of NOIDA

Accessibility Index

FORECASTING OF PLANNING AND TRAVEL PARAMETERS

Existing Forecast Based on CAGR Method

Details 2001(Master Plan)

2005RITES

2014UMTC 2015 CAGR

(2001 - 2015) 2020 2025

PT Trips

Population (in Lac) 3.05 4.01 7.74 8.24 7.4% 11.27 15.42

PT Trips (in Lac) 0.60 1.3 2.23 2.31 10.1% 3.48 5.25PCTR (Exl. Walk) 0.86 0.86 0.90 0.90 0.3% 0.91 0.93Total Trips (Exl.

Walk) 2.63 3.46 6.97 7.41 7.7% 10.26 14.21

PT share (Exl.Walk) 23% 38% 32% 31% 2.3% 34% 37%

• CAGR Method used as the previous years’ data was available

• A rapid growth of Population observed from 1991 to 2001 which is an unexpected growth

• Travel characteristic data is available from 2001.

• Hence, 2001 to 2015 is considered.

• Total Trips are having a highest CAGR in comparison to PT trips as it is observed that there are

more dependency on personal vehicles when compared to Public vehicles

SCENARIO 1: BUSINESS AS USUAL

Assumptions:• Network Length- 97.5 km• Accessibility Index- Same as Base Year(2015)• Zone wise PT Demand- Base Year Distribution has been

adopted• Bus Network Speed- 18 km/hr.• Frequency of routes passing parallel to Proposed

Metro- 2 ( Base Year Frequency)

Outcome:• Population coverage – 38%.• Public transport share– 24.6%.• In vehicle time – 71mins• Waiting time/ pax. – 10mins.• Average trip length – 18.8 Kms

Concept:• Developments and improvement plans are not

considered.

Methodology

SCENARIO 2: INCREMENTAL INCREASE IN BUS NETWORK LENGTH

Key Assumptions:• Zone wise population distributed based on the

proposed master plan for the Horizon year• Population density increased in zones which have

low PPHa and have proposed development• Growth of core area population considered low• Required PT network density estimated based upon

the future population density as per PT networkdensity vs population density relation

• Zone wise PT ridership estimated based on theaccessibility model

Description Details

Existing PT N/W Density (In Km) 97.5

Desired PT Network Density(KM/Sq.KM) 1.0

Required in length (in Km) 200Gap in Network (in KM) 112.52025 Population (in lacs.) 15.24

Scenario 2 PT Network

Concept:• PT demand is estimated based on the PT Accessibility

Index Model and spatial growth patterns.

Outcome:• Population coverage – 76%.• Public transport share– 39.7%.• In vehicle time – 51mins• Waiting time/ pax. – 8mins.• Average trip length – 16 Kms

Methodology

Scenario 3 PT Network

SCENARIO 3: RESTRUCTURING OF ROUTES WITH HUB N SPOKE CONCEPT

Key Assumptions:• Population density increased in zones which have low

PPHa and have proposed development• Growth of core area population considered low• Required PT network density estimated based upon the

future population density as per PT network density vspopulation density relation

• Zone wise PT ridership estimated based on theaccessibility model

Concept:• PT network developed based on the direction oriented

demand to increase the share PT trips• Provision of High frequency services along the spoke and

routes parallel to metro will have lower frequency.

SCENARIO 3: RESTRUCTURING OF ROUTES WITH HUB N SPOKE CONCEPT

Parameters Details

Feeder route length (KM) 132

Trunk Route Length (KM) 68

Trunk Route 38

Feeder Route 12

Max Transfers 1

Major PT demand interchange areas

Population projected

PT demand

Major demandareas

Existing land use& proposed land

use activities

Interchangebetween varioustransport system

Based on accessibility index model

Location of Hub’s and Spokes

Restructuring of routes and new routesdevelopment

Outcome:• Population coverage – 82%.• Public transport share – 41%• In vehicle time – 44mins• Waiting time/ pax. – 6 mins.• Average trip length – 21 Kms for stand. Bus

& 12 Km for Minibus

EVALUATION OF SCENARIO

Summary S.No Parameter Sc-1(BAU WithMetro)2025

Sc-2 (IncrementalExpansion)2025

Sc-3 (Hub &Spoke)2025

Standard Bus Mini Bus

GEN

ERAL

1 PT Network Density(Km/Sq.Km) 0.4 1 1

2 PT Network Length(In km) 98 203 203

3 Population Covered 38% 76% 82%4 Total PT Trips( in Lakhs) 3.57 5.65 5.845 Bus Supply( Fleet Size) 521 950 200 8006 Total Bus Trips 3126 3800 800 70887 Avg Route Length ( km.) 25 27 28 148 Avg Trip Length (km) 18.8 16 21 12

USE

R 9 Vehicle Utilization(Km/Bus) 240 270 238

10 In vehicle time ( Mins.) 70 51 4411 Avg. Waiting Time/Pax. 10 mins 8 mins 6 Mins

OPE

RATO

R

12 Passenger Km Travelled(PKT) (in Lakhs) 71 87 96

13 Total Earnings/Day(In Lakhs) 53.4 65.3 71.9

14 Fleet Procurement Cost(In Lakhs) 14588 18788 7388

15 Operating Cost/ day(In Lakhs) 23.4 34.2 26.6

CONCLUSIONS AND RECOMMENDATIONS

Conclusion There is a strong relationship is observed between the accessibility index and

ridership. Hub and spoke concept is more feasible network approach to enhance the

Public Transport coverage in cities form like NOIDA. The approach developed in this study is useful to in assessing inequities in

Public Transport accessibility index in urban areas and aids in evolving PTnetwork strategies.

Recommendations Need for a scientific approach to enhance the Public Transport usage in

Indian cities as it is having rapid growth in cities Public transport network approach should be rationale rather than

conventional approach, so there is a need for integrated land use and publictransport network forms.

Further study• Similar Studies need to be conducted in different size of cities and application

of various network forms have to be tested.

“An advanced city is not a place where the poor move about incars, rather it’s where even the rich use public transportation”