Digital engineering for software and systems in the automotive industry
fortiss is shaping the future of automotive software technology, transforming tomorrow's mobility into a safer, smarter, and more efficient experience. We achieve this by supporting our partners with cutting-edge scientific insights and reliable engineering expertise. As an innovation hub for the automotive industry, fortiss delivers efficient, well-founded solutions that meet today’s demanding software development needs.
Our agile approach bridges the gap between rigorous scientific research and the fast-paced demands of the market. In an industry often constrained by budgets and resources, fortiss provides state-of-the-art R&D capabilities that many companies would otherwise struggle to achieve on their own.
fortiss provides scientifically elaborated potential analyses and specialist studies in the fields of AI, Industry 4.0, autonomous driving and cognitive systems specially tailored to the requirements of the automotive industry. In company-specific workshops, we work out your individual challenges and requirements, analyse the problems, identify possible causes and solutions and develop optimization options to tap into the untapped potential of your organizations. The results can serve as a basis for the development of concrete prototypes or for the establishment of cooperation projects.
With the quick fortiss Quick-Checks, fortiss offers small and medium-sized companies in the automotive industry application-oriented online tools for the initial analysis of internal software development processes. This includes feasibility analyses and adaptation of specific methods to the respective task.
fortiss is a reliable technological and manufacturer-independent partner for companies in the automotive industry that want to implement innovative digital processes, products or services in pilot projects. Depending on the scope of the project, the institute develops initial concepts through to pre-competitive software solutions (TR level 6), which are evaluated in industrial environments.
The fortiss experts design and implement projects together with industrial partners and within the framework of public funding, whether in bilateral cooperation or in larger consortia. We support your company competently on the way to a collaborative research project and analyze your questions and challenges.
In introductory workshops, we identify suitable cooperation and funding opportunities, provide technical and administrative support when submitting joint project applications and offer state-of-the-art research in the field of software and AI.
fortiss takes on software engineering based on specific simulation environments and offers a wide range of options for exploring, testing and evaluating new solutions for software-intensive systems. As a partner, you can access the know-how of experienced experts to jointly develop solutions for challenges in the automotive environment.
The fortiss service includes:
The fortiss Labs offer companies their own premises in which partners from research and industry can interact using existing or newly developed demonstrators. Here, platforms, simulation environments and software tools are available, while the fortiss Mobility Lab enables the practical testing of technologies using realistic automotive use cases with fortiss open source solutions. As a central engine for research, fortiss uses its extensive expertise in the automotive industry and first-class infrastructure to apply the latest research results, identify potential for improvement through testing and initiate new research projects.
The labs are located on the 15th floor of the Highlight Towers Munich and comprise a test area for Industrial IoT (IloT), mobility, robotics, energy and neuromorphic computing. Here, central questions of the automotive industry are analyzed and modern research methods are combined in an interdisciplinary way, while technologies are tested under real conditions and the results are prepared as prototypes for practical application.
With the “fortuna” research car and a small-scale vehicle, fortiss carries out tests on cooperative driving, among other things, and implements scientific findings directly in the automotive industry.
The tailor-made training and further education offers for companies in the automotive industry include practice-oriented training courses, workshops and lectures on current topics. Experts impart both theoretical knowledge and practical skills, the combination of which is crucial for the successful implementation of innovative software solutions.
The training courses cover specific methods and tools and demonstrate the potential of new software technologies and their practical application in the automotive sector. In addition, we offer customized training courses that enable teams to acquire the necessary knowledge and skills for specific challenges, including Model-based Systems Engineering basics and advanced topics.
Specifically for the needs of the automotive sector, we offer the following training courses:
We offer these and many other topics both in-house and at your premises. Talk to us about your topics.
Do you have a question about our services, are you looking for an innovative solution in the field of automotive software or do you already have specific ideas?
Our automotive software research focuses on key areas such as developing reliable autonomous driving functions and connected mobility services. We also design safe, intuitive human-machine interfaces for vehicle environments and advance digitalization and automation to enhance automotive production efficiency. By leveraging state-of-the-art technologies and algorithms, we integrate artificial intelligence and machine learning to create innovative, sustainable solutions for the future of mobility.
The development of safe autonomous driving functions is powered by the integration of advanced algorithms and AI in the software. By combining expertise from multiple research fields, we enable vehicles to achieve exceptional navigation, decision-making, and responsiveness in complex traffic situations. This enhances not only the safety but also the efficiency and reliability of autonomous driving systems.
Comprehensive coverage of all phases of system development, from requirements and modeling to implementation and testing, to meet the stringent safety standards of the automotive industry.
Systematic management and handling of complex software variants and configurations, ensuring an efficient and cost-effective development process through reuse and modularity in design.
Development of AI-based assistance systems to enhance driver support and improve road safety.
Integration of sensor data into a unified real-time environment model to support driving decisions through sensor and data fusion. Development of advanced systems using neural networks to enhance vehicle safety and intelligence.
Analysis of the environment to derive driving decisions based on traffic conditions, regulations, and safety considerations.
Prediction of maintenance needs for vehicles and infrastructure components to prevent breakdowns and traffic disruptions, ensuring overall safety.
Implementation of advanced systems and formal methods to ensure the reliability and safety of vehicle technologies through rigorous testing and validation procedures. This includes automated and continuous verification, validation, and certification of safety-critical and autonomous systems, adhering to development and certification standards to guarantee the safety, reliability, and integrity of software and AI components.
Securing control units, communication systems, and data to ensure data security and protect against manipulation.
Intelligent networking through vehicle-to-everything (V2X) technology allowed us to enhance communication between vehicles, infrastructure, and mobility services. This created numerous opportunities for us to significantly improve transportation infrastructure, optimize traffic flow, and introduce innovative services and applications. By leveraging our comprehensive software skills, we effectively designed and integrated these complex communication systems.
Ensuring the secure and efficient transfer and use of data between vehicles, infrastructure, and mobility services.
Facilitating the interaction of data in highly automated vehicles with intelligent infrastructure, providing value-added services based on a precise and highly available digital twin.
Linking different modes of transportation to create a seamless mobility experience, including the integration of various platforms.
Development of methods for formalizing, verifying, monitoring, and analyzing continuous usage control systems across cloud, edge, and IoT environments.
The development of modern infotainment systems is a key challenge in the automotive industry. Expertise in human-centered software development is essential to create user-friendly and efficient solutions. Our goal is to design systems that are intuitive and easy to use, reducing drivers´ distractions while enhancing comfort and safety.
The digitalization of production processes creates new opportunities for optimizing efficiency, quality and safety. In the automotive industry, this enables the flexible and cost-efficient design of production facilities. At the same time, digitalization presents companies with challenges such as integrating new technologies, adapting existing systems and ensuring data security and integrity.
We use models for systematic planning, optimization, and simulation of vehicle systems and production processes.
Real-time acquisition and processing of sensor data to optimize production control.
Creation of virtual models and simulations of production systems and processes to optimize production.
Synthesis of plant architectures and production plans for flexible and individualized production with digital twins and model-based systems engineering.
Autonomous production of multi-variant configurations for the automatic configuration of production systems for individualized one-off productions.
Creation of complex scenario-based tests using advanced algorithms, machine learning and model-based techniques to dynamically generate comprehensive production test cases.
The course offers a practical insight into model-based systems engineering (MBSE). Using an end-to-end open source application example from the automotive industry, it shows how abstraction in models can be used to overcome the complexity in the development of safety-critical systems.
