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Enhanced perception algorithms are the key requirement for the introduction of more sophisticated active safety functionalities to urban areas. In order to realize the principles of test-driven development for such systems, either a set of representative and comprehensive test-drive logs needs to be available up front or a sufficiently universal simulation environment for virtual maneuvers should be employed. In this article a case study of developing a radar-based estimator for target heading is considered. This relatively standard problem serves as an illustrative example to assess the merits of an inherently simplified stimulus generated from virtual maneuvers and its limitation in comparison to real measurements. It is argued that a convenient modelling approach for a virtual scene simulation applied from an early development stage can further improve the quality and integrity of active safety projects, especially when they involve multiple sensor types.

In this paper we present an example design process of filters used in automotive industry. Signal preprocessing is very important operation in active safety algorithms. Such algorithms usually take into account the vehicle state that includes position, velocities and accelerations of the car. On the basis of these data, as well as the parameters and trajectories of external objects “observed” by the car, the algorithms make decisions about various safety actions. Designer of such algorithms must assure an appropriate quality of such signals, which usually means a proper filtering. In this paper we focus on selected important aspects of the filter design process. The main objectives of the presented investigations is to obtain such filters that ensure a sufficient rejection of undesired components from the signal and at the same time that do not introduce too high delay to the processed signals.

Active Safety (AS) and Advanced Driver Assistance Systems (ADAS) can nowadays be considered as distributed embedded software systems where independent microprocessor systems communicate together using different communication protocols. Typical AS or ADAS functionality is then realized by several microprocessors communicating with each other. AS and ADAS systems interact with other Electronic Control Units in a vehicle via communication networks and gather vehicle's surroundings via camera, radar or laser sensors. Quality assurance and safety standards combined with increasing complexity and reliability demands related to vision sensing, radar sensing and data fusion, often together with a short time to market, make the development of such systems challenging. As the number of important road scenarios for the system grows, mathematical modelling and computer simulation become important engineering tasks that aim to assure the required quality and compliance with safety standards.