# Interface Design for Responsible Remote Driving: A Study on Technological Mediation
## 4 Interface Design Analysis
### Sight: Video Feedback
#### 4.1.2 Augmented Reality  
To cope with reductions, the best strategy might be to build a multi-sensory (or multimodal) HMI by integrating visual feedback with other kinds of feedback, as the next subsections discuss. However, and interestingly, visual HMIs also offer a further possibility of amplifying vision by superimposing to the video feed data visualization tools aimed at translating non-visual reduced aspects into visual cues, thus minimizing the effects of the corresponding reductions and providing ROs with much needed additional context and guidance (e.g., Figure 4). Similar solutions can be loosely grouped under the umbrella of augmented reality (AR; e.g., [2; 44]). For example, a digital representation of the dashboard might help ROs  
Figure 4: Example of superimposed digital information on video feedback including various camera feeds (left, top, right) and a digital dashboard (bottom) displaying information on (left to right) control mode and system status, speed, acceleration, and cruise mode. obtain a clearer sense of speed and other (\"invisible\") information about vehicle status along with force-related information such as acceleration and braking, for which dedicated infographics might be created. Confusion about spatial orientation could be counteracted by superimposing maps showing vehicle position and current direction of travel. Maneu-vering problems caused by the reduction of width and depth perception might also be managed by superimposing visual cues. The over-impression of self-adjusting trajectories might enhance ROs' understanding of the vehicle's projected path and relative position with reference to obstacles. Additionally, depth perception might also be supported by integrating cues such as safe braking distance indexes or color-coded visual indicators similar to those used in rear-view cameras or in medical visualizations [45]. Width perception can be enhanced through visual representations such as collision avoidance zones, increasing ROs' spatial awareness and facilitating navigation through complex environments. Finally, the integration of other sensor technologies, such as LiDAR (Light Detection and Ranging), radar, and ultrasonic sensors to the system might provide supplementary data on distances, speed, and object detection, which could be translated into visual cues to further enhance ROs' SA and decision-making capabilities [46]. V2X connectivity might also open new amplification opportunities along the same line. Smart traffic cameras could transmit video feed to remotely operated vehicles, which, in turn, would relay it to visual HMIs and enable ROs to access visual information about incoming traffic or intersections situated beyond the FOV provided by vehicle sensors. Managing reductions by further amplifying vision, however, represents a mono-sensory solution that runs the risk of putting an excessive burden on ROs' perceptive and cognitive capabilities. Indeed, transmitting all information necessary to responsible RD through monitors might overload ROs' capacity to process it properly. On the one hand, cognitive overload might be caused by cumbersome methods of data visualization. For instance, symbolizing distance from an object through superimposed digital numbers might require too much cognitive effort to be quickly translated into actionable information [7]. However, the sheer amount of overlaid information, although easily interpretable, might lead to cognitive overload and communication failures--a problem that could be better handled through multi-sensory HMIs. That being said, AR technology could also be applied to intelligently manage ROs' cognitive capabilities and guide attention to salient elements displayed on monitors, thus amplifying sensitivity to salient stimuli. For example, AR tools paired with image recognition software could superimpose computer-generated imagery onto live video feeds highlighting safety-critical information about road conditions and potential hazards [47].