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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.

Modern vehicles use Electronic Control Units (ECU), connected via Controller Area Network (CAN) to perform functions. Many of these functions are distributed across several ECUs. This network interconnection enables the sharing of sensors, calculated information and actuators. As new functionality is added, the number of ECUs and their complexity increase. This paper describes the values and possibilities of a Hardware-In-the-Loop (HIL) based Integration Lab, which enables a wide range of automatic tests to be performed on networked ECUs. The Integration Lab is the complex rebuild of a Scania truck/bus, containing the ECU superset, for connecting and testing networked ECUs. It involves more than 30 ECUs and eleven CAN networks.