For OEM, suppliers and developers, automation of vehicles brings with it a wealth of new tasks. At the same time, the classic functions and purchasing criteria fall ever further into the background. As a service provider, FEV supports its clients from the initial concept to start of production in its decision processes associated with these new subjects.
Since 2016, FEV has been bundling all of the steps associated with advanced, fully connected, automated vehicles in its "Smart Vehicle" Center of Excellence. Smart Vehicle includes all sorts of development fields in a rapidly-changing, highly complex environment – from sensor technologies to software algorithms all the way to electrical/electronic architectures and connectivity.
With our FEV smart vehicle fleet we have launched an important demonstration and development tool.
Sensor fusion: Key element for vehicle environment detection and localization
We have integrated extensive sensors, including radar, GPS, different types of cameras as well as differential GPS and LIDAR and a vehicle-2-network connection. Thanks to these sensors and interfaces, we are able to perceive the immediate environment of the vehicle as well as to anticipate the oncoming road and traffic conditions on a longer range. Using intentional redundancies in varying technologies, we can thus eliminate the shortcomings of one type of sensor by enriching and comparing the results using those from other systems.
FEV's decision making algorithm manages driving commands
The driving commands are managed using a "decision making algorithm" we developed ourselves. This algorithm has three main parts: perception, planning and decision/action. As a modular development platform, the vehicle is actually equipped with two types of powerful embedded controller hardware. This allows us to test and compare different types of control algorithms, for example a rule based approach and a machine learning/artificial intelligence approach.
Communication between the vehicle and its environment is mandatory for automated vehicles. Even today, the vehicles already have a Vehicle-to-Everything ("V2X") connection. The intelligent connection unit – abbreviated as iCU – is based on microservice architecture and processes data and information from all sorts of control units and sensors. The FEV iCU is in a position to process data from vehicle-to-vehicle ("V2V") communication via DSRC. Thanks to the microservice architecture, integration of corresponding 5G standards ("C-V2X") will be possible directly, as soon as they are available. Intermediate data aggregation and data conversion services harmonize the data sets and formats, which often differ a lot from each other.
Cybersecurity in vehicles is actually one of the greatest challenges. The biggest danger comes from the OBD interface but also from the infotainment system. As soon as the vehicle starts working within a network, the sources of danger grow exponentially. With our Cyber Security Gateway, we offer an important tool to prevent cyberattacks. In addition, FEV works with leading world manufacturers to implement so called Hardware Security Module –HSM- and TPM technologies, known as Trusted Platform Modules, for the automotive industry for secure booting and secure over the air software (OTA) updates to name a few applications.
A powerful tool
As a powerful tool to address important challenges such as integration of new functions, interfaces, and components, the FEV smart vehicles offer a broad range of possibilities for FEV as well as for our partners and customers. As a flexible platform, they have an important role in the development and improvement of our control algorithms. They enable our engineers to make their innovations in ADAS and automated driving features more tangible. This flexible platform can obviously also be offered to our partners and customers as basis for commonly developed "Proof of Concepts" to demonstrate new technologies or features for example.
For sensor benchmarking as well as for system and overall vehicle benchmarking, the most important part is reproducibility of results and test runs, and automation is very important for that. In this case, our smart vehicle is not the technology platform for the test vehicle but is acting as the testing tool. Driving maneuvers of the target vehicle can be automated and done reproducibly and it can be verified that the test object operates reliably.