multimodal activity modelling for … · dr patrizia franco. transport systems catapult. ... •...
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MULTIMODAL ACTIVITY MODELLING FOR MOBILITY AS A SERVICE
Midlands Intelligent Mobility ConferenceDr Patrizia Franco
Transport Systems Catapult
Nottingham24th January 2018
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Tailored around your needs
Flexible Efficient
User Friendly Seamless
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THE MOBILITY ON DEMAND LABORATORY ENVIRONMENT (MODLE)
Consumers access the service online via the web, an app or SMS text
Demand Prediction
MODLE platform
• aggregates demand• calculates itineraries• informs passengers and
vehicles• Informed by an Activity
Based Model
OperatorsDeliver services
Funder
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• E-hailing minibus service to improve mobility services in an area currently disconnected by public transport and strongly relying on private cars
• The service extends PT services penetration rather than competing and consider social inclusion, providing services to hospital and low income areas
THE MOBILITY ON DEMAND LABORATORY ENVIRONMENT (MODLE)
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Synthetic population• The MODLE case study includes five
areas (2 industrial park Severnsideand Avonmouth, Frenchay –University West of England Campus – Glenside with the busiest Park and Ride Rail station in UK, and Staple hill)
• The area of interest includes the Greater Bristol to account for commuting habits
ACTIVITY BASED MODEL FOR GREATER BRISTOL
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• Agent based model built using the open platform MatSim. • Demand for the model is coming from a synthetic population
built using anonymised and aggregated Mobile Phone Network Data
• Multimodal public transport network built with publicly available data
ACTIVITY BASED MODEL FOR GREATER BRISTOL
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• OD matrices built using anonymised and aggregated Mobile Phone Network data (MND)Segmentation by:– Mode (by rail and road trips)– Purpose– Start zone, end zone– Time period (AM; 3 Inter-peaks;
PM and off-peak)– Trip Chain Data set: Aggregated journeys with intermediate legs per time
period– Distribution of departure times from each area zone from the area of interest
• Demographics to define static agents behaviour• Multimodal Public Transport (bus and rail)• Facilities from OpenStreet map
Activity Based Model for Greater Bristol
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• Identify Catchment area for on demand flexible and responsive shared service• Identify demand coming from fixed scheduled public transport services (Bus and
rail) for a first mile and last mile service, delivered in partnership with bus operators
ACTIVITY BASED MODEL FOR GREATER BRISTOL
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CONCLUSIONS AND FURTHER WORK
• Activity Based models are flexible tools to model and visualize demand for flexible mobility services (fixed scheduled transport services vs. dynamic agents);
• Newly available big data source, such as MND, are an ideal solution to build a synthetic population for newly developed areas;
• MND can be available at different granularity than classic OD matrices: Static agents maintain the trip chain journeys;
• The simulation identifies pockets of demand for a flexible demand responsive service and a first/last mile service for the fixed schedule public transport, which extend PT provision and patronage (two level of definition: LSOA and MSOA)
• Further work will include data feed from the service to evaluate the performance• Calibration of the model will be improved based on the
revealed preference survey run by UWE
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Dr Patrizia FrancoSenior TechnologistTransport Systems [email protected]