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Challenge the future
DelftUniversity ofTechnology
Oded Cats PTV WGM SAB, 10-01-2017
Planning and operations of multi-modal public transport systems
Oded Cats/ [email protected]; [email protected]
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
4Oded Cats PTV WGM SAB, 10-01-2017
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
7Oded Cats PTV WGM SAB, 10-01-2017
How can the value of reduced
congestion be quantified?
8Oded Cats PTV WGM SAB, 10-01-2017
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.
9Oded Cats PTV WGM SAB, 10-01-2017
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.
11Oded Cats PTV WGM SAB, 10-01-2017
Reliability
or when the average headway is hardly experienced
12Oded Cats PTV WGM SAB, 10-01-2017
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.
13Oded Cats PTV WGM SAB, 10-01-2017
Results
Fadaei and Cats (2016). Evaluating the impacts and benefits of public transport design and operational measures. Transport Policy, 48, 105-116.
14Oded Cats PTV WGM SAB, 10-01-2017
Information provision
or when passengers do not have perfect knowledge
15Oded Cats PTV WGM SAB, 10-01-2017
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.
16Oded Cats PTV WGM SAB, 10-01-2017
Network vulnerability
or when passengers can not execute their pre-trip plan
17Oded Cats PTV WGM SAB, 10-01-2017
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)
18Oded Cats PTV WGM SAB, 10-01-2017
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.
19Oded Cats PTV WGM SAB, 10-01-2017
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)
20Oded Cats PTV WGM SAB, 10-01-2017
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