spatio-temporal modelling of network data james haworth department of civil, environmental and...

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Spatio-temporal modelling of network data James Haworth Department of Civil, Environmental and Geomatic Engineering [email protected]

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Page 1: Spatio-temporal modelling of network data James Haworth Department of Civil, Environmental and Geomatic Engineering j.haworth@ucl.ac.uk

Spatio-temporal modelling of network dataJames Haworth

Department of Civil, Environmental and Geomatic Engineering

[email protected]

Page 2: Spatio-temporal modelling of network data James Haworth Department of Civil, Environmental and Geomatic Engineering j.haworth@ucl.ac.uk

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What information do we need to forecast future travel times on Gower Street?

1. Temporal information2. Spatial information3. Other forms of adjacency

• Build adjacency from underlying network.

• Use distance based adjacency.

4. Other sources of information• Incident data?• SCOOT flow data• Social media data.

@traffic_update@londontraffic

Model Naïve Hist. Avg ARIMA STARIMA STANN KRRAvg. R2 0.34 0.19 0.43 0.40 0.42 0.64

RealKRR

Network adjacency based forecasting:• Network structure is

modelled in a spatial weight matrix.

• ONLY SPATIAL information is used in this example.

The Network is not complete:• Some events have

spatio-temporal effect, some don’t…

Generally good but:• Can’t predict

sudden changes.• Can’t deal well with

missing data

Page 3: Spatio-temporal modelling of network data James Haworth Department of Civil, Environmental and Geomatic Engineering j.haworth@ucl.ac.uk

Thank you for listening

James HaworthDepartment of Civil, Environmental and Geomatic

[email protected]