The project AVRM (autonomous vehicles and road markings) aimed to examine how vehicles’ advanced driver assistance systems (ADAS) are constructed, how they function and how they detect road markings on the Nordic road network. Focus was on the systems lane departure warning (LDW) and lane keeping assist (LKA). The project was divided into four different parts, namely a literature study, an empirical pilot study, an analysis of a large dataset and an empirical main study. The literature study was carried out with the aim to compile knowledge about the technology, construction, and function of LDW and LKA, differences in quality and function and how the physical environment influences detection of road markings. It consisted of a literature search where empirical studies on machine-readability of road markings were included, as well as interviews with a series of informants to acquire more knowledge of the construction and technology of ADAS. The literature study revealed that many parameters affect machine-readability. From the interview survey, it was found that exact performance properties of road markings do not directly correspond to machine-readability and that a combination of data collection technologies is often used. Both the literature study and the interview study concluded that if the human eye can detect the road marking, then the road marking is machine-readable. However, only a few studies had been conducted in wet conditions relating machine-readability to road marking functionality. The pilot study aimed to test equipment and to find a method to connect machine-readability data with contrast ratio under various weather and light conditions, and to reveal possible problems before conduction of a main study. The pilot study focused on the contrast ratio between the road marking and the road surface in both dry and wet weather conditions. The pilot study confirmed that there are many parameters affecting machine-readability that are not related to road marking functionality.