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Traditionally, an in-vehicle map consists of only one type of data, tailored for a single user function. For example, the navigation maps contain spatial information about the roads. On the other hand, a map built for adaptive cruise control use consists of the detected vehicles and their properties. In autonomous vehicle research, the maps are often built up as an occupancy grid where areas are classified as passable or impassable. Using these kinds of maps separately, however, is not enough to support the traffic safety enhancing and advanced driver assistance systems of today and tomorrow. Instead of using separate systems to handle individual safety or planning tasks, information could be stored in one shared map containing several correlated layers of information. Map information can be collected by any number of different sensor devices, and fusion algorithms can be used to enhance the quality of the information.

The performance of a parking system is dependent on many factors. One is the placement of the sensors. In this paper a system which uses ultrasonic ranging sensors is considered. The mounting of a ultrasonic sensor on a passenger vehicle is restricted by, among other factors, design, assembly process, enclosure cost and reliability. All of which must be considered when choosing optimal mounting locations. The basis of this work includes a ray-trace based simulation environment which is used to capture the physical properties of sound traveling through air. The simulation environment together with sensor models, is used to evaluate the effect of different mounting positions on the accuracy of the detection of the parking space. The Hough transform is used here, as well as in the real system, in order to extract the confining lines of the parking space from the sensor measurements. The strength of these lines are then used to compare different sensor mounting locations.

This paper describes a system for supporting the driver of a passenger car in different parking situations. Todays cars are getting larger in size and the drivers view in both forward and rearward direction is becoming more limited. This fact calls for a system of sensors and algorithms capable of supporting the driver through the parking maneuvre in a safe and smooth way. The paper presents the development of some of the subsystems in a fully automatic parallel parking system, utilizing ultrasonic ranging sensors for environment mapping. In contrast to existing passive parking aid systems, the ultrasonic range sensors need to have a narrower aperture to be able to map the surroundings properly. This can be accomplished by either increased sensor size or by a higher number of sensors. The emphasis of the paper is the signal conditioning in the parking system. The Hough-transform along with a statistical CUSUM test are used to find the properties of the target parking space.