The increasing development of autonomous vehicles (AVs) influences the future of transportation. Beyond the potential benefits in terms of safety, efficiency, and comfort, also potential risks of novel driving technologies need to be addressed. In this article, we explore risk perceptions toward connected and autonomous driving in comparison to conventional driving. In order to gain a deeper understanding of individual risk perceptions, we adopted a two‐step empirical procedure. First, focus groups (N=17) were carried out to identify relevant risk factors for autonomous and connected driving. Further, a questionnaire was developed, which was answered by 516 German participants. In the questionnaire, three driving technologies (connected, autonomous, conventional) were evaluated via semantic differential (rating scale to identify connotative meaning of technologies). Second, participants rated perceived risk levels (for data, traffic environment, vehicle, and passenger) and perceived benefits and barriers of connected/autonomous driving. Since previous experience with automated functions of driver assistance systems can have an impact on the evaluation, three experience groups have been formed. The effect of experience on benefits and barrier perceptions was also analyzed. Risk perceptions were significantly smaller for conventional driving compared to connected/autonomous driving. With increasing experience, risk perception decreases for novel driving technologies with one exception: the perceived risk in handling data is not influenced by experience. The findings contribute to an understanding of risk perception in autonomous driving, which helps to foster a successful implementation of AVs on the market and to develop public information strategies.

No abstract

No abstract

Although electric drives can locally reduce the environmental impact of traffic, the penetration rates of battery electric vehicles (BEV) are far below expectations, not least because the charging infrastructure network is still considered insufficient by potential users. Therefore, the planning of charging infrastructure that considers both needs and user requirements is essential to remove an important barrier to widespread adaptation of e-vehicles, but it is also a challenge. A better understanding of the charging behavior and the underlying usage motivation is therefore needed. A frequently mentioned factor is the so-called range stress. While there are many studies on this subject with new BEV users, there is a lack of approaches that also include experienced e-vehicle users and at the same time allow a comparison with drivers of cars with internal combustion engines (ICE). In this paper, this is realized with the help of a questionnaire study ( n = 204 ). The results show that ICE and BEV users at different experience levels hardly differ regarding the perceived range stress; BEV users even perceive less stress. BEV users also showed more trust in the vehicle and in the tank/battery indicators, while this trust depends only marginally on the type of information provided by the car. Furthermore, there is a correlation between users’ technology commitment and risk-taking, on the one hand, and range stress, on the other. However, for the prediction of range stress, gender, experience with e-cars, and the question of whether cars are privately owned, or car-sharing is used, are more relevant.

Autonomous driving will provide higher traffic safety, meet climate-related issues due to energy-saving mobility, and offer more comfort for drivers. To ensure reliable and safe autonomous traffic, and to provide efficient and time-critical mobility services, data exchange between road users and systems is essential. In public perception, however, sharing data and information may pose a challenge due to perceived privacy restrictions. In this paper, we address user perceptions and their acceptance towards data and information distribution in autonomous driving. In a multi-step empirical procedure, qualitative (focus groups, guided interviews) and quantitative approaches (questionnaire-study) were combined. The findings reveal that autonomous driving is commonly seen as a highly useful and appreciated technology. Though individual risk perceptions and potential drawbacks are manifold, mainly described in terms of data security and privacy-related issues. The findings contribute to research in human-automation interaction, technical development, and public communication strategies.