## 2 Background
### Highly Automated Vehicles  
The main difference between conventional vehicles and HAVs is that the latter will integrate Intelligent Transport Systems (ITSs), which will enhance surface transport safety and efficiency through advanced technologies. These systems include environmental sensors and V2V and V2I communications. ITSs use data collection and the analysis of real-time information on road conditions, traffic and vehicle status to optimise route planning and improve responses to unforeseen scenarios [12; 13; 14]. Singapore has already implemented advanced ITSs that efficiently manage traffic flow and reduce accidents, thus demonstrating the full potential of these systems [15]. The Society of Automotive Engineers (SAE) framework provides a widely accepted taxonomy of advanced driver assistance systems (ADAS) [3], as summarised in Table 1. \begin{table}
\begin{tabular}{c c} \hline \hline
**Level** & **Description** \\ \hline
0 & No Driving Automation \\ \hline
1 & Driver Assistance \\ \hline
2 & Partial Driving Automation \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Taxonomy of HAV automation levels according to SAE. This paper focuses on Levels 3 and 4 of automation due to their distinct requirements for driver involvement. Level 3 requires the vehicle to take control in certain situations, like driving on highways or in slow-moving traffic, while the driver must stay alert and ready to take over if needed. At this level, the DVI must provide clear, timely information to help the driver react quickly when needed [16]. On the other hand, Level 4 autonomy allows the vehicle to operate independently in certain areas or under certain conditions, such as in an urban environment with speed limits. In these scenarios, the driver's involvement is no longer required [3]. The focus of the DVI is to provide updates on the vehicle's status and operating parameters, ensuring intuitive interactions without compromising the driver's role. As HAVs continue to progress towards higher levels of autonomy, regulatory frameworks need to adapt to ensure their safe integration into the road network. In the EU, amendments to Regulation (EU) No 2018/858 established the legal basis for the approval of HAVs of SAE Level 3 and 4 in low-volume production from November 2022 [17]. Germany has enacted two major amendments to its Road Traffic Act (StVG): the 2017 amendment allowing for Level 3 automation and the 2021 amendment allowing for Level 4 automation outside of testing phases [18]. These laws address technical standards, operator roles, data management, and owner liability. Similarly, the UK's Automated Vehicles Act 2024 has laid the foundation for the widespread use of automated vehicles from 2026 by outlining the initial requirements for the use of vehicles [19]. The continuous evolution of HAVs requires robust communication with their environment, which can be achieved through ad hoc networks such as the Internet of Vehicles (IoV). This enables vehicles to adapt to unexpected events in real-time, such as sudden braking by a preceding vehicle [20]. However, the effectiveness of these systems depends not only on the level of intelligence of the HAVs, but also on the reliability of the IoV. HAVs are designed to handle a wide range of situations. However, a poorly designed IoV may hinder drivers' ability to interpret signals and make quick decisions, increasing the likelihood of accidents. [PERSON] et al. [21] note that unreliable human-computer interaction systems can undermine safety by distracting drivers, exposing vehicles to cyber threats and decreasing user confidence. Distracted driving remains a leading cause of crashes, with the National Highway Traffic Safety Administration (NHTSA) predicting that distracted driving will lead to 3308 deaths and approximately 290,000 injuries in 2022 [22]. DVIs can also contribute to this issue because if these interfaces are not clear and intuitive they can force drivers to shift their attention away from the road to understand information, creating a distraction.