Review of Data Maintenance Practices of SRTUs

Prof. Geetam Tiwari

MoUD Chair Professor,

Transportation Research and Injury Prevention Program (TRIPP),

Civil Engg. Department, IIT Delhi.

Ms. Himan Jain,

Senior Project Scientist, TRIPP, IIT Delhi.

&

Structure

1. BUS POLICIES and SRTC - CTU

2. BUS MARKET

3. FLEET REQUIREMENT

4. DATA MANAGEMENT PRACTICES

5. FINDINGS and SUGGESTED KPIs

Public Transport Demand

PT policies and strategies must balance conflicting goals

Data is needed to generate decision supporting analytics

Pool of data generated by ITS - yet facing Declining Ridership and Increasing Losses.

System must be observed through multiple perspectives i.e.

• User,

• Operator,

• Societal (community as a whole)

• Regulatory bodies (authority)

Policy Evolution Major policies which aimed to guide the bus specifications-

• Bus design code (AIS: 052), for bus building (1989)

• Low floor buses in Delhi by DTC (Delhi Transport Corporation) vide global bid no DCGM -(MS -1)C&BP/820/2006.

• Bus Code Publishing (2008)

• MoUD Specs JnNURM-I (2009) UBS 1

• MoUD Specs JnNURM-II (2013) UBS 2

• Body Builder Accreditation (Apr 2013),

• Bus Code Notification (Apr 2014)

State / City Road transport Corporations 73 SRTUs owned and regulated by respective state governments

Multiple SRTUs in one state, increasing since 1999

SRTUs own 28.7% bus fleet, but growing very slowly

Accountable for funds from central and state governments

Maintain their performance data in terms of - • Capital investment

• Revenue

• Bus services

• Maintenance

Organized city bus systems:

Bus Market

2006 – 26 states and only 20 cities 2014 - available in 31 states and 177 cities

Low Floor vs. Standard Buses

Bus type distribution during CBF scheme –I (2009-10) Bus type distribution during CBF scheme – II (2013-14)

Need for Research • Art and science of Chassis Design had been

matured by all Indian OEMs

• Body design has long not been accorded high priority

• Bus Design Code (AIS: 052) (1989), adopted for bus building

• UBS-2 (2013) not adopted in spirit by states and OEMs

The bus sector did not go under transformation as expected by Ministry

.

0-5 years, 510,000, 38%

5-10 years, 533,000, 40%

over 10 years, 302,000, 22%

Distribution of the bus sector fleet by the age

0-5 years 5-10 years over 10 years

Fleet Required

S.

No

Population

category

No of

Districts in

this

category

Buses

Required

(maximum)

Buses

Required

(minimum

)

1 100,000-500,000 259 29034 23369

2 5000,000-1000,000 109 63795 51497

3 1000,000-2000,000 73 49641 36196

4 2000,000-5000,000 44 131505 97410

5 ABOVE 5000,000 6 91661 73972

Total Buses Required 365636 282444

• 2011 – 2.82 – 3.65 lakh buses required

• 2017 – 3.32 – 4.0 lakh buses required (current latent demand)

• 2021 – 3.6 – 4.3 lakh buses (as estimated on population projections by Census 2011 )

Average Fleet Required Fleet requirement per lakh population, as estimated from the sample districts using the fleet estimation toolkit (headway less than 20 minutes).

*districts in this category are smaller, dense with Urban agglomeration areas, and other large town or cities *Study assumed that buses are run within districts and not as Cluster or as Mofussil services beyond

Population category Avg fleet size–

Minimum

shift scenario

Avg fleet size–

Maximum shift

scenario

Avg fleet size determined from sample

100,000-500,000 33 41 12 to 22 seater

500,000-1000,000 67 83 12 to 44 seater

1000,000-2000,000 26 * 57 * 44 to 60 seater *

2,000,000-5,000,000 80 108 44 seater

Above 5000,000 184 228 44 to 80 seater

Appropriate Bus The impact of following on bus type choice –

• Size

• Power train,

• AC and other premium features

• Fuel Economy

Different type of buses for inner city limits and periphery of the city (Mofussil operations and Intercity operations)

