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There is a pressing need for road authorities to take a proactive role in the deployment of automated vehicles on the existing road network. This requires a comprehensive understanding of the driving environment characteristics that affect the performance of automated vehicles. In this context, a field test with Lane Departure Warning (LDW) and Lane Keeping Systems (LKS)-enabled vehicles was conducted in the Netherlands. Empirical data from the experiment was used to estimate the impact of driving environment components such as weather condition and lane width on the performance of the automated vehicles. Driving at night in the presence of streetlights with rain resulted in least detection performance for both the vehicles as compared to other visibility conditions. As for lane-keeping performance, the LKS positioned the vehicle significantly more to the left of the lane on left-curves than on straight sections. The LKS also positioned the vehicle more left on lanes with a width less than 250 cm than on wider lanes. These findings were translated into levels of service of the Operational Design Domain (ODD). Each level of service corresponded to a performance level of the lane assistance systems, classified as &#x201C;High&#x201D;, &#x201C;Medium&#x201D;, and &#x201C;Low&#x201D;, and defined using indicators.

Operational Design Domain Requirements for Improved Performance of Lane Assistance Systems: A Field Test Study in The Netherlands