## 3 Results and Discussion
Totals 72.62% of the OSNMA strict solutions, 86.75% of the OSNMA loose solutions, and 86.86% of the OSNMA off solutions had an accuracy of better than 2 cm. These results show that under open sky conditions a vehicle can safely be guided within a traffic-lane, and this is also in agreement with [27; 28; 29]. The right hand side of Figure 5 shows CDFs for data aggregated over different driving environments. This is a result from drives where we passed motorways, hilly and forested rural roads, a mountain, and suburban and urban areas. The 2D errors are obviously  
Figure 4: Proportion of position types depending on the number of satellites. (**Top left**): 4 to 6 satellites; (**top right**): 7 to 8 satellites; (**middle left**): 9 to 10 satellites; (**middle right**): 11 to 12 satellites; (**bottom left**): 13 to 14 satellites; (**bottom right**): \(>=\)15 satellites. significantly larger due to the more challenging environments. Hence, an RTK-fixed solution was not always possible, but all solution types occurred (no-fix, SPP, RTK float and fix). The worst performance was achieved in the OSNMA strict mode, which is mainly due to the limited satellite visibility and availability of authenticated Galileo satellites. Only 73.2% of the data had an error of less than 20 cm. For the OSNMA off case, 92.47% of the PVT solutions were better than 20 cm, and the OSNMA loose case again performed slightly better with 92.55% of the solutions being better than 20 cm. This is a very good performance for a mass-market receiver. Looking more into detail, one can observe that the localization accuracy typically increases with the number of satellites used during the PVT calculation. The general behavior of the 2D errors is shown in Figures 6 and 7. When the satellite number was between 4 to 6 (top left), the solutions for all OSNMA configurations performed moderately well. The OSNMA strict solution performed slightly better in the relevant accuracy range (below 50 cm). This most probably resulted from the fact that the satellite visibility is better in situations where 4-6 Galileo satellites are visible instead of when 4-6 GPS+Galileo satellites are visible (comparing solutions with a different number of visible satellites does not mean comparing the performance at the same locations!). In addition, Galileo signals are typically better than GPS ones, especially in multipath conditions. For the OSNMA strict configuration, 65.37% of the 2D errors were smaller than 20 cm, compared to 61.16% for OSNMA loose and 58.19% for OSNMA off. The authors would expect that the advantage of the OSNMA strict solution over the others should be maintained, but this was not the case for the group of 7 to 8 visible satellites. The reason for it is unclear. In summary, the performance significantly improved when having 7-8 satellites. For the use of 9 to 10 satellites, the OSNMA strict performance was extraordinarily good (98.00% of the errors were below 20 cm). This is obvious because having 9 or 10 satellites of one constellation means that the receiver was in a very open area compared to having 9 or 10 satellites of two constellations. Further increasing the satellite number to more than 10 satellites only slightly improved the positioning accuracy. In principle, one can see nearly no difference between the OSNMA loose and off configurations. This indicates that nearly all Galileo satellites could be authenticated (or the status was unknown). The combined GPS+Galileo solutions with 15 or more satellites have a comparable performance to that of the OSNMA strict solution with 9 or 10 satellites, which is obvious since most probably, the receiver was in a very open region. The performance of the OSNMA loose configuration gives an indication of what most probably can be achieved with the Galileo OSNMA service when it is fully operational. This is a very promising result in view of highly automated vehicles. Figure 5: CDF functions of the 2D localization error.