Geodemographic profiling of culpable drivers to target road safety interventions in serious injury crashes

Injury caused by road traffic collisions impose significant human and financial burdens on society.

In the UK, several decades of concerted effort to reduce traffic injuries significantly reduced fatalities and injuries, however, that reduction plateaued from around 2010.

To further improve road safety in the UK county of Cambridgeshire, a Vison Zero approach to road safety has been adopted by the Vision Zero Partnership of the Cambridgeshire and Peterborough Road Safety Partnership and the Cambridgeshire Police and Crime Commissioner (Vision Zero Partnership, 2020).

As part of the reach toward improved measures for road safety improvement, this research explored and developed a new approach to reduce road traffic casualties by evaluating the potential use of geodemographic profiling to deliver targeted road safety interventions. The profiling, allowing the application of direct and social marketing methods, common in other fields, to the delivery of road safety interventions is proposed, with preliminary application of the technique. This technique is not currently applied to road safety interventions but has been instrumental in the fields of retail and business since its introduction. The research used injury collision data and hospital trauma patient data for the county of Cambridgeshire over a five-year period from 2012 to 2017.

Three studies were conducted to explore which factors could differentiate the motor vehicle drivers involved in the collisions. The first linked STATS19 police collision data to hospital trauma patient data to identify the collisions which resulted in a clinically serious injury at MAIS3+, to be explored further along with the collisions resulting in a fatality. The second undertook culpability scoring of the motor vehicle drivers involved in the collisions identified. The third geodemographically profiled the motor vehicle drivers involved in the identified collisions.

The analysis undertaken provided information on the preliminary application of the technique as well as exploring the sample characteristics. The data linkage process successfully linked the patient data to the collision data. The culpability scoring tools available in the literature were successfully applied to the motor vehicle driver related collision data. This also led to the proposition of an alternative culpability scoring tool specifically designed for UK police collision data for the purpose of segmenting the drivers into culpable and non-culpable categories, which could be applied to bulk data.

The collision data contained sufficient postcode data to allow the profiling of the motor vehicle drivers. Analysis of the profile distribution identified profiles which occurred more frequently in the collision data, additionally, the majority of the most frequent were also overrepresented compared to the general population. The contributory factors involved in attributing motor vehicle driver culpability in the most frequent profiles showed similarity with the national statistics, where poor driving standards were primarily involved. The successful segmentation of the driver population opens opportunities to apply direct and social marketing methods to intervention application.

The data analysed was for one county in the UK, but overall, these studies showed that the methodology was applicable to any geographic construct within the UK, given suitable access to data. Importantly it would enable resources to be used more efficiently.