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Activity Number:
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220
- Contributed Poster Presentations: Transportation Statistics Interest Group
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Transportation Statistics Interest Group
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Abstract #313410
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Title:
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A Random Effects Model to Capture Seasonal and Zonal Effects on Road Traffic Collisions
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Author(s):
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Nicola Hewett* and Lee Fawcett and Joe Matthews and Neil Thorpe and Karsten Kremer
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Companies:
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Newcastle University and Newcastle University and Newcastle University and Newcastle University and PTV Group
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Keywords:
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Road safety;
Transport;
Hierarchical Modeling;
Random Effects;
Spatiotemporal Model
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Abstract:
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Improving road safety is hugely important with the number of deaths on the world’s roads remaining unacceptably high; an estimated 1.35 million people die each year (WHO, 2018). This paper investigates the dependencies of road traffic collisions on season and zone location. The random effects model introduced uses a Bayesian hierarchical formulation to capture the seasonal and site effects separately to allow for prediction of the potential number of collisions per month for each zone through inference using Metropolis-within-Gibbs sampling. The study analyses road traffic accident rate data over zones in North Florida (accident rates per month per zone). The results show a clear seasonal effect and slight zonal effect across longitude/latitude on the number of collisions. We also include a comparison to a fixed effects model showing the increased precision of parameter estimates with their posterior standard deviations reducing by approximately a third.
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Authors who are presenting talks have a * after their name.
