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Dr. Lauren GardnerAssociate Professor
Civil Engineering at Johns Hopkins University Co-Director, Center for Systems Science and Engineering
Member, Research Centre for Integrated Transport Innovation (rCITI) at UNSW SydneyVisiting Scientist, CSIRO (Australia)
Network Modeling of Transport Systems
Center for Systems Science and Engineering
Pricing for Transport Networks• Model Road Pricing Schemes
• Consider Uncertainty/Information• Compare Policy Options• Quantify System Performance
Planning for Alternative Vehicle Technologies• Integration of Power and Transport Systems
• User Behaviour• Sustainability Metrics• Policy Development• Multi-Objective Network Design
Mobility and Epidemiology• Role of Transportation in Disease Spread
• Quantification of Disease Spreading Risk• Predicting Outbreak Behaviour Patterns• Optimizing Intervention Strategies
Research Areas of Focus
Overview of Research Methods
Objective: Exploit available information to infer and predict local and global patterns of contagion, quantify the risk posed (e.g., by components of transport systems) in the spread of disease, and design optimal mitigation strategies
Methods:i. Mathematical modeling ii. Network theoryiii. Optimizationiv. Simulationv. Statistics
Contributions:i. Policy evaluation and decision supportii. Optimize resource allocation
Hypothesis: The movement of people, pathogens and vectors (e.g., mosquitos) plays an integral role in the risk of disease.
Case Geo-location Data Environmental, Land-use and Climate
Large-scale Data Requirements
Local Mobility Global Transport Networks
Social Media, Cell phone, Credit Card, Google, etc
Social-Contact Network Models
Can we use available spatiotemporal infection data (and other information) to better understand the risk posed by an outbreak?
Modeling Public Transit Contact PatternsLocal Mobility Patterns
“Flu on the Bus” ProblemDefine Contact Networks
High Risk Transit Trips
Bota, et al. (2017), Netw Spat Econ.
Apply network-based statistics, algorithms and simulation
Extract ridership data
Vehicle trip network• Nodes ← vehicle trips loads• Links ← transfer passenger volumes
Public Transit Network AnalysisContact network. Large circles represent vehicle-trips
Fig. Vehicle-trip network
Vehicle Trip Network:• 8002 nodes (vs 94,475)• 263,792 links (vs 6,287,847)
Planning for New Vehicles Technologies
Research Questions:1. How will infrastructure and planning decisions change due to the presence of new
vehicle technologies? e.g., Electricity Pricing, EV charging Station location, Transport System Design Objectives (safety, emissions, etc)
2. How does the behaviour of drivers change in the presence of these new technologies?
Research Applications:Integration - Convergence of transport/power systemsPlanning - Demand-Supply for electric power gridUser Behaviour – Range Anxiety, RoutingSustainability - Upstream emissionsPolicy Decisions - Charging Infrastructure Location Network Design Problem – Multiple objectives
Modeling Sustainable Transport Systems:
ELECTRIC VEHICLES
•improve battery storage•power train configuration
Transportation:
•encourage clean sources•reduce fossil fuel dependence
•standards•incentives
•affordability•business models•financing
•consumers•travellers•range anxiety•education
•network modelling•distance limitations•destination choices, route choice•infrastructure improvement Electric Power Systems:
Economic:
Policy:
Energy:
Technology:
Behavioural:
•Smart Grid•effective management•charging infrastructure•mobile storage devices
Modeling the System Impact of Travel Demand Variability on Emissions and Congestion
★ The expected performance of a system may not be correlated to the variability of the system
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Design Scenarios
Expected ΔTSTTExpected ΔTSEC_PEV
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Design Scenarios
ΔTSTT STDΔTSEC_PEV STD
These are the the same design scenario and so on
Modelling Spatiotemporal EV Uptake and Energy Consumption Rates
Relative likelihoods that households in each CCD
would purchase an electric vehicle.
AECOM Vehicle Sales Forecast for
Sydney GMA
Average daily distance driven by a vehicle owner
residing in each CCD.+ +