## 2 Background
### Driver-Vehicle Interfaces  
DVIs are a particular type of Human-Machine Interface (HMI) that integrates hardware and software to enable efficient human-machine interaction. \begin{table}
\begin{tabular}{c c} \hline \hline
**Level** & **Description** \\ \hline
3 & Conditional Driving Automation \\ \hline
4 & High Driving Automation \\ \hline
5 & Full Driving Automation \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cont. This study focuses specifically on internal vehicle interfaces, excluding external interfaces that handle communication between the vehicle and other road users, such as pedestrians, cyclists and other motorists [23; 24; 25; 26]. In-vehicle interfaces provide information and facilitate interaction with passengers inside the vehicle, using visual, tactile, or auditory cues. [PERSON] et al. [27] note that visual interfaces, such as dashboard or windscreen displays, provide vehicle status and driving information. Auditory interfaces rely on sounds or acoustic signals, such as beeps or warnings, to attract the driver's attention, especially in critical situations. In contrast, haptic interfaces use physical feedback, such as vibrations in the steering wheel or seat, to communicate warnings without taking the driver's eyes off the road. The NHTSA outlines these interface classifications in its \"2016 Human Factors Design Guidance for Driver-Vehicle Interfaces\" report [27], which also discusses general guidelines for interface design. For example, the report examines visual displays that convey safety messages, and focuses on certain aspects of these interfaces such as display placement, use of colour, readability of text, etc. The NHTSA's goal is to ensure that interfaces are clear and unambiguous, avoiding driver distraction. In 2018, the US government agency developed specific guidelines for designing automated vehicle interfaces, particularly for Levels 2 and 3 of automation [28]. These recommendations aim to describe principles that clearly convey the change of control from the driver to the automation, while ensuring that the driver develops a consistent mental model. Guidelines on best practises for designing driver-friendly messages are given through consideration of the most appropriate integration of sensory modalities: visual, auditory, and tactile. It focuses on the usability and clarity of these messages, synchronising signals and information with the driver's needs. The design of interior interfaces must therefore be carefully considered to avoid misunderstandings or errors. This need has developed a tendency to create customisable interfaces. However, customised interfaces risk fostering overconfidence in drivers who could be induced to reduce their attention while driving. Such overconfidence, combined with potential interface errors, could trigger inappropriate actions in the driver due to inaccurate information received from the interface itself. A key case is [PERSON] et al. vs. Tesla Inc. (2018), which is currently under review by the Santa Clara County Superior Court in California. The case examines Tesla's responsibility for a fatal accident on 23 March 2018 in which [PERSON], an Apple engineer, was killed while driving his Tesla Model 101 on Route 101 in Mountain View, California. The lawsuit alleges that Tesla's Autopilot misunderstood road signs and failed to detect a concrete barrier, causing the car to speed toward the barrier instead of slowing down. [PERSON]'s family filed a lawsuit, citing product liability, failure to warn and misleading advertising claims. It also charged the state of California with inaction, alleging it had failed to install a guardrail that would have mitigated the damage caused by the crash. The NTSB confirmed Tesla's Autopilot was engaged during the accident and failed to detect [PERSON]'s hands on the wheel. The system also struggled to read the lane markings and was unable to detect the concrete median barrier. As a result, instead of braking, the system accelerated toward the barrier.