An Active Safety System for Wheeled Mobile Driving Simulators

Wheeled mobile driving simulators (WMDS) represent an innovative concept in driving simulator technology that differs from conventional systems in its independence from a fixed infrastructure. Instead, WMDS move like mobile robots on wheels within a given open space, requiring novel approaches to establish safety. Previous safety concepts ensured continuous controllability of the WMDS, but required the intervention of operators to protect against collisions. The following work addresses the research question of whether the unbound movement of a WMDS can be actively safeguarded with a likewise mobile safety architecture. For this purpose, requirements are defined and based on this, the feasibility is practically examined. It is deduced that an active safety architecture for WMDS requires two further safety functions: A workspace compliance function that forces the WMDS to maintain its prescribed workspace during a driving simulation, and a collision protection function to actively protect the test person and people in the WMDS environment from collisions. Minimum functional requirements are derived in terms of required measurement quantities and decision logics. This results in a concept that monitors the presence and distance of objects within a speed-adaptive protection zone around the WMDS as well as the compliance with local, position-dependent speed limits, demanding reliable information of the WMDS position and speed in the entire workspace. So far, no sensory systems for those measurement quantities have been realized for an application for WMDS. Therefore, this work investigates hardware and software components that can reliably perform the intended functions within the operational design domain (ODD) of a WMDS. An approach based on lidar sensors is chosen to implement all required measurement variables with the addition of artificial workspace landmarks. The hardware and software requirements are concretized, selected sensors are implemented on a physical prototype and software algorithms are presented. Finally, the resulting safety system is evaluated in a representative environment. The design goals and the evaluation address the safety of the intended function under all conceivable operational conditions, fault detection capability and robustness against undesired interventions during WMDS operation. If the functions prove themselves under the most difficult conceivable operational conditions, they are considered suitable as a safety relevant function. The results of the work show that landmark-based position and velocity detection can fulfil the requirements of a safety-related function for workspace compliance. For object detection, the fulfilment of the target function can be shown, but only under ODD limitations of the WMDS. The general applicability of lidar sensors for the active safety system is thus not considered to be falsified with the results, but limited by further requirements, e.g. on the ground conditions of the workspace. The findings of this work provide requirements, test cases and promising approaches for an active safety system for WMDS that can be followed up and optimised in future work

Prädiktionsbasierte Optimierung des Betriebs elektrischer Antriebsstränge unter Nutzung von Silent Testing automatisierter Fahrfunktionen

Betriebsstrategien für komplexe elektrische Antriebsstränge mit mehreren E-Maschinen basieren häufig auf stark vereinfachten Regelungsmodellen, um ausreichend schnelle Strategieoptimierungen zu ermöglichen. Im Folgenden stellen die TU Darmstadt und Rimac einen Ansatz vor, der die Umgebungswahrnehmung nutzt, um das zukünftige Fahrverhalten zu prädizieren und so zusätzliche Zeit für die Verwendung genauerer Optimierungsmodelle zu gewinnen. Auf diese Weise können Perzeptions- und Planungsmodule, die derzeit für automatisierte Fahrfunktionen entwickelt werden, in einer nicht sicherheitsrelevanten Funktion eingesetzt werden. Dies ermöglicht eine neue Art des sogenannten Silent Testing bei der ein erlebbarer Mehrwert für die Fahrzeugnutzer entsteht

Systematic derivation of use case clusters for a generalized low-speed automated driving function

One approach for the introduction of SAE Level 3+ Automated Driving are low- speed driving functions due to a reduced risk associated with them. In this paper, a systematic methodology to derive use cases and use case clusters for low-speed applications of Automated Driving (AD), which can be potentially fulfilled by a generalized low-speed function architecture, is described and applied. The use case clusters are defined according to a classification of the derived use cases in the dimensions of safety and technical capabilities. Thereby, the results of this paper simplify the definition of the ODD as well as the functional requirements and architecture for the future development of low-speed AD functions

Rolling out a new Driving Simulator Concept - Design and Challenges of Wheeled Mobile Driving Simulators

Wheeled mobile driving simulators (WMDS) intend to cue the motion of road vehicles by moving a tire-bound, electrically driven, omnidirectional platform. The motion space of a WMDS is a planar surface, which can theoretically be increased infinitely without having to modify the system itself. The concept therefore has high potential to represent scenarios with long-lasting, longitudinal and lateral accelerations with high immersion. For this reason, the Technical University of Darmstadt and the Technische Universität Dresden are both independently developing full-scale prototypes of a WMDS. Both are currently working on common research questions and challenges, which arise from the tire characteristics and the unboundness of the system. This paper aims to give an overview of the two simulator designs and an insight into the main research topics and solution approaches for the development of wheeled mobile driving simulators

AUTOtech.agil: architecture and technologies for orchestrating automotive agility

Future mobility will be electrified, connected and automated. This opens completely new possibilities for mobility concepts that have the chance to improve not only the quality of life but also road safety for everyone. To achieve this, a transformation of the transportation system as we know it today is necessary. The UNICARagil project, which ran from 2018 to 2023, has produced architectures for driverless vehicles that were demonstrated in four full-scale automated vehicle prototypes for different applications. The AUTOtech.agil project builds upon these results and extends the system boundaries from the vehicles to include the whole intelligent transport system (ITS) comprising, e.g., roadside units, coordinating instances and cloud backends. The consortium was extended mainly by industry partners, including OEMs and tier 1 suppliers with the goal to synchronize the concepts developed in the university-driven UNICARagil project with the automotive industry. Three significant use cases of future mobility motivate the consortium to develop a vision for a Cooperative Intelligent Transport System (C-ITS), in which entities are highly connected and continually learning. The proposed software ecosystem is the foundation for the complex software engineering task that is required to realize such a system. Embedded in this ecosystem, a modular kit of robust service-oriented modules along the effect chain of vehicle automation as well as cooperative and collective functions are developed. The modules shall be deployed in a service-oriented E/E platform. In AUTOtech.agil, standardized interfaces and development tools for such platforms are developed. Additionally, the project focuses on continuous uncertainty consideration expressed as quality vectors. A consistent safety and security concept shall pave the way for the homologation of the researched ITS