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Today's Advanced Driver Assistance Systems (ADAS) adopt an autonomous approach with all instrumentation and intelligence on board of one vehicle. In order to further enhance their benefit, ADAS need to cooperate in the future. This enables, for instance, to solve hazardous situations by coordinated maneuvers for safety intervention on multiple vehicles at the same point in time. Our prototyping environment presented in previous work addresses developing such cooperative ADAS. Its underlying approach is to either 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. In this paper, we focus on handling the application specific parameter space, and more precisely on the scenario related aspects. As a part of our iterative prototyping process, defining and tuning scenarios and application parameters are highly repetitive tasks which needs to be designed very efficiently. We, therefore, strive to create a scenario definition methodology, which provides best flexibility and a minimal expenditure of time on the developer side.

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Nowadays, smart mobility applications could benefit from environment perception, enabled by evolving sensor technology and processing capabilities available for traffic entities. On the application level, in many cases, information about detected objects is required instead of the raw sensor data. Developing and evaluating the impacts of such applications can be done in co-simulation frameworks, which combine the modeling of different domains such as application, communication, and traffic. Eclipse MOSAIC is a suitable solution for this task, combining the traffic simulation of Eclipse SUMO with other simulators, such as the integrated Application Simulator, or OMNeT++ and ns-3 for modeling communication. However, a model for perceiving surrounding traffic entities, such as vehicles, traffic signals, and traffic signs, is only available to a limited extent. In this paper, we introduce an object-level perception module to the MOSAIC Application simulator. It takes advantage of state-of-the-art spatial indexing methods to get rapid access to traffic objects, especially moving objects, within a defined field of view. We furthermore evaluate the computational performance of the indexing techniques as well as the integration with the traffic simulator SUMO using TraCI and libsumo. With the aid of this model, novel connected applications that analyze or share surrounding objects, e.g. for an improved traffic state estimation, can now be evaluated with Eclipse MOSAIC.