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AI in Automated & Connected Driving

£3,259 | Buy now  This report captures the maturity of Artificial Intelligent-based automotive applications for Automated Driving in private cars and shared mobility. It also provides expert insights on strategic innovation from leading companies.


AI in Automated & Connected Driving 1

AI in Connected & Automated Driving

Artificial Intelligence is one of the key enablers for the transition from today’s driver assistance systems to self-driving chauffeurs in private cars, ride-hailing (optimization of pricing in car-sharing, robotaxis) and other use cases of Automated-Mobility-on-Demand (AMoD), such as first / last mile mobility.

This report captures the maturity of Artificial Intelligent-based automotive applications for Automated Driving in private cars and shared mobility. It also provides expert insights on strategic innovation from leading companies.

AI in Automated Driving
AI in Automated Driving

European Commission’s first attempt to regulate “high risk” AI

  • EC’s White Paper or Artificial Intelligence – A European Approach  sets guidelines to establish trust, promote AI and address high-risks AI applications
  • Proposed legal requirements for high-risk AI applications-only for the future regulatory framework include: data training and record-keeping, human oversight, information provision when interacting with an AI system, robustness and accuracy
  • EC’s approach is based on 3 pillars: being ahead of technological developments, foresee the socio-economic impact and establish an ethical and legal framework

On February 20th, European Commission President Ursula von der Leyen announced in her political Guidelines a coordinated European approach on the human and ethical implications of AI as well as a reflection on the better use of big data for innovation.

The paper is seen as the first attempt to regulate AI and forms part of the European Union’s grand plan for regulating technology over the next years. The EC points out the risks posed by AI, the existing laws that apply to AI, plus its intention to update laws to fix any gaps which may exist.

The framework would prescribe a number of mandatory legal requirements for “high risk” AI applications in order to ensure the regulatory intervention is proportionate.

EC suggests legal requirements for a future regulatory framework on high-risk AI applications only:

  1. Training AI data on accurate, representative data
  2. Keeping accurate records of the data used to train and test the AI systems, the data themselves and the programming and training methodologies
  3. Information provision to individuals so that they know when they are interacting with an AI
  4. Requiring human oversight for AI systems

The European Commission is seeking comments until 19th May 2020. Then they will start drafting legislation based on these proposals and comments at the end of 2020.

Table of contents

1. Executive Summary (5 pages) 

    1. AI penetration in ADAS in 2018-19 by application or feature & also by geography
    2. Investment in AI in AD 2016-18 & distribution by type
    3. Company initiatives & product roadmaps 2018-20
    4. Key trends in AI-AD ecosystem:
      1. How the main challenges are being addressed?
      2. Partnerships
      3. New players

2. Today’s use cases & emerging opportunities for AI in Automated Driving (20 pages)

    1. AI in perception sensors for visual recognition: front-facing camera and radar
    2. Digital maps enhanced with artificial intelligence for highly automated driving
    3. AI supercomputers/Central domain controllers from leading suppliers & carmakers
    4. AI in vehicle Actuation: Features
    5. AI & machine learning in Automated Mobility on Demand (AMoD): robotaxis & micro-mobility
      1. Robotaxis
      2. Micro-mobility
    6. Intelligent Transportation Systems

3. Roadmap & Forecast (15 pages)

    1. Product roadmap 2018-25 from carmakers, major suppliers and innovative startups
    2. Investment data: measuring the investment gap
    3. Market penetration Forecast 2018-25
    4. Market sizing: Capturing the size of the opportunity
    5. Product Benchmarking

4. 25 Major company profiles: strategy, product portfolio & roadmap (25p)

    1. Carmakers
      1. Audi: AI in zFAS, empathetic concepts
      2. BMW
      3. GM & Cruise Automation
      4. Hyundai
      5. Tesla: DNN for AI chip for Full-Self Driving & robotaxis
      6. Toyota
      7. VW
    2. Major automotive suppliers
      1. APTIV
      2. Alibaba
      3. Bosch
      4. Continental
      5. HERE
      6. Mobileye
      7. NVIDIA
      8. Valeo
      9. ZF
    3. Mobility Service providers
      1. Waymo
      2. Cruise Automation
      3. Uber
    4. Startups
      1. AEye (idar lidar)
      2. AIMotive
      3. Cognata (simulation)
      4. Metawave (Warlord radar)
      5. ai
      6. ThinCI

For more information on this report, including sample pages and a full Table of Contents, please contact us on (+44) (0)20 3286 4562.