In the course of the current demographic change, the proportion of the population aged 65 and older is projected to steadily increase in many countries of the world (UN DESA Population Division, 2015). The ageing society is reflected in an increasing number of older road users (Koppel & Berecki-Gisolf, 2015), especially considering the growing need for older adults to maintain individual mobility (Eby & Molnar, 2012). This development raises new issues of transportation research, since age-related changes in mobility patterns as well as sensory, cognitive, and motor functions reduce older adults’ traffic safety (Polders, Vlahogianni, Leopold, & Durso, 2015). Accordingly, new strategies to aid older drivers and their mobility needs are required, which could potentially be provided by emerging in-vehicle technologies (Karthaus & Falkenstein, 2016). The overall aim of present dissertation project was to evaluate whether in-vehicle technologies that appear promising to support older drivers can actually contribute to their individual mobility, which requires an improvement in aspects related to driving performance as well as the acceptance of such systems in this age group. Therefore, contact-analogue head-up displays (also labelled as Augmented Reality Displays, ARDs) and highly automated driving were selected as two exemplary technologies, representing completely different levels of driving automation and accordingly different approaches to support drivers. The ARD-technology represents a technical implementation approach for IVIS and therefore an example for Automation Level 0 (no automation; SAE International, 2014) by helping the driver to execute the driving task manually through useful information. In contrast, the HAD-technology aims at supporting the driver by taking over the driving task, which corresponds to Automation Level 4 (high automation; SAE International, 2014). Despite these different approaches, both technologies were previously assumed to have a strong potential to support especially older drivers (Meyer & Deix, 2014; Polders et al., 2015; Rusch et al., 2013; Schall et al., 2013). Three empirical studies were conducted to examine performance- and acceptance-related aspects of both technologies. All studies were carried out with a group of older drivers (maximum age range: 65 85 years) and a younger comparison group (maximum age range: 25-45 years) representing the ‘average’ (i.e. young, but experienced) driver in order to identify age-specific results. Focusing on performance-related aspects of the ARD-technology, Study I represents a reaction time experiment conducted in a driving simulator. One age-specific beneficial function of such an ARD is to provide prior information about approaching complex traffic situations, which addresses older drivers’ tendency to process multiple information successively (serially) rather than simultaneously (parallel) (Davidse, Hagenzieker, van Wolffelaar, & Brouwer, 2009; Küting & Krüger, 2002). Therefore, the aim of this study was to examine the effects of an ARD providing prior information about approaching intersections on drivers’ speed and accuracy of perceiving these intersections, which is considered a necessary precondition for a safe driving performance (Crundall & Underwood, 2011). Based on concerns about the counterproductive effects of presenting information via an ARD, especially in cases of inaccurate information, system failures were included in this examination. The ARD-information aided drivers from both age groups in identifying more relevant aspects of the intersections without increasing response time, indicating the potential of the system to support both older and younger drivers in complex traffic situations. Experiencing system failures (i.e. inaccurate information) did offset this positive effect for the study’s duration, particularly for older drivers. This might be because it was difficult to ignore inaccurate prior information due to their presentation via an ARD. Study II represents a driving simulator study on acceptance-related aspects of an ARD providing prior information about approaching intersections. This study focused on the effects of system experience on drivers’ acceptance as well as on the identification of age-specific acceptance barriers that could prevent older drivers from using the technology. In summary, older and younger drivers’ evaluation of the ARD was positive, with a tendency to more positive evaluations with than without system experience in the driving simulator. Compared to the younger group, older drivers reported a more positive attitude towards using the ARD, even though they evaluated their self-efficacy in handling the system and environmental conditions facilitating its usage as less strong. Both performance- and acceptance-related aspects of HAD were addressed in Study III, a two-stage driving simulator study. The focus of the performance perspective shifted in parallel with the shift of the human role from driver to passenger due to the increasing driving automation. Accordingly, the examination of HAD was focused on the human evaluation of the automated system’s driving performance. In this context, affective components of human-automation interaction, such as comfort and enjoyment, are considered important for the acceptance and thus usage of automated vehicles (Tischler & Renner, 2007). It is assumed that the implemented driving style has an impact on such affective components in the context of HAD (Bellem, Schönenberg, Krems, & Schrauf, 2016). One theoretical approach to increase the comfort of HAD recommends the implementation of familiar, natural driving styles to mimic human control (Elbanhawi, Simic, & Jazar, 2015). Therefore, the effects of driving automation and the familiarity of the HAD-style on driving comfort and enjoyment were examined. Automation increased both age groups’ comfort, but decreased younger drivers’ enjoyment. For all dependent variables, driving style familiarity significantly interacted with drivers’ age the same way: while younger drivers preferred a familiar HAD-style, older drivers preferred an unfamiliar driving style in a highly automated context. Accordingly, the familiarity approach can be supported at least for younger drivers, but not for older drivers, whose manual driving styles are characterised by strategies to compensate for age-related impairments of sensory, cognitive, or motor functions. HAD-style preferences of this age group seem to be more influenced by the desire to regain a driving style free from these compensation strategies than by a need for familiar driving manoeuvres. In parallel with the evaluation of the ARD, acceptance-related issues in the context of HAD included the effects of system experience on drivers’ acceptance and potential age-specific acceptance barriers. Considering a system-specific design issue, it was additionally examined whether drivers’ acceptance of HAD is modifiable by the familiarity of the implemented driving style. In this driving simulator study, members of both age groups showed slightly positive a priori acceptance ratings, which significantly increased after the initial experience and remained stable afterwards. Similar to drivers’ acceptance of the ARD, older drivers reported a more positive attitude towards using HAD despite their lower self-assessed self-efficacy and environmental conditions facilitating HAD-usage compared to younger drivers. Regarding HAD-style, acceptance was subject to the same interaction between drivers’ age and driving style familiarity as driving comfort and enjoyment. These findings demonstrate that effective approaches to support the independent mobility of older adults are provided by emerging in-vehicle technologies on different levels of driving automation. The majority of the performance-related improvements did apply to both older and younger drivers, confirming that automotive technologies suggested for older drivers have the potential to support drivers of other age groups as well. Regarding drivers’ acceptance, findings suggest that both systems would be accepted by different age groups, which correspondents to the results from the performance perspective. The comparable acceptance patterns identified for two systems at different stages of driving automation, such as ARDs and HAD, indicate underlying general aspects of older adults’ acceptance of in-vehicle technologies. This includes their strong need to preserve their individual mobility as well as their lower self-efficacy in handling relevant technologies and insufficient access to a support infrastructure. These insights can enrich both theories of older drivers’ acceptance of in-vehicle technologies and measures to ensure the successful development and introduction of systems aiding them in maintaining a safe individual mobility. Considering the importance of driving for older adults’ physiological and psychological well-being (e.g. Adler & Rottunda, 2006; Lutin, Kornhauser, & Lerner-Lam, 2013), these results emphasise the potential of emerging in-vehicle technologies to improve both older drivers’ traffic safety and quality of life.