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Study of Sustainable Value in Automobile Manufacturing Finds Mixed Performance for Most OEMs, BMW and Toyota as the Clear Leaders

Green Car Congress

Frank Figge of Queen’s University Belfast and Dr. Tobias Hahn of Euromed Management School Marseille. The research project was undertaken by researchers working at Euromed Management School Marseille, Queen’s University Belfast and IZT—Institute for Futures Studies and Technology Assessment in Berlin. Click to enlarge.

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European consortium launches 4-year, $80M L3Pilot research project to test Level 3, 4 autonomous driving in 11 countries

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Thirteen European automobile manufacturers, suppliers, research institutes and universities, and small and mid-sized companies will operate 100 vehicles with 1,000 drivers under real conditions and in a wide range of applications. Suppliers: Autoliv, Delphi Deutschland GmbH, FEV Group GmbH.

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Potsdam/TUB/BMW report says cap-and-trade instrument for road transport fuels combined with vehicle efficiency metrics is the most promising policy approach to reduce transport GHG

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tank-to-wheel-based fuel efficiency metrics, is the most promising policy option for future climate policy regulation of the road transport sector, according to a new study developed under the direction of Professor Ottmar Edenhofer of the Potsdam Institute for Climate Impact Research (PIK). Automobile manufacturers have no influence on that.

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Japanese carmakers still ‘most sustainable’

Green Cars News

A focus on tailpipe CO2 emissions has distracted away from the impact of car production, suggests Professor Frank Figge who co-authored the ‘Sustainable Value in Automobile Manufacturing’ study. Tags: Green credentials car production Queen's University study sustainble. The survey attempts to close this gap.”.

Sodium 36
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New Audi A8 debuting Level 3 autonomous AI traffic jam pilot; parking and remote garage pilots; zFAS controller

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Audi will be the first automobile manufacturer to bundle these in a central domain architecture. Its modular concept makes the zFAS flexibly scalable and thus future-proof. In intelligent and piloted vehicles, there will be numerous use cases for machine learning in the future. Sensors and cameras, with zFAS.

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