Open.Connected.Testbed

As the main goal of the automotive industry is to develop safe, efficient and affordable mobility concepts, a number of innovative concepts are being validated in virtual or real testing environments. However, the upcoming challenges related to automated driving will involve a significant shift to strongly context-embedded vehicle technologies. Broad modular and virtual/real development approaches are a key to managing the resulting complexity in system design. The unique OPEN.CONNECTED.TESTBED concept, a R&D infrastructure representing a suitable framework for open experimentation with highly innovative solutions, is currently under investigation.

Current market trends show a significant shift to strongly contextembedded vehicle technologies, which require more holistic system consideration for adequate investigation of vehicle, driver (human), environment (infrastructure) and data (cloud) interactions. An all-encompassing engineering framework is generally not available today, and the human factor, in particular, is not currently covered with the required depth, which significantly limits future innovation capacity.

Figure 1: Cross-Domain experimentation platform

Envisioned R&D infrastructure

The OPEN.CONNECTED.TESTBED approach seeks to bridge this gaps between individual stand-alone simulations (real and virtual), thereby providing an open R&D infrastructure that combines real testing with virtual design in real-time. Research plans include the installation of a high-performant driving simulator, which shall be connected to existing testbeds (e.g. an unique powertrain testbed in an anechoic chamber (DIN45635), existing HVAC test cells, and existing ADAS/AD equipment) in a modular and distributed manner, by using the recently developed real-time co-simulation approach (see Figure 1). Furthermore, gathered measurement data is panned to be made available for cross-domain system investigations. This will enable massive interdisciplinary research and provide significantly increased innovation capacity.

VIRTUAL VEHICLE has been exploring the modular, interdisciplinary engineering of complex systems since its founding in 2002. With its early research focus on co-simulation, simulation models and realtime systems (e.g. testbeds) were integrated via patented coupling algorithms, which have enabled outstanding virtual and real subsystem integration possibilities. These prominent research results were fed into the commercial co-simulation Platform AVL Model.CONNECT(TM), thereby creating a solid foundation for subsystem integration and the operation of the envisioned OPEN.CONNECTED.TESTBED. This will ensure a precise simultaneous interoperation of real test beds and various virtual testbeds (simulation tools), right up to the real-time-capable “Hardware-in-the Loop” systems.

Figure 2: Integration of typically separate engineering domains

Enhanced engineering

Classical automotive engineering domains include powertrain development, thermal management (including HVAC) and driver assistance systems  (ADAS). As vehicles are becoming more and more intelligent and specialized, system design and validation approaches must also be extended. Instead of covering purely virtual or real domains, the OPEN.CONNECTED.TESTBED enables flexible and virtual/real analysis. The human role is to integrate the different engineering domains, which are typically handled separately, which will significantly enhance the development of future mobility concepts. Figure 2 depicts this approach, whereby design meets real testing to provide an efficient, human-centric development at all stages of the product development cycle.

Figure 3: State-of-the-art and positioning of the OPEN.CONNECTED.TESBED

Technical framework

The core element of the OPEN.CONNECTED.TESTBED concept will be a high-performant (e.g. 9 Degrees of Freedom) driving simulator. This simulator is then planned to be connected to existing testing facilities (e.g. an engine testbed, powertrain testbed, HVAC cells, ADAS-Ford Mondeo 2.0) utilizing VIRTUAL VEHICLE’s modular co-simulation platform approach. Due to its flexible integration possibilities, the testbed will offer significant (open) extension possibilities for 3rd-party components or testing environments. A data management system featuring an Open Data Service shall extend the novel R&D testing infrastructure to make anonymized and approved measurement data available for 3rd parties. In the long term, the OPEN.CONNECTED.TESTBED will serve educational purposes, as well as the dedicated training of personnel in the use of highly innovative technologies.
Currently, there is no comparable comprehensive R&D infrastructure in Europe. Most existing driving simulators are used for design decisions and some functional testing. Thus, static or dynamic simulators (up to a full-vehicle mockup) are deployed. In contrast, as shown in Figure 3, the OPEN.CONNECTED.TESTBED enables a smooth transition from pure virtual to real testing, covering human-centric aspects during all system development stages. Due to this novel cross-domain system engineering possibilities from virtual design to real testing, significant improvements human-centric system design, Automated Driving and Data Analytics are expected on short term.

Conclusion and outlook

The OPEN.CONNECTED.TESTBED will represent a unique R&D infrastructure that bridges system design and validation. Prominent, highly-innovative research outcomes can be achieved in interdisciplinary and virtual/real environments, thereby fostering technology awareness and thus rapid market uptakes. Furthermore, the OPEN.CONNECTED.TESTBED will serve as a centre for collaboration by bringing together academic and industrial partners. The primary use is within funded national and pan-European research projects in the form of fast-track (up to 5 month) and lighthouse experiments (up to 3 years). Beyond the non-funded and co-financing partners, more than 14 potential users have already expressed a strong interest in the unique
OPEN.CONNECTED.TESTBED R&D Infrastructure, which highlights the strong demand and potential innovation capacity.