# Determining Key Parameters with Data-Assisted Analysis of Conditionally Automated Driving
## 1 Introduction  
The ever-advancing automation of vehicles is bringing more and more comfort to our daily migrations. However, along with convenience, many new challenges are being introduced. Recent studies show that in densely populated cities, children, the older population, and individuals with low income would be the main beneficiaries of fully automated vehicles, as they would improve their traveling possibilities [1; 2]. For those who would benefit, the main concerns are accessibility, privacy, reliability, and safety of shared automated vehicles [3; 4; 5]. Insights showed that the elderly population is only willing to use a vehicle equipped with an automated driving system (ADS) if it is supervised by a human operator [6]. Therefore, remote control by a human driver is one of the possible countermeasures, although it is associated with a number of other safety concerns [7]. In terms of safety, Western European countries are more pessimistic than Asian countries [8]. Although potential users would be willing to pay more for a conditionally or fully automated vehicle [9; 10], it seems unlikely that the future will be dominated by privatelyowned automated vehicles, as the total vehicle kilometers traveled could increase by as much as 60%, with more than half of these being zero-occupancy trips [11]. Getting back from the future, today's technology trends are mainly focused on conditionally automated driving, the automation level where the vehicle can drive on its own in some predefined environments (highway, cities with dedicated road infrastructure, sunny weather, etc. ), but can request the driver's intervention at any time in case of unpredictable situations that cannot be handled by the internal algorithms. The Society of Automotive Engineers (SAE) defines this as Level 3 (L3) conditional driving automation [12]. During fully automated driving, the driver can engage in secondary tasks, such as checking mail, answering missed calls, etc. However, the driver must always be present in the driver's seat in case the vehicle issues a take-over request (TOR) that requires intervention within a limited time (usually within a few seconds [13]). Then, the driver is solely responsible for resolving the potentially critical situation. Research by [PERSON] et al. showed that drivers are willing to engage in L3 automated driving if the perceived situations do not appear too complex [14]. Ensuring safe driving continuity is even more important in L3 automated vehicles, as more drivers tend to use their mobile phones or other handheld devices while driving, transforming their vehicles into mobile offices. Multitasking to mitigate the negative effects of travel time and to use travel time more efficiently for work or study is already present in conventional transport modes and is only expected to increase with the introduction of L3 vehicles [15; 16]. If the driver is using a handheld device when a TOR is issued, the reaction time consists of periods for gaze switching, information gathering, and cognitive processing, which together result in gaining situational awareness, and a period for decision making [17]. According to [PERSON]'s theory of situational awareness, one must be aware of a situation before any effective action could be taken [18]. Therefore, reduced engagement in driving tasks (due to the use of handheld devices, etc.) results in an additional period for handling the switch between non-driving and driving tasks, thus increasing the time needed to (re)gain situational awareness, to know what is going on around you. From the perspective of a vehicle user interface (UI) developer, it is of crucial significance to use an appropriate interface that makes it easy and efficient for the driver to put away the handheld device and regain situational awareness, e.g., by choosing the appropriate modality, display, timing, etc. [19; 20; 21]. Nowadays, almost everything in a vehicle is monitored. There are many sensors available, but how can they be used to help the driver regain situational awareness after a TOR?