Future work and research is based on limitations identified as part of the experiment implementation and possible techniques to overcome them. An opportunity to apply the experiment to another research problem is also considered.
Changes to current experiment design
As previously discussed, rerunning the experiment with three target values instead of two may help to improve the false positive issue identified in this experiment. This would involve commencing the experiment from the initial data selection stage and redefining the target values as fatal, serious and slight instead of fatal and no-fatal as in
the current research. In addition consideration of the data groups by a subject matter expert may provide additional insights which could help extract more meaningful contributory factors.
The experiment could also be expanded to consider the results obtained for serious and slight accidents and identify the related key predictors and contributory factors. This experiment extracted data from the STATS19 accident dataset. There are two other STATS19 datasets maintained vehicle and casualty and integrating the three datasets may provide additional insights. Unfortunately due to time constraints and insufficient data knowledge, it was not considered as part of this research experiment.
Support vector machine (SVM)
Research has demonstrated that SVM has been successful in improving the accuracy of cancer classification where clustering was applied before classification (Wahed, et al., 2012). As accuracy was the key limitation of this research experiment evaluation, this technique is of interest. Similarly if clustering was applied to traffic accident data, a rare event like cancer, before applying a classification technique, like SVM, the prediction accuracy may be improved. SVM classification is available in SPSS Modeler.
Consider applying the experiment to Irish road accidents
The experiment was completed based on the UK STATS19 data due to the availability, quality and wide use of the data. However, the experiment could also be applied to the Irish road accidents, although the scope may need to be widened as fatal accident volumes may not be sufficient. Road safety trends are in line with trends in the UK, as outlined in Fig. 6.1, with similar proportion of deaths by road user group.
Figure 6. 1 Trends in Ireland road traffic accident deaths
In order to assess the readiness in Ireland to meet the experiment requirements, a brief questionnaire was prepared and forwarded to a road safety professional in Ireland. The results of the questionnaire are presented in Appendix 1. From the reply it appears that road safety data is consistently recorded and reported and some consideration has already been given to the application of predictive analytics to road safety in Ireland.
6.6 Conclusion
This final chapter considers the experiment completed as part of the research and results achieved. The initial objectives achieved are outlined, together with contributions to the body of knowledge identified during the course of the research. The experiment achievements and limitations are discussed. Future work which could help overcome limitations in this experiment or add to the research learning is considered.
The experiment met many of the initial objectives and although accuracy performance was poorer than expected, fatal traffic accidents prediction was successful. Consideration has been given to further work which could improve the experiment results.
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