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AI Opportunities in Mobility & Transport

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AI Opportunities in Mobility & Transport
Andreas Metzger (Head of Adaptive Systems and Big Data Applications, Paluno)

Publicado en: Datos y análisis
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AI Opportunities in Mobility & Transport

  1. 1. AI Opportunities in Mobility & Transport Andreas Metzger paluno (The Ruhr Institute for Software Technology)
  2. 2. Transport Market Shape and Opportunity Annual growth rates (EU-28, 2016) • Passenger transport: 3.2% • Freight transport: 4.5% Turnover (EU-28, 2015) • 1,491 Billion EUR Key EU sector • E.g., see EC’s Communication on ‘Artificial Intelligence for Europe’ Profit margins via AI • > 5% reported by early adopters of AI [McKinsey] EBDVF 2019, Helsinki [EU Transport in Figures – Statistical Pocketbook 2018]
  3. 3. Main Potential for AI in Mobility & Transport Improved decision making • Deep Learning High accuracy descriptive and predictive analytics • Explainable AI Enhanced decision support Autonomic enactment • Reinforcement Learning Solving complex planning and decision problems • Actuation Seamless physical and human action and interaction EBDVF 2019, Helsinki  (Self-)managing Operations and Processes!
  4. 4. TransformingTransport: Data-driven AI Pilots EBDVF 2019, Helsinki New Business Models Improved Operational Efficiency Better Customer Experience Data-driven decision making in retailing Real-time incident warnings Proactive terminal management Dwell time Shopping probability Dwell time frequency New Business Models Improved Operational Efficiency Better Customer Experience New Business Models Improved Operational Efficiency Better Customer Experience New Business Models Improved Operational Efficiency Better Customer Experience New Business Models Improved Operational Efficiency Better Customer Experience New Business Models Improved Operational Efficiency Better Customer Experience 0,00000 0,10000 0,20000 0,30000 0,40000 0,50000 0,60000 0,70000 1 2 3 4 5 6 7 8 9 10 Diagrammtitel Datenreihen1 Datenreihen2 Datenreihen3 Datenreihen4 MLP RNN Process Duration Accuracy [MCC] Time Accuracy
  5. 5. But also Challenges! Software quality of AI-based systems • AI software testing and verification How to handle (unprecedented levels of) non-determinism in software? • Governance of self-learning software How to “control” the quality of continuously learning systems? • Vulnerability detection and analysis How to cope with AI as an additional attack surface (adversarial input)? Skill pipeline • Must cover industry professionals as well as researchers • How to keep abreast of latest developments of advanced AI technologies? e.g., over 16,000 papers on deep learning indexed By DBLP EBDVF 2019, Helsinki
  6. 6. Thanks EBDVF 2019, Helsinki AI Research leading to these results has received funding from the EU’s Horizon 2020 research and innovation programme under grant agreements no. 731932 – http://www.transformingtransport.eu 732630 – http://www.big-data-value.eu

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