Comfort to Passenger • Indian Anthropometry

• Ergonomics for comfort

• Balancing needs of All – UNIVERSAL ACCESSIBILITY

• Optimize seating vs. standing

SRTU / CTU Operations Data

1. Review of local and international practices : performance data for 2009-14 of SRTUs

2. Comparison of the indicators: State Transport Undertakings Profile & Performance, published by CIRT, Pune

3. Patterns in data to develop generic framework : Performance of State Road Transport Undertakings (SRTUs), published by MoRTH, New Delhi

4. Comparing local practices vs. best practices (Annual Performance Reports: Singapore, Hong Kong, London and Few US Cities) to identify more /useful indicators

Gaps

• SRTUs have abundant raw data but lack variety of KPIs

• Dominance of Operator Perspective – Financial, Physical and Material

• Lack of Enforcement in Reporting Data

• Lack of Data Collection Technology (ITS)

• Lack of User Perception – level of service

• Lack of Community and Environment KPIs

DATA FORMATS

Data collection method • Manually – 82%

• Electronically – 18%

Data storage media • Logbooks (Registers)

• Spreadsheets (MS-Excel)

• ERP software (Tally ERP).

DATA STORAGE Key Performance

Indicators (KPIs)

MCTSL (Meerut) AMCTSL (Mathura)

Data Collection

(M/A)

Data Storage

(L/S/E)

Data Collection

(M/A)

Data Storage

(L/S/E)

M = Manually

A = Electronically

L = Logbooks

S = Spreadsheets

E = ERP Software

M = Manually

A = Electronically

L = Logbooks

S = Spreadsheets

E = ERP Software

Category I – Financial

Category II – Operations

Category III – Human Resources

Category IV – Maintenance

Total Manual = 82.9%

Electronic = 17.1%

Logbooks = 24.4%

Spreadsheets =

36.6%

ERP Software =

36.6%

Not stored=2.4%

Manual = 82.9%

Electronic = 17.1%

Logbooks = 19.5%

Spreadsheets =

41.5%

ERP Software =

36.6%

Not stored=2.4%

Mathura and Meerut Parameters Mathura Transit Region Meerut Transit Region

Area (sq.km) 3014.5 144.21

Population (2011) 1733346 1889507

Population density (pax/km2) 575 13102.47

Buses per 100,000 3.46 6.35

Fleet Size (since 2011) 60 120

Fleet Composition Mini Buses = 60 Mini Bus = 40

Low Floor Bus = 10

Standard Bus = 70

Estimated Fleet Size# 780 775

Estimated Buses per 100000 45 41

Network Size (km) 705 421

No. of Routes 12 18

Average Route Length (km) 49.45 (excluding 161 km circular route

of “Brajdarshan”)

58.75 (including 161km circular route

of “Brajdarshan”)

23.38

Range of Frequency (min) 30 – 180 7 – 180

Monthly Average Load Factor (%) 70 (March 2016) 69 (May 2016)

Service Density (km/km2) 0.26 2.92

Mathura and Meerut Section AMCTSL MCTSL

Administration The main administration of AMCTSL

covers city bus operations for two cities:

Agra and Mathura, exclusively.

Concerned with financial performance

The main administration team consists for 4

persons including MD who is the head of the

SPV: MCTSL and covers Meerut and Modinagar

(Dist. Ghaziabad).

Concerned with increasing service area of the

city

Operations

(differences)

The buses run in 12 routes covering

various villages and municipalities which

surround Mathura Municipality.

59 out of 60 buses are operational as one

is damaged beyond repair but is not

scrapped or replaced yet.

Fuel is provided by the SPV. Filling station

exists in Mathura Depot.

