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Managing Automated Vehicles Enhances Network

Objective

Highly automated vehicles and cooperative ITS technology will get more and more present in the near future. By combining both, guidance of (groups of) such vehicles can considerably improve especially in urban areas. For management of automated vehicles at signalized intersection and corridors, the MAVEN (Managing Automated Vehicles Enhances Network) project will develop infrastructure-assisted platoon organization and negotiation algorithms. These extend and connect vehicle systems for trajectory and maneuver planning and infrastructure systems for adaptive traffic light optimization. Traffic lights adapting their signal timing to facilitate the movement of organized platoons and reversely will yield substantial better utilization of infrastructure capacity, reduction of vehicle delay and reduction of emission. The MAVEN project will build a system prototype for both field tests and extensive modeling for impact assessment, contribute to the development of enabling technologies such as communication standards and high-precision maps, and develop ADAS techniques for inclusion of vulnerable road users. Additionally, MAVEN will include a user assessment and the development of a roadmap for the introduction of vehicle-road automation to support road authorities in understanding changes in their role and the tasks of traffic management systems. Finally, MAVEN will white paper on ‘management of automated vehicles in a smart city environment’ will be written to position the MAVEN results in the broader perspective of passenger transport in smart / future cities and to embed them with smart city principles and technologies as well as service delivery.

Call for proposal

H2020-MG-2014-2015

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Sub call

H2020-MG-2015_TwoStages

Coordinator

DEUTSCHES ZENTRUM FUR LUFT - UND RAUMFAHRT EV
Net EU contribution
€ 840 098,74
Address
LINDER HOHE
51147 Koln
Germany

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Region
Nordrhein-Westfalen Köln Köln, Kreisfreie Stadt
Activity type
Research Organisations
Links
Total cost
€ 840 098,74

Participants (11)