Complexity Economics Engineering Society

Systemic Impacts on Automated Traffic from Quantitative Complexity Rating

25th ITS World Congress, Copenhagen, Denmark, 17-21 September 2018
Paper ID EU-TP1627, by Walter Aigner, Andreas Kuhn, Jacek Marczyk

Abstract
While connected and automated driving has seen broad attention in the ITS community, automation of processes in traffic management has not yet been studied widely. A new and revolutionary approach to analysis and automation of traffic management processes comes from the field of Quantitative Complexity Management. We here introduce approaches and an outline how traffic management will see entirely new ways of coping with semi automated driving and growing traffic by explicitly assessing the complexity of traffic. This approach, in turn, makes dealing with complexity as a design parameter a real possibility that opens the door to many exciting use cases. Managing complexity at a design level may well be a key to intelligent traffic management and to effectively taking advantage of the improvement opportunities expected from traffic automation. The necessity for traffic automation is partly driven by automated and connected drivi ng coming to market.

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Established originally in 2005 in the USA, Ontonix is a technology company headquartered in Como, Italy. The unusual technology and solutions developed by Ontonix focus on countering what most threatens safety, advanced products, critical infrastructures, or IT network security - the rapid growth of complexity. In 2007 the company received recognition by being selected as Gartner's Cool Vendor. What makes Ontonix different from all those companies and research centers who claim to manage complexity is that we have a complexity metric. This means that we MEASURE complexity. We detect anomalies in complex defense systems without using Machine Learning for one very good reason: our clients don’t have the luxury of multiple examples of failures necessary to teach software to recognize them. We identify anomalies without having seen them before. Sometimes, you must get it right the first and only time!

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