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Journal of Advanced Transportation
Volume 2018, Article ID 2586520, 32 pages
Research Article

A Rapid Prototyping Environment for Cooperative Advanced Driver Assistance Systems

1Daimler Center for Automotive IT Innovations, Technical University of Berlin, Berlin, Germany
2Fraunhofer Institute for Open Communication Systems (FOKUS), Berlin, Germany

Correspondence should be addressed to Kay Massow; ed.refohnuarf.sukof@wossam.yak

Received 26 August 2017; Accepted 11 December 2017; Published 20 March 2018

Academic Editor: Yuchuan Du

Copyright © 2018 Kay Massow and Ilja Radusch. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Advanced Driver Assistance Systems (ADAS) were strong innovation drivers in recent years, towards the enhancement of traffic safety and efficiency. Today’s ADAS adopt an autonomous approach with all instrumentation and intelligence on board of one vehicle. However, to further enhance their benefit, ADAS need to cooperate in the future, using communication technologies. The resulting combination of vehicle automation and cooperation, for instance, enables solving hazardous situations by a coordinated safety intervention on multiple vehicles at the same point in time. Since the complexity of such cooperative ADAS grows with each vehicle involved, very large parameter spaces need to be regarded during their development, which necessitate novel development approaches. In this paper, we present an environment for rapidly prototyping cooperative ADAS based on vehicle simulation. Its underlying approach is either to bring ideas for cooperative ADAS through the prototyping stage towards plausible candidates for further development or to discard them as quickly as possible. This is enabled by an iterative process of refining and assessment. We reconcile the aspects of automation and cooperation in simulation by a tradeoff between precision and scalability. Reducing precise mapping of vehicle dynamics below the limits of driving dynamics enables simulating multiple vehicles at the same time. In order to validate this precision, we also present a method to validate the vehicle dynamics in simulation against real world vehicles.