Zukunftslabor
MOBILITÄT

Modern autonomous vehicles rely heavily on complex sensor systems for perception tasks, including Advanced Driver Assistance Systems and Autonomous Driving Systems. Accurate sensor perception is essential to ensure the safety of these systems, especially as the level of automation increases. External sensors from the infrastructure or other vehicles can provide useful information to verify the trustworthiness of on-vehicle sensors using V2X communication. This paper presents a novel concept of runtime monitoring to verify the performance of ADS perception systems, taking advantage of the design diversity of connected vehicles and infrastructure based perception sensors in Intelligent Transportation Systems. The proposed approach uses standardised V2X services, such as Collective Perception Service and Location Service from connected participants to estimate a reliable common environment model (CEM) of the driving situation. The established CEM can be used to evaluate the quality of perception of individual road participants during operation, allowing detection and mitigation of system malfunctions of a connected vehicle perception system and enhancing road safety in connected environments. We also discuss open design questions with respect to the perception runtime monitor concept

Current surveys indicate limited public and individual trust in autonomous vehicles despite a long tradition to ensure their (technical) trustworthiness in informatics and systems engineering. To address this trust gap, this article explores the underlying reasons. The article elaborates on the gap between trust understood as a social phenomenon and, in contrast, the research tradition aimed at guaranteeing (technical) trustworthiness. It discusses to what extent those research traditions in the social sciences and humanities have been recognized and reflected in systems engineering research to date. Trust, according to the current state of research in the social sciences and humanities, heavily relies on individual assessments of an autonomous vehicle's abilities, benevolence and integrity. By contrast, technical trustworthiness is defined as the sum of intersubjective, measurable, technical parameters. They describe certain abilities or properties of a system, often according to respective technical standards and norms. This article places the explainability of autonomous systems in a bridging role. Explainability can help to conceptualize an integrative trust layer to communicate a system's abilities, benevolence and integrity. As such, explainability should respect the individual and situational needs of users, and should therefore be responsive. In conclusion, the results demonstrate that learning from life requires extensive interdisciplinary collaboration with neighboring research fields. This novel perspective on trustworthiness aligns existing research areas. It delves deeper into the conceptual how, dives into the intricacies and showcases (missing) interconnectedness in the state of research.

This study investigates the influence of marketing activities of shared mobility service operators on their capacity utilization in multiple cities. We use a transactional dataset including trips from seven operators across sixteen German cities and analyze it using multilevel analysis. Our findings indicate that a wide assortment of vehicle types in a fleet and deep assortment in terms of fleet size are key drivers of capactity utilization, while pricing activities have a mixed impact. While higher unlock fees and a higher price per minute impact capacity utilization negatively, set up costs have a positive impact. Additionally, the study points at the risks of business area expansion, as it may lower capacity utilization. These insights provide operators of shared mobility services insights on the effects of marketing-related activities on capacity utilization.