Planning and operations of multi-modal public transport systems€¦ · Planning and operations of...

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DelftUniversity ofTechnology

Oded Cats PTV WGM SAB, 10-01-2017

Planning and operations of multi-modal public transport systems

Oded Cats/ o.cats@tudelft.nl; cats@kth.se

2Oded Cats PTV WGM SAB, 10-01-2017

Bio background

• Dual PhD in Transportation Sciences, 2012

• Royal Institute of Technology KTH, Stockholm and Technion - Israel

Institute of Technology

• Transport Engineering, Operations Research, Business Management

• 35 Journal publications and 45 conference proceedings

• Transit assignment and simulation models

• Real-time information and control

• Travel behaviour, route choice

• Network robustness, disruption management

• Leading national and European projects on public transport

planning and operations

3Oded Cats PTV WGM SAB, 10-01-2017

Integrated modelling and simulation

of transport system dynamics

Traffic Dynamics & Transit Operations

Dynamic Loading

Automated Data Collection

Real-Time Prediction

Control Centre

Traveler Decisions

Network

Traveller Population

Fleet

Short-term

Mid/Long-term

Assignment

SystemPerformance

Traveler Perception

Service Planning

Traveller Strategy

Choice modelling

Traffic flow

Traffic prediction

Control theory

Market economics

Optimization

Travel behavior

Network modelling

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Strategic

Tactical

Operational

Evaluating network alternativesNetwork robustness analysis

Reliability of timetable designTransfer synchronization

Real-time control strategiesDisruption management

Range of model applications

• Available with networks on: https://odedcats.weblog.tudelft.nl/busmezzo/

5Oded Cats PTV WGM SAB, 10-01-2017

Congestion

Focus a

reas

Reliability and

Control

Real-time

Information

Network

Resilience

6Oded Cats PTV WGM SAB, 10-01-2017

Congestion

or when VOC=0.8 is not good enough

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How can the value of reduced

congestion be quantified?

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Evaluation of congestion effects

On-board crowding

Denied boarding

Reduced service relaibility

Increased preceived in-vehicle time

Increased waiting time

Increased total travel time

Cats, West and Eliasson (2016). A dynamic stochastic model for evaluating congestion and crowding effects in transit systems.Transportation Research Part B 89, 43-57.

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Appraisal of Increased Capacity

• Crowding factor in static/dynamic model: +3%/+120%

• Value of increased capacity: underestimated in static models

10Oded Cats PTV WGM SAB, 10-01-2017

Modelling congestion in public

transport networks

1

Cats and Hartl (2016). Modelling public transport on-board congestion: Comparing schedule-based and agent-based assignment approaches and their implications. Journal of Advanced Transportation 50 (6), 1209-1224.

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Reliability

or when the average headway is hardly experienced

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A series of field experiments

RETT2

• Experiment – L1

• Focus on regularity, decentalization

RETT3

• Experiment – L1; L3

• Clean-operations, control center actions

• Led to its incorporation in the tendering process

RETT4

• Experiment – L4

• Additional measures – boarding, priority

• Support full-scale implementation

Cats et al. (2012). Holding control strategies: A simulation-based evaluation and guidelines for implementation. Transportation Research Record, 2274, 100-108.

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Results

Fadaei and Cats (2016). Evaluating the impacts and benefits of public transport design and operational measures. Transport Policy, 48, 105-116.

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Information provision

or when passengers do not have perfect knowledge

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Service and Information Reliability

2 4 6 8 10 12 14 16 18 20 22 240

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

day

credibility coefficients - disaggregate analysis

alphaRTI

alphaEXP

alphaPK

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

alphaRTI

fre

qu

en

cy

end of the learning period

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

alphaEXP

fre

qu

en

cy

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

alphaPK

fre

qu

en

cy

Final distribution of credibility coeff. Example: evolution of credbility coeff.

Cats O. and Jenelius E. (2014). Dynamic vulnerability analysis of public transport networks: Mitigation effects of real-time information. Networks and Spatial Economics, 14, 435-463. Cats and Gkioulou (2015). Modelling the impacts of public transport reliability and travel information on passengers’ waiting time uncertainty. EURO Journal of Transportation and Logistics.

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Network vulnerability

or when passengers can not execute their pre-trip plan

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Capturing disruption dynamics

• Static model: underestimation of disruption effects

• En-route decisions, imperfect information

• Both passengers and operators can respond to disruptions

• Graph representation (infra vs. service, multimodality, time-dependency)

• Flow (re-)distribution model (route choice)• Modelling disruptions (capacity, frequency)• Identifying critical links (network indicators)• Modelling adaptation strategies (ex-ante, ex-post)• Measuring the impact (connectivity, robustness)

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Cats O. (2016). The robustness value of public transport development plans. Journal of Transport Geography, 51, 236-246.

Jenelius and Cats (2015). The value of new public transport links for network robustness and redundancy. Transportmetrica A, 11 (9), 819-835.Cats and Jenelius (2015). Planning for the unexpected: The value of reserve capacity for public transport network robustness. Transportation Research Part A 81, 47-61.

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On-going activities

• Real-time control beyond a single line (optimization, simulation)

• Smartcard data analytics (route choice, performance)

• Short-term predictions (travel times, flows)

• Disruption and robustness (criticality, planned works)

• Mitigation measures (from strategic to real-time)

• Demand responsive transit (routing and operations, perceptions)

• PT + bike (usage, determinants)

• Door-to-door mode and route choice models (reliability, crowding)

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Research directions

• Shared mobility

• Demand responsive transport

• Mobility as a Service (MaaS)

• Proactive supply management

• Real-time fleet management strategies

• Anticipatory control

• Disruption management

• Mitigation measures

• Network resilience

• Impacts of information

• Adaptation and learning

• Anticipatory information

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o.cats@tudelft.nl

odedcats.weblog.tudelft.nl