The performed work can be summarized as follows:
Objective A: to use emotion3D’s 3D human sensing methods and software and adapt it to the restraint control case:
emotion3D in close collaboration with the consortium members was working towards adapting existing 3D human sensing software. The software was adapted in such a way that Veoneer’s Time of Flight (ToF) camera could be used as an input for the algorithms and provides all the relevant output needed for controlling the RCS. After the first reporting period, a first version of the software was available. This version could already process the output generated by Veoneer’s ToF camera and does already provide meaningful output data. Veoneer's ToF camera was then further developed to obtain a prototype B, which has a smaller form factor and more precise measurements. At the end of the project, an optimized software in terms of accuracy and runtime is available, which also supports the optimized ToF.
Objective B: to integrate this new software in Veoneer’s RCS:
After adaption of emotion3D’s software framework, the software was ported onto Veoneer’s processing platform. First, prototype A was used and then the software was also ported on prototype B.
Objective C: to test and validate this system using profound testing expertise from AVL:
For setting up a testing and validation strategy, capturing massive amounts of data is needed. This data should be complete, precise, and reproducible, it should be representative in terms of test-persons, test-vehicles and test-scenarios, efficiently acquired and in compliance with GDPR. The objective was therefore – in collaboration with all consortium members – to define the relevant data to be acquired for the development, verification, and validation of the algorithms & systems. AVL has developed a central data acquisition system to acquire data from all sources and to ensure the synchronization of the same in all test environments. An additional, camera-based ground-truth system has been integrated in the data acquisition system. Furthermore, virtual test-scenarios were created to be executed on the dynamic Driver-in-the-Loop simulator at AVL and ensure reproducible and comparable data. A workflow was defined and is continuously improved, to efficiently execute the test scenarios in all environments. To validate and improve the increased safety of the Smart-RCS, a virtual crash-simulation was set up which will compare the injury severity of traditional restraint control systems vs. Smart RCS in various parameterizations.
Objective D: to contribute to testing & safety standards
On the one hand, testing procedures were developed that will represent a starting point for official testing protocols. On the other hand, regulators and safety organisations must be made aware of the safety benefits smart-RCS provides. Thus, we were engaging in discussions with several of such organisations. Also, we have compiled an advisory board consisting of top-level academia, Tier-1, OEM and regulatory representatives. At the end of the project, we had some recommendations and findings available, which we would also like to share with potential customers after the end of the project.
Objective E: to pave the way to bring the new personalized RCS to the automotive market
To date, we have set numerous general communication activities and engaged intensively with potential customers. The feedback from key stakeholders of the industry has been tremendously positive and there is strong interest from potential customers to start proof of concept development projects. We are on a good way to successfully bring Smart-RCS to the automotive market.
Exploitation:
The consortium developed a demonstrator that was shown to several OEMs over the course of this project. The demonstrator will also be used beyond the scope and after finishing the project.
Dissemination:
We published 2 publications at peer-reviewed conferences.
