Jointly researching AI for automated driving in cities

July 01, 2020 //By Julien Happich
AI for automated driving
Continental continues its long-standing PRORETA research cooperation with international universities under the slogan "urbAn drIving".

By the end of 2022, algorithms based on artificial intelligence (AI) should be developed and tested for the entire chain of effects of automated driving. Enhanced interdisciplinary and inter-university collaboration covers the entire range of technology for the relevant functional steps of automation.

Together with Technical University (TU) Darmstadt, the University of Bremen (Germany) and TU Iaşi (Romania), technology company Continental is continuing the series of its PRORETA research projects. PRORETA 5 is dedicated to one of the most challenging tasks for automated driving: recognizing complex traffic situations in inner cities and how algorithms from sensor data can deduce the correct driving decisions in these situations. At an unregulated intersection, for example, it is a challenge to correctly interpret all objects related to the intended direction of travel – including their direction of movement, intention and priority – without human intervention. Artificial Intelligence (AI) plays a key role in this. AI methods are to be tested when the implementation of traditional approaches becomes too complex or reaches its limits. The main advantage of AI is that, following a training period, it is able to draw its own correct conclusions based on its learning, even in unknown situations. This element is reflected in the slogan “urbAn drIving.”

The PRORETA 5 project (2019–2022), based on a three-and-a-half-year term, is examining the algorithms of cognition, behaviour prediction and decision making in a demonstration vehicle built and equipped by Continental. At the end of the project in September 2022, the aim is to assess the performance of the new AI-based automation for the Society of Automotive Engineers (SAE) Level 4, using the widest possible range of inner-city scenarios and thus demonstrate the potential for future deployment.


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