Perceiving the rear view : Design to enhance the human-machine interaction in Camera Monitoring Systems

As the automotive industry becomes increasingly digitalised, demands for bothsafety and driver experience grow. One step in this development is the transitionfrom side mirrors to camera-based systems, known as Camera MonitoringSystems (CMS). These offer advantages such as improved aerodynamics, a widerfield of view, and enhanced visibility in poor weather conditions. However,challenges related to depth perception remain, as screens replace conventionalmirrors, making distance estimation more difficult. With increased digitalisationdrivers also become more skeptical of new systems, especially if they areperceived as difficult to interpret or unreliable. There is therefore a need forsolutions that are clear, intuitive and foster trust. This study investigates how different types of augmentations in CMS affectdistance estimation during overtaking scenarios. Thirty participants viewed videosequences from a vehicle in three different road scenes, using four interfacetypes: a base case without augmentation and three with different AR solutions.Participants estimated the distance to an overtaking vehicle, rated theiruncertainty and answered questions about their experience and preferences. The concept using distance lines and vehicle outlines performed best in bothdistance estimation and user experience. It was described as clear, reliable, andmodern and was the most desirable by participants. A learning effect from theconcept was observed, as estimations in the base case improved after thedistance lines were removed. The study suggests that CMS augmentations should use intuitive depth cues,colours that are accessible to all users and visual elements that appear anddisappear at appropriate times. Recommendations for future research includeexploring sound as a complement, symbol-based warnings and longer-termstudies to assess acceptance over time.