Research Project “Age-Appropriate Behavior”

We are collaborating with Continental to explore the concept of “level-appropriate behavior.” Identifying and monitoring safety-critical situations poses challenges for drivers, especially when there are frequent transitions between fully automated, partially automated, and manual driving.

The goal is to clearly show drivers which level of automation they are currently in and how they should respond. To this end, we are developing a virtual co-pilot that explains the test scenario, answers questions, and is available throughout the drive. Our AI provides support, particularly when switching between autonomous driving levels. 

KARLI Research Project: "Motion Sickness" Subproject

Together with the Ford Motor Company, we are investigating the topic of “motion sickness.” This term refers to a condition that most people have experienced firsthand: nausea, dizziness, or headaches. The effect is particularly pronounced when reading in a car, as this causes a significant discrepancy between the sense of balance and visual perception. Motion sickness is more likely to occur in an automated vehicle. The goal is therefore to develop AI algorithms and HMI (human-machine interface) systems capable of recognizing motion sickness in specific situations and reducing or even preventing its occurrence.

For research purposes, we developed both the voice prompts and several visual elements. Here, test drivers are encouraged to perform various driving maneuvers or respond to different situations—for example, by looking out the window, reading something, and reporting how they feel. Our voice assistant SUSI interacts with the test drivers at regular intervals to determine their motion sickness level. The test results are then analyzed and provide insights into factors such as the effects of the surrounding environment.

KARLI Mid-Year Presentation 2023

Experience research firsthand! SUSI&James attended the KARLI Project midterm presentation at Continental’s Zukunftswerkstatt in Frankfurt. Our voice-based applications were also on display there as part of the AI solutions developed by our partners Ford Motor Company, Continental, and the University of Stuttgart.

The KARLI project consists of eight subprojects, three of which are supported by our technology in the research phase. The latest interim results on the topics of “level-compliant behavior,” “AI interaction,” and “motion sickness” were presented in technical talks and could also be experienced firsthand in the test vehicles.

Intelligent driving of the future requires the development of AI systems capable of triggering in-vehicle interactions that are tailored to the individual and the context, thereby helping to ensure a safe and comfortable ride. 

It was exciting to experience the systems and voice interactions firsthand in test vehicles and try them out for ourselves. We also had the opportunity to meet familiar faces and discuss their projects, visions, and goals with stakeholders and decision-makers. Networking with others is very valuable to us.

We are excited to be working with KARLI to help shape the future of driving.

Three months after the official end of the pandemic: Marcel Martini looks back on the time of masks, social distancing, and hygiene guidelines

[Question] Marcel, you joined SUSI&James as managing director in early 2021. What was your daily routine like back then?

Marcel: I know that there was short-time work in 2020. The slump in orders was clearly noticeable, ultimately, of course, due to the extremely difficult situation our customers were facing—for example, because of production stoppages or the breakdown of supply chains. Today, however, it’s clear that the pandemic has very clearly demonstrated the need for a digital transformation of business processes, which has naturally helped us.

In addition, the pandemic has led companies to become more cost-conscious. While this naturally makes investing more challenging in general, when a quick return on investment is expected—as is the case with our solutions—I find our customers to be very receptive. Furthermore, flexible licensing models tailored to specific use cases provide additional flexibility.

[Question] Has the pandemic changed the business model?

Marcel: Generally speaking, no. I believe that customers have become much more receptive and open to topics related to digitalization, process acceleration, efficiency improvements, and so on. And that is exactly what we Leistungsversprechen.

However, as awareness has grown, a certain degree of willingness to take risks has been lost. These days, before actual development can begin, we must at least demonstrate the immediate value of a project through a “proof of concept.” This is understandable, of course, but it can sometimes slow down the process.

[Question] How has the way we interact with companies, prospective clients, and customers changed?

Marcel: Most people are working from home these days. That makes it a bit harder to reach them than before. But a bigger challenge for us is that it’s difficult to build a personal relationship of trust without face-to-face contact. After all, we’re deeply involved in business processes, which requires a high level of trust.

Building trust used to be much easier, since we would often talk face-to-face, have coffee together, or drop by a client’s office on the spur of the moment. These days, meetings tend to take place via Teams, Zoom, or the phone, or we exchange brief messages via email. While this certainly has major advantages, it poses a certain obstacle when it comes to building relationships and networking. This makes networking events, trade shows, and similar formats all the more important.

[Question] Our Smart Office product was developed not too long ago. To what extent did the pandemic and the need for digitalization contribute to its development?

Marcel: While the pandemic and the resulting pressure to digitize have accelerated the development of the smart office, our solution is ultimately the logical answer to common market challenges: poor telephone accessibility, a shortage of skilled workers, inefficient processes, and so on. I can’t say for certain whether the pandemic was the decisive factor, but it certainly played a part.

[Question] Is it harder to sell the product these days?

Marcel: Not necessarily harder, but different. The sales channels have simply changed. The challenge lies in identifying the target audience’s needs and determining the best way to address them. The initial contact is often made via email, LinkedIn, or even cold calling. Before the pandemic, in-person networking played a bigger role.

That makes it all the more enjoyable to meet people at events, get to know one another, and exchange ideas. The last such event we attended was the Partner Networking Event  the Future Workshop 4.0.

[Question] Has end-user acceptance of AI solutions changed?

Marcel: Es gibt Studien, die zeigen, dass immer mehr Menschen offener gegenüber neuen Technologien sind. Ob das der Pandemie zuzuschreiben ist, wage ich zu bezweifeln. Generell steigt die Akzeptanz gegenüber neuen Technologien stetig, auch durch die derzeitige starke mediale Präsenz. Gleichzeitig gibt es natürlich auch eine gewisse Skepsis bzgl. Kundenzufriedenheit, Nutzerfreudlichkeit, Datensicherheit, etc.  Wir legen jedoch extrem viel Wert auf diese Themen, eine positive User-Experience zu erzeugen ist Kern unserer DNA. Das spiegeln uns auch unsere Kunden wider, was uns sehr freut. Die Endkunden kommen mit der Geschwindigkeit, in der SUSI speaks , they get along very well. This is especially important when older people call.

[Question] What is the current pace of project and product implementation?

Marcel: My impression is that decision-making processes on certain issues have slowed down again, which is understandable, however, because the pressure to implement changes has eased. During the pandemic, for example, companies had no choice but to offer their employees the option to work remotely and to put the necessary infrastructure in place.

There is a fundamental need for and understanding of the necessity of ongoing digital transformation, though not at the same pace as three years ago. At the same time, this gives us the opportunity to work with our customers to identify their requirements in detail and tailor our products and solutions accordingly.

Natural Language Understanding (NLU)

With NLU, data can be analyzed and its meaning determined by algorithms by reducing human language to a structured ontology—a data model consisting of semantic and pragmatic definitions. The two fundamental concepts of NLU are intent recognition and entity recognition.

Artificial Intelligence (AI)

Simply put, artificial intelligence (AI) is the ability of a computer or machine to mimic the capabilities of the human mind. It learns from past experiences to understand language, make decisions, and solve problems, and to respond accordingly.

Large amounts of data are often used to train AI and develop algorithms that enable these capabilities. Various AI capabilities, such as computer vision and user interfaces, are integrated into many standard business processes across industries such as retail, finance, healthcare, and high-tech.

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