4.21 - SIESTA Enhancing Safety by usIng data from rEal-Time driver drowSiness feedbAck

Project description

Project SIESTA aimed to explore, for the first time, ‘opportunistic’ data to investigate driver behaviour namely distraction and drowsiness. The data was gathered from a driver-monitoring systems (DMS) vendor which developed two distinct solutions: a fixed dashboard infrared camera deployed in different companies and a smartphone camera-based application freely available for the general drivers’ population. The DMS solution emits an alert when detects distraction or drowsiness of the driver, storing a set of information of that event (e.g. date and time). Moreover, information about the journey (e.g. date and time of the start and end of the journey), the company name and the driver age and sex are also collected, depending on the DMS solution.  These two solutions lead to two distinct analysed populations. Two main goals were addressed, namely identification and analyses of risk factors and drivers’ profiles, based on two distinct statistical techniques. Regarding risk factors analysis, the results suggest for instance that increasing the driving continuous time of professional drivers, the number of alerts of both type increase too. If the driver stops during the journey, the number of alerts, either distraction and drowsiness, decreases. The duration time of the breaks revealed also an effect on the alert frequency. The results for non-professional drivers showed the same kind of trends, despite same differences. The results of the clustering analyses revealed at least three clusters of drivers that can be distinguish in terms of journey characteristics and alert frequency, allowing a clear classification. These findings were compared with other studies whenever was possible. Various limitations were found during the project arising mainly from the use of retrospective data which was gathered under conditions not observed and controlled by the research team. Overall, the project showed that data from emerged technology has potential to be explored to road safety studies.

Research team


  • António José Fidalgo do Couto
  • José Pedro Maia Pimentel Tavares
  • Sara Maria Pinho Ferreira (PI)
Financial Support


Stage of Progress
  • Concluded in 2018