The buses run in 18 routes covering Meerut

Municipal Corporation and urban

agglomeration. One route also covers

Modinagar from neighbouring Ghaziabad

district.

110 out of 120 buses are targeted to be

operational and 10 as spare buses. It may vary

depending upon whether the bus is available

from the maintenance contractor or not.

Fuel is outsourced in Meerut. Filling stations

are private and they maintain records of fuel.

Public Transport Coverage URBAN OPERATIONS (Meerut city) MOFUSSIL OPERATIONS (Mathura city + Brij Circuit )

Key Points

• No significant difference in population of both the transit regions

• Population density in Meerut transit region is 22 times of Mathura

• Fleet in Meerut is just double the fleet size in Mathura

• Meerut transit region Network area is at least 40% smaller than that of Mathura.

Findings - 1

• Characteristically Mathura transit region is different from Meerut transit region.

• Thus, there is a need to understand new model of city bus system prevailing in small towns – CLUSTER OR MOFUSSIL OPERATIONS.

• Mathura have less than required fleet.

• The gap between current fleet size and required fleet size has to be addressed scientifically in terms of fleet type suitable for city bus systems in small towns.

Findings -2

36 SRTUs and 71 indicators (2009 – 2013) shows –

• None SRTUs report 100% indicators.

• BMTC (urban) has reported highest number of indicators (96%)

• KnSRTC , NEKnRTC and NWKnRTC (rural) maximum number

• SRTUs reporting more than 90% of the indicators (big SRTUs)

Organization structure and management may not be equipped enough to practice performance measurement.

These SRTUs are old and with the expansion in services, they have grown bigger in fleet size and manpower.

Findings -3

reliability

100% reported by SRTUs

Under-reported indicators

• Financial performance • Fleet and capacity utilization • Manpower productivity • Material performance

• Punctuality in departure and arrival of bus from and to the depot

• Number of public complaints • Measures of safety like

accidents, fatalities and injuries

Mostly from Operators perspective: measures subject to Audit, etc

Mostly from Users perspective: measures of Level Of Services - safety,

security, comfort and reliability

Urban vs. Rural SRTC

URBAN OPERATIONS MOFUSSIL OPERATIONS

RURAL OPERATIONS

User demand, average waiting time at bus stops, average speed of the public bus systems Infrastructure : Road density (km/km2) ; No. of stations per km2

Measure of Connectivity between parent city and peri-urban areas Connectivity to nearby Satellite towns, large villages, etc.

Measures of connectivity between two points, number of transfers, etc.

KPIs not used by SRTUs

• Annual ridership per bus station

• Operating cost per trip

• Operating cost per passenger km

• Revenue per passenger

• Operating cost per passenger

• Avg. fare per passenger km

• Passengers per capita

• Accidents per year

+ 7 more

• Air pollutants (tons per day)

• Compensation per accident

• Injuries per lakh passenger

• Ratio of ridership growth to population growth

+ 14 more

Please refer to the TRIPP report for further details and other explanation.

• Avg. Passenger km per Vehicle km

• Annual ridership per bus • Passenger trips per

effective vehicle km • Riders per effective km • Operating cost per

boarding • Avg. fare per boarding

+ 8 more

Easily re-estimated To be combined with other parameters

To be collected and estimated

Missing Perspective Environmental Parameters –

• Carbon foot print (Tonnes per passenger km) • Emissions (Tonnes per passenger km)

Community perception indicators - • Average daily PT trips per person etc.

Quantitative reliability Parameters – • Average passenger waiting time (min.) • Average transit speed (km/h)

Qualitative comfort and safety Parameters – • Crew behaviour • Ride Quality (cleanliness, sudden

acceleration/deceleration, etc.)

Key Characteristics of KPIs

Stakeholder acceptance

Linkage to community goals

Clarity, Reliability and credibility

Integration into agency decision-

making

(Source: TRB, 2003 - Transit Cooperative Research Program (TCRP) Report 88 ‘A Guidebook for Developing a Transit Performance-Measurement System’)

Proposed Indicators from Current Data

Category-I (System Utilization)

Describes relating two existing categories in local practices viz. Fleet Utilization and Capacity Utilization.

