Driver state monitoring using consumer electronic devices : Innovation report

An impaired mental and physical state such as fatigue, high level of workload, or distraction, can make a driver prone to errors and lead to sub-optimal driving performance. If a human remains in full or partial control of a vehicle, drivers’ state is an important aspect of driving and cannot be neglected, given its significant impact on road safety. It is, therefore, beneficial for future automobiles to be fitted with a feature which enables detection of any physical and mental abnormalities in drivers’ state in real time using physiological and emotional indicators. Such a feature is often referred to as Driver State Monitoring (DSM) system. It is forecasted that DSM is expected to become a standard passenger car feature by 2025 and its integration is encouraged by the standards authorities. Previous research has predominantly considered the use of medical grade devices for the purpose of DSM. Instead, this research project has considered the potential use of Consumer Electronic Devices (CEDs) as part of DSM. However, the literature lacks evidence that this can be accomplished in a valid and reliable manner. Thus, the research, presented in this doctorate, aims to provide knowledge that describes feasibility and integration of CEDs into the vehicles for the purpose of DSM, from both technological and human factors perspectives. Firstly, this research project has produced a model of a hybrid DSM system. The model combines physiological and emotional sensing within CEDs. This can be used to enhance validity and reliability of DSM in a flexible and cost-efficient manner. The model also acknowledges barriers of introduction of hybrid DSM into the automotive market. Acceptance, one of the important adoption barriers of DSM technology, was studied and behaviour intention to use the system was statistically appraised using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. It was found that social influence is a significant factor affecting drivers’ behaviour intention to use hybrid DSM in the near future. On the other hand, it was demonstrated that there is no significant negative attitude towards the use of hybrid DSM technology due to apprehension, intimidation, or fear of making mistakes. These findings indicate viability of DSM in the driving context. To further deepen understanding of CED-based DSM, three driving simulator user trials were conducted. Overall, supporting evidence for adoption of CEDs in DSM was provided by utilising state of the art methodology in DSM while characterising sensory capabilities of CEDs. The studies were specifically aiming to (1) determine the reliability and validity of wearable CEDs to measure human physiology while driving, (2) provide supporting evidence for employing CEDs in physiological and emotional evaluation of common driving activities, and (3) explore the effect of cognitive and visual workload on drivers’ state and driving performance during the automated to manual control transition scenarios. All three studies have demonstrated evidence of CEDs being well suited to reliably monitor drivers’ state. For instance, it was demonstrated how an extent of workload can be reliably measured using heart rate variability, captured by means of CEDs in the driving context. This approach could enable cost-efficient access to drivers’ state outside of driving activities