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Publicação
Spatio-temporal modeling of traffic risk mapping on urban road networks
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Autores
Resumo(s)
Over the past few years, traffic collisions have been one of the serious
issues all over the world. Global status report on road safety, reveals
an increasing number of fatalities due to traffic accidents, especially on
urban roads. The present research work is conducted on five years of
accident data in an urban environment to explore and analyze spatial
and temporal variation in the incidence of road traffic accidents and
casualties.
The current study proposes a spatio-temporal model that can make
predictions regarding the number of road casualties likely on any given
road segments and can generate a risk map of the entire road network.
Bayesian methodology using Integrated Nested Laplace Approximation
(INLA) with Stochastic Partial Differential Equations (SPDE)
has been applied in the modeling process. The novelty of the proposed
model is to introduce "SPDE network triangulation" precisely on linear
networks to estimate the spatial autocorrelation of discrete events.
The result risk maps can provide geospatial baseline to identify safe
routes between source and destination points. The maps can also
have implications for accident prevention and multi-disciplinary road
safety measures through an enhanced understanding of the accident
patterns and factors. Reproducibility self-assessment : 3, 1, 1, 3,
2 (input data, preprocessing, methods, computational environment,
results).
Descrição
Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
Palavras-chave
Network triangulation Spatio-temporal modeling Traffic risk mapping