AI-enabled Intelligent Traffic Systems (ITS)
Together with the Huawei Research Center Munich, the Fraunhofer Institute for Cognitive Systems IKS has written a white paper on Artificial Intelligence (AI) for Intelligent Transport Systems (ITS).
AI-enabled Intelligent Traffic Systems (ITS) offer the potential to greatly improve the efficiency of traffic flow in inner cities resulting in shorter travel times, increased fuel efficiency and reduction in harmful emissions. These systems make use of data collected in real-time across different locations in order to adapt signaling infrastructure (such as traffic lights and lane signals) based on a set of optimized algorithms. Consequences of failures in such systems can range from increased congestion and the associated rise in traffic accidents to increased vehicle emissions over time.
Challenges of introducing AI into ITS
This white paper summarizes the results of a roundtable event between safety, mobility and smart city experts and addresses the following questions:
- How does the use of AI fundamentally change our understanding of safety and risk related to such systems?
- Which challenges are introduced when using AI for decision making functions in Smart Cities and Intelligent Traffic Systems?
- How should these challenges be addressed in future?
Based on these discussions, the white paper summarizes current and future challenges of introducing AI into Intelligent Traffic Systems in a trustworthy manner. Here, special focus is laid on the complex, heterogeneous, multi-disciplinary nature of ITS in Smart Cities.