Category II (Operating Efficiency)

Tracks how well monetary resources are working in operational sides of the system. (Indicators are derived from financial and physical performance indicators together in ratios).

Category-III (Safety)

Is an important aspect which a user thinks before choosing a mode of transport.

Category-IV (Fare Level)

Is an important factor for different socio-economic groups of people to decide on PT.

Category III and IV in derived performance indicators are based on user perception of any PT system.

Thank You

Annexures

Example Category Key Indicator Description

Category I – System

Utilization

Avg. passenger-km per vehicle-km = 𝑇𝑜𝑡𝑎𝑙 𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟 𝐾𝑚𝑠. / 𝑇𝑜𝑡𝑎𝑙 𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝐾𝑚𝑠.

This indicator measures the average system loading, in other words, how well the operating capacity has been utilized. A higher value suggests better utilization.

Annual ridership per bus station = 𝑇𝑜𝑡𝑎𝑙 𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟𝑠 𝐶𝑎𝑟𝑟𝑖𝑒𝑑 / 𝑁𝑜.𝑜𝑓 𝑏𝑢𝑠 𝑠𝑡𝑎𝑡𝑖𝑜𝑛𝑠 𝑠𝑒𝑟𝑣𝑒𝑑

This indicator normalizes the ridership by the number of bus stations. A higher value suggests a better utilization of the system.

Annual ridership per bus = 𝑇𝑜𝑡𝑎𝑙 𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟𝑠 𝐶𝑎𝑟𝑟𝑖𝑒𝑑 / 𝑇𝑜𝑡𝑎𝑙 𝑛𝑜.𝑜𝑓 𝑏𝑢𝑠𝑒𝑠

This indicator normalizes bus ridership by bus fleet size, and reflects the asset utilization. A higher value means that on average, a bus carries more passengers and suggests better asset utilization.

Category I – System Utilization

SUGGESTIONS Category Key Indicator Description

Category-II (Operating Efficiency)

Operating cost per trip= 𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐶𝑜𝑠𝑡 / 𝑇𝑜𝑡𝑎𝑙 𝐴𝑐𝑡𝑢𝑎𝑙 𝑇𝑟𝑖𝑝𝑠 𝑂𝑝𝑒𝑟𝑎𝑡𝑒𝑑

This indicator measure average cost to run a scheduled trip from origin to destination. Lower value suggests better cost efficiency.

Passenger trips per effective vehicle km = 𝑇𝑜𝑡𝑎𝑙 𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟𝑠 𝐶𝑎𝑟𝑟𝑖𝑒𝑑 / 𝑇𝑜𝑡𝑎𝑙 𝐸𝑓𝑓. 𝐾𝑚𝑠.

This indicator measures average no. of passenger trips per bus per km. Higher the value, higher is the system efficiency and vice versa. However in SRTUs’ case, passenger trips are unlinked therefore total passengers carried is equal to total passenger trips.

Operating cost per passenger-km = 𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐶𝑜𝑠𝑡 / 𝑇𝑜𝑡𝑎𝑙 𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟 𝐾𝑚𝑠.

This indicator measures the cost required to deliver every kilometer a passenger travels. As operating cost is largely fixed (e.g. manpower cost, fuel cost) once the route and schedule are determined, a higher ridership and longer trip distance would lead to higher operational efficiency.

Category II – Operating Efficiency

KEY POINTS • The average route length in Mathura

transit region is 49.45km whereas it is less than half i.e. 23.38km in Meerut transit region.

• The current systems’ service density is 0.26km/km2 in Mathura, while it is 11 times higher in Meerut i.e. 2.92km/km2.

• Significant potential to increase services in Mathura transit region.

Proposed Indicators( Existing and New)

Please refer to the TRIPP report for further details and other explanation.