Variation in driving controls and in-vehicle information systems: Impact on fleet drivers

Road crashes are the most common form of work-related fatalities, injuries and absence from work in Australia, and studies show that one quarter of all company cars are involved in a crash each year.

Drivers receive their license on one model of car but later drive different models with an array of variations in presentation and function of controls, inherently and immediately introduce risk. Fleet drivers are required to interact with changes in interface systems and smart technology more frequently that other drivers. Despite fleet drivers being expected to know all systems in cars they are required to drive for work they often do not know how to use or do not wish to use new systems.

This project is further investigating the issues faced by fleet drivers changing from a car model with less technological features to one with new sets of controls with new functions and back again on a regular basis. The impact of driver’s existing mental models have not been given enough recognition as introducing higher levels of risk due to increased variation in driver controls and interfaces. Under stressful situations a fleet driver may react by reverting back to control expectations formed on a previous car resulting in incorrect control selections in the current car. Time spent familiarising drivers with different controls to build new and relevant automaticity is essential.

Research Aims:
• Provide organisations with information on the strengths/limitations of their current fleet safety policies in relations to fleet variations.
• Highlight areas where driver performance can be improved in terms of learning about and interacting with variations in controls and in-vehicle information systems.
• Recommendations on proactive training improvements to target car variations to achieve performance improvement when drivers change between vehicles in the fleet.


Funding / Grants

  • IHBI Seeding Grant (2019 - 2020)

Other Team Members

This project includes researchers from University of Queensland.