During the last decade, the concept of composite safety performance index (CSPI) has become a popular practice in the field of road safety, namely for the identification of worst performing areas or time slots also known as hotspots. The overall quality of a composite index depends upon the complexity of phenomena of interest as well as the relevance of the methodological approach used to aggregate the various indicators into a single composite index. However, current aggregation methods used to estimate CSPI suffer from various deficiencies at both the theoretical and operational level; these include the correlation and compensability between indicators, the weighting of the indicators as well as their high "degree of freedom" which enables one to readily manipulate them to produce desired outcomes. This research strives to minimise the aforementioned deficiencies of the current approaches through the introduction of a nonlinear aggregation approach for the estimation of a CSPI. The developed method can be summarised into two main steps: the introduction of mathematical definitions, which facilitate the pairwise comparison of indicators and the development of marginal and composite road safety performance functions. The method was applied for the assessment of both the temporal and spatial hotspots within Northern Ireland and Great Britain, facilitating a comprehensive benchmarking exercise. For temporal assessment, an additional analysis was carried out, using rates based on averaged hourly indicators. For the spatial assessment, two additional exposure indicators were incorporated into the model, namely the population density and the population, respectively. A comparative study was performed to assess the effectiveness of the proposed method over traditional weighting methods. Finally, cluster analysis and principal component analysis, have been used to investigate and highlight any hidden patterns associated with collisions that occurred in the most prevalent under-performing policing districts in Northern Ireland and Great Britain.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:705890 |
| Date | January 2016 |
| Creators | Coll, Bronagh |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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