First-stage evaluation of a prototype driver distraction Human-Machine-Interface warning system

Christine Mulvihill, Tim Horberry, Michael Fitzharris, Brendan Lawrence, Raphaela Schnittker, Mike Lenné, Jonny Kuo, Darren Wood

Research output: Contribution to journalArticleResearchpeer-review


Recent advances in vehicle technology permit the real-time monitoring of driver state to reduce distraction-related crashes, particularly within the heavy vehicle industry. Relatively little published research has evaluated the human machine interface (HMI) design for these systems. However, the efficacy of in-vehicle technology depends in large part on the acceptability among drivers of the system’s interface. Four variations of the HMI of a prototype multi-modal warning system developed by the authors for driver distraction were evaluated in a truck simulator with eight car drivers and six truck drivers. Driver acceptance of the HMIs was assessed using the System Acceptability Scale; and salience, comprehension and perceived effectiveness of components of the HMIs (modality, intensity of warning) were assessed using likert scales. The results showed that participants considered the HMIs to be acceptable and useful, and that the warning components were largely noticed, understood correctly, and perceived to be effective. Although this study identified no major design flaws with the recently developed HMIs, further simulator testing with a larger sample size is recommended to validate the findings. On-road evaluations to assess the impact of the HMIs on real world safety are a necessary pre-requisite for implementation.

Original languageEnglish
Pages (from-to)4-14
Number of pages11
JournalJournal of Road Safety
Issue number4
Publication statusPublished - 2021


  • Driver Distraction
  • Human Machine Interface
  • In-Vehicle Technology
  • Simulation
  • Warning Systems

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