Improved driving performance combined with lower computing power demands paves the way for cost-efficient Level 2+ assistance systems. Compared to conventional approaches without AI, the two companies have now proven that their solution can carry out automated lane changes much more accurately and increase the energy efficiency of driver assistance systems.
13 Sep 2024 | 2206 Views | By Autocar Professional Bureau
The ZF Group and Infineon Technologies AG have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the EEmotion project. The project was co-funded by the German Federal Ministry for Economic Affairs and Climate Action. The AI algorithms developed in the project, ...
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The ZF Group and Infineon Technologies AG have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the EEmotion project. The project was co-funded by the German Federal Ministry for Economic Affairs and Climate Action. The AI algorithms developed in the project, proven in a test vehicle, control and optimize all actuators during automated driving according to the specified driving trajectory.
The EEmotion project's objective was to develop an AI algorithm-based control system for automated driving that ensures more precise trajectory control in various driving situations. The implementation of the project included the definition of the requirements for the AI-based functions, the development of an overall concept and corresponding hardware as well as developing the integration of AI in control architectures for safety-critical applications.
ZF has added AI algorithms to its two existing software solutions cubiX and Eco Control 4 ACC, which have been implemented on Infineon’s AURIX TC4x microcontroller (MCU) with integrated Parallel Processing Unit (PPU). The result: More efficient artificial intelligence algorithms and better utilization of computing power. This in turn leads to better driving performance and increased driving safety. Compared to conventional approaches without AI, the two companies have now proven that their solution can for example carry out automated lane changes much more accurately. The energy efficiency of driver assistance systems such as Adaptive Cruise Control has also been increased. The improved driving performance combined with lower computing power demands paves the way for cost-efficient Level 2+ assistance systems.
The EEmotion project's objective was to develop an AI algorithm-based control system for automated driving that ensures more precise trajectory control in various driving situations.
"The EEmotion funding project shows that our artificial intelligence-based algorithms provide our customers with new advantages: AI makes it possible for products to be equipped with new functions and to be developed faster and more efficiently," said Torsten Gollewski, Head of Research and Development at ZF.
“With our world-leading semiconductor products, software and services, Infineon enables customers to develop their own AI applications,” said Peter Schiefer, President of Infineon’s Automotive Division. “Our AURIX TC4x is ideally suited for in-car AI applications because its Parallel Processing Unit enables the fast and parallel processing of data that is essential for artificial intelligence, heralding the next stages of automated and ultimately autonomous driving."
"The EEmotion project successfully integrated artificial intelligence into the safety-critical functions of the vehicle control system; this was validated on the software side, making further progress towards highly automated driving possible," said Ernst Stoeckl-Pukall, Head of the Digitization and Industry 4.0 department at the Federal Ministry for Economic Affairs and Climate Action. "The project has thus provided important impetus that has strengthened the innovative power and competitiveness of the German automotive industry."
Software-based chassis control optimized with AI
ZF's cubiX software makes it possible to control all chassis components in passenger cars and commercial vehicles. This includes longitudinal and lateral dynamics as well as the vehicle's vertical dynamics. In addition, the Eco Control 4 ACC predictive cruise control system is being further developed using a computationally intensive optimization algorithm and model-predictive control to achieve as much as 8 percent more range under real driving conditions.
The EEmotion project has also developed AI algorithms which are applied as early as during the development phase. This allows more efficient design of vehicle software which can then be made available to customers more quickly. The accelerated and AI-supported application of vehicle software offers vehicle manufacturers clear advantages when adapting to different vehicle models.
Microcontroller from Infineon enables use of AI algorithms
Lean, AI-based algorithms require a lot of computing power, which makes it advisable to integrate them into high-performance microcontrollers such as the AURIX TC4x.
Infineon states that its AURIX TC4x microcontrollers offer high real-time and implement the latest trends in AI modelling, virtualization, functional safety, cybersecurity and networking functions. They pave the way for new E/E architectures and the next generation of Software-Defined Vehicles (SDV). An important part of the AURIX TC4x is the Parallel Processing Unit, which supports powerful AI applications thanks to fast and parallel data processing.