Public Transport Pricing Strategies using an Agent-based Simulation Platform

(A Case study of Singapore and Lessons for Pakistan)

Speaker : Dr. Muhammad AdnanAssociate ProfessorDepartment of Urban and Infrastructure EngineeringNED University of Engineering and Technology, Karachi

National Conference on Sustainable Transport18-19 December 2015

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OutlineAgent-Based Models and Simulation SimMobilityPT Pricing StrategiesSingapore Case StudyLessons for Pakistan

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Agent-based Models and Simulation (1)

Agent-based models and simulation (ABMS) is a relatively new approach to modelling complex systems composed of interacting, autonomous ‘agents’.

ABMS is particularly applicable when agent adaptation and emergence are important considerations.

A combination of several synergistic factors is moving ABMS forward rapidly.◦ continuing development of specialized agent-based modelling methods

and toolkits◦ the widespread application of agent-based modelling◦ the mounting collective experience of the agent-based modelling

community◦ the recognition that behaviour is an important missing element in

existing models◦ the increasing availability of micro-data to support agent-based models◦ advances in computer performance

• Integrated platform

• Collaborative research laboratory

• Development and evaluation of mobility portfolios

SimMobility – Introduction (I)

What bundle of options best performs under an inherently uncertain future

SimMobility - Introduction (II)

SimMobility- Introduction (III)

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SimMobility-Introduction(IV)

Applications◦Road and PT pricing strategies ◦Innovative modes & services◦Crisis management◦Bus lane optimization◦Adaptive traffic control strategies

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Public Transport Pricing (I)Pricing policies in public transportation:

• Off-peak periods → price discounts (up to free).• [Peak periods → price markups].

Pricing policies can be:• Time-based (e.g. before 7:30AM on weekdays).• Location-based (e.g. outside CBD into CBD).• User-based (e.g. applicable to senior citizens).

Why are they used?• To influence a demand shift from peak to off-peak

periods, to improve the level of service, to attract commuters to more sustainable (public) travel modes etc.

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Singapore Case Study

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Singapore ExperienceFREE PRE-PEAK TRAVEL ON MRT

Source: Land Transport Authority

Source: Ministry of Transport

OFF-PEAK MONTHLY TRAVEL PASS

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Free Pre-Peak MRT Policy Free Pre-peak Travel on

Singapore MRT:• As of 24 June 2013, free trips

outside CBD into 16 (18) CBD stationsbefore 7:45AM and up to 50 cents discount 7:45AM – 8:00AM.

Implementation in SimMobility:

• Free trips from non-CBD zones to zones assigned to 16 CBD stations,with arrival before 8:00AM.

• Zones assigned to their centroid’s nearest stations.

OD flows from EZ-Link card data (August 2013)

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Peak Ridership into CBD

EZ-Link tap-outs at CBD MRT stations

7:30AM

beforeafter

8:30AM

beforeafter

The effects of the free pre-peak policy on peak ridership into CBD:• After policy: higher pre-peak ridership and lower peak

ridership.• EZ-Link card data: before (2011) and after (2013):

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Results/Policy Implementation Changes in KPIs:

• Peak ridership into CBD: ↓ -4.55%

• Average MRT trip fare: ↓ -1.92% (-2¢ )• Average MRT trip fare into CBD: ↓ -

15.27% (-20¢)

• Operator’s revenue: ↓ -0.96%

• Number of MRT trips: ↑ 0.99%• Number of MRT trips into CBD: ↑ 1.81%

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Results/Policy ImplementationMRT Mode Share for trips into CBD:

Increased MRT mode share in the free period is mostly due to a time shift rather than a mode change.

Trips into CBD Before Policy After Policy ChangeBefore 8:00AM 37.49% 42.33% +4.84%

Before 9:30AM 41.63% 42.81% +1.18%

Whole day 39.39% 39.72% +0.33%

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Lessons for Pakistan (I)Huge investments are being made in urban

mobility sector◦Mass Transit Projects◦ Intelligent Transport based Developments◦ Investments in Road Infrastructure

Urban Mobility-based policy decision needs to be analyzed in new and emerging modeling tools for better results◦Traditional forecasting models are being

outdated and not able to address complex nature of interactions involved in such situation

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Lessons for Pakistan (II)ABMS are now used in many

developed countries for innovative policy scenarios for their operational systems ◦(Lahore BRT can be a case in Pakistan i.e.

data availability) for investigating policies such as skip-stop operations, time-, location-people-based pricing policy multi-modal travel options in terms of

innovative access and egress modes, such as bike sharing and free access or egress ride.

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Thank You