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Safety research has focused on drivers, pedestrians and vehicles, with scarce attention given to highway traffic officers (HTOs). This paper develops a robust prediction model which enables highway safety authorities to predict exclusive incidents occurring on the highway such as incursions and environmental hazards, respond effectively to diverse safety risk incident scenarios and aid in timely safety precautions to minimise HTO incidents.

Using data from a highway incident database, a supervised machine learning method that employs three algorithms [namely Support Vector Machine (SVM), Random Forests (RF) and Naïve Bayes (NB)] was applied, and their performances were comparatively analysed. Three data balancing algorithms were also applied to handle the class imbalance challenge. A five-phase sequential method, which includes (1) data collection, (2) data pre-processing, (3) model selection, (4) data balancing and (5) model evaluation, was implemented.

The findings indicate that SVM with a polynomial kernel combined with the Synthetic Minority Over-sampling Technique (SMOTE) algorithm is the best model to predict the various incidents, and the Random Under-sampling (RU) algorithm was the most inefficient in improving model accuracy. Weather/visibility, age range and location were the most significant factors in predicting highway incidents.

This is the first study to develop a prediction model for HTOs and utilise an incident database solely dedicated to HTOs to forecast various incident outcomes in highway operations. The prediction model will provide evidence-based information to safety officers to train HTOs on impending risks predicted by the model thereby equipping workers with resilient shocks such as awareness, anticipation and flexibility.

The purpose of this paper is to demonstrate how critical realism can be mobilised as a meta-theory, or philosophical under-labourer, for research on space accounting and how this may further inquiries into the known as well as the unknown implications of space exploration and commercialisation.

This is a conceptual paper that applies critical realism to the field of space accounting using cost management in space contracts as an illustrative example.

Adopting a naturalised version of critical realism that recognises the complex interplay between natural and social realities, the author nuances the distinction between intransitive and transitive objects of knowledge and advances a framework that may be used as a starting point for a transfactual mode of reasoning. The author then applies this mode of reasoning to the topic of cost management in the space sector and illustrates how it may enhance our insights into what causes cost overruns in space contracts.

By adopting a naturalised version of critical realism, the author establishes a philosophical framework that can support the broadly based, inter-disciplinary research agenda that has been envisaged for research on space accounting and possibly inform policy development.

This paper is the first to apply a critical realist perspective to space accounting and lays a philosophical foundation for future research on the topic.