A segmentation of drivers is presented, based on driving style, behaviours and attitudes. Four main segments are identified and described. The segmentation was complied using the Delphi method and is based on the synthesis of the views of a range of leading experts in the field.
The segmentation is an essential first step in understanding drivers and creating solutions which will enhance driving behaviour and find acceptance among the drivers at who they are targeted.
One approach to enhancing driving safety is Advanced Driver Assistance Systems [ADAS]. These use in-car technology to assist the driver and potentially enhance safety. However, the success of these systems is likely to depend on drivers’ acceptance of them and this may vary from segment to segment.
Statistics show that there are a wide variety of different types of accidents and a variety of behavioural causes. These reflect drivers’ attitudes towards driving and the approaches and behaviours that they bring to the road (Lancaster and Ward 2002).
This paper reports a study in which drivers were segmented according to attitudes and behaviours. The approach was based on a technique known as the Delphi method (Linstone and Turoff 1975) This involves interviewing experts in a particular field – in this case driving and driver behaviour – and coming to a conclusion based on the common ground between them.
In this case representatives of the following institutions were interviewed: Institute of Advanced Motorists, Royal Society for the Prevention of Accidents, Transport Research Laboratory, Brunel University, Chalmers University, Driving Standards Authority, Driving Instructors’ Association.
The outcome was the segmentation described below. This doesn’t necessarily represent the views of any of the organisations listed above, but rather a composite of their views based on the professional judgement of the author.
Drivers were largely defined by their attitudes towards speed and their attitudes towards safety. These two dimensions formed the primary variables for the segmentation and drivers positioning on these dimensions was broadly predictive of not only their attitudes, but also their driving behaviour.
A range of secondary variables associated with each of the segments was also identified. These included:
* Demographics: age, gender, socio-economic status etc.
* Accidents: the frequency with which drivers were likely to have accidents as well as the nature and causes of the accident.
* Examples of Behaviour: the way that drivers behave when they are on the road. This includes the risks that they may take and their attitudes and behaviour towards other road users.
* Enjoyment of Driving: is driving something they enjoy, is it a chore or is it something they actively fear?
* Distances: the average mileage covered per year.
* Type and Purpose of Journey: the reason that people make journeys and the characteristics of their journeys in terms of road type etc.
* Car Type: the types of car that people in each of the segments are most likely to drive." (Continued via uiGarden.net, Jordan, Patrick W. Chen, Fang, Lindgren, Anders
Chalmers) [Ergonomics Resources]