EEmotion project: ZF and Infineon develop AI algorithms

Automated driving EEmotion project: ZF and Infineon develop AI algorithms

2024-09-17 Source: Press release | Translated by AI 2 min Reading Time

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In automated driving, all vehicle movements must be calculated and executed precisely and quickly without a human driver. Thanks to software and AI algorithms, the drive, brakes, front and rear wheel steering and damping systems are controlled safely. The more efficient the AI algorithms are, the better the computing power can be used.

ZF and Infineon have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the publicly funded EEmotion project.(Image: ZF Group) — ZF and Infineon have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the publicly funded EEmotion project.
(Image: ZF Group)

As part of the "EEmotion" project, ZF and Infineon Technologies have jointly developed and implemented AI algorithms for the development and control of vehicle software. The AI algorithms developed in the project and tested in a test vehicle control all actuators during automated driving according to the specified driving trajectory and improve them.

More precise ADAS versions

ZF has added AI algorithms to its existing cubiX and Eco Control 4 ACC software solutions, which have been implemented on Infineon's Aurix TC4x microcontroller (MCU) with integrated parallel processing unit (PPU). The result: the artificial intelligence algorithms become more efficient and the computing power is better utilized. This in turn leads to better driving performance and greater driving safety. Compared to approaches without artificial intelligence, the partners have 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 paves the way for cost-efficient Level 2+ assistance systems.

Software-controlled chassis control optimized—thanks to AI

The cubiX software from the automotive supplier from Friedrichshafen enables the control of all chassis components in passenger cars and commercial vehicles. This includes the longitudinal and lateral dynamics as well as the vertical dynamics of the vehicle. In addition, the predictive cruise control system "Eco Control 4 ACC" is being further developed with a computationally intensive optimization algorithm and model-predictive control in order to achieve up to 8 percent more range in real driving conditions. AI algorithms were also developed in the EEmotion project, which are already applied during the development phase. This allows vehicle software to be designed more efficiently and made available more quickly.

Powerful microcontrollers required

Lean, AI-based algorithms require a lot of computing power; it is therefore advisable to integrate them into powerful microcontrollers. The Aurix TC4x microcontrollers from the Neubiberg/Germany-based semiconductor manufacturer implement topics such as AI modelling, virtualization, safety, cybersecurity and network functions. An important part of the MCUs is the Parallel Processing Unit (PPU), which enables powerful AI applications thanks to its fast and parallel data processing.

What does the EEmotion project involve?

The EEmotion project aimed to develop a control system for automated driving that is based on AI algorithms and 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 the development of the integration of AI in control architectures for safety-critical applications. In addition, aspects such as the development of secure AI-monitored communication and the investigation of the simulative development and validation of vehicle dynamics systems were taken into account. Infineon Technologies acted as joint coordinator for the project. The project ran from September 2021 to August 2024 and included partnerships with ZF Friedrichshafen, b-plus technologies, samoconsult, the Technical University RWTH Aachen and the University of Lübeck - all based in Germany. (se)

Opsys Tech intends to enhance sensor technology's performance and cost-effectiveness with its compact solid-state lidar sensors, thereby giving automated environment recognition a renewed push. (Image:Opsys)

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