*2.3. Data Analysis*

Raw data from the Mobileye device was extracted using Control Area Network (CAN) bus interface separately for each road. As stated in Section 2.1, the data was recorded with Mobileye, and two main variables were analysed: view range and the detection quality of the markings. View range was determined in meters (maximal value 80 m) while the quality level was ranked on the scale from 0 to 3, where 0 equalled "nothing detected", 1 presented "low detection confidence", 2 "medium detection confidence" and 3 "high detection confidence". The thresholds for each quality level are not known to the authors since this information is a "know-how" of the manufacturer. The sampling rate of the camera was set at 100 Hz and GPS coordinates were recorded for each sample.

Since smaller parts of the roads are passing through settlements with road lighting, we have excluded those sections from the analysis in order to eliminate the impact of such environmental lighting on Mobileye during night-time. Also, since edge markings were not located on the whole length of the analysed roads, sections without edge lines are also excluded from the analysis.

The results of the "measurements" between day and night conditions were correlated based on the GPS coordinates. Two analyses were conducted: (1) quality of lane marking detection; and (2) view range. With respect to (1), the number of samples per each quality level was calculated for each road. Wilcoxon signed-rank test was used to test the difference in the number of quality rankings on each road during daytime and night-time. The Wilcoxon signed-rank test is a non-parametric equivalent of the dependent *t*-test, meaning that it is based on the differences between scores in the two comparing conditions. Once the differences are calculated, they are ranked and the sign of the difference (positive or negative) is assigned to the rank [23]. To calculate the significance of the test statistic (*T*), the mean (*T*) and the standard error (*SET*) are used as shown in the following equation:

$$T = \sqrt{n(n+1)4} \tag{1}$$

$$SE\_T = \sqrt{\frac{n(n+1)(2n+1)}{24}}\tag{2}$$

Based on the test statistic, the mean of the test statistic and the standard error, z-score is calculated using the Equation (3):

$$z = \frac{T - \frac{n(n+1)}{4}}{\sqrt{\frac{n(n+1)(2n+1)}{24}}} \tag{3}$$

The view range analysis included the calculation of the absolute averages for each road, line and visibility conditions as well as the average difference and standard deviation when daytime reading quality was higher compared to night-time and vice versa for both markings (middle and edge). Finally, a paired samples *t*-test was used to test the difference between night-time and daytime conditions for each line on each road. In general, a paired samples *t*-test compares the means of two measurements taken from the same individual object, or related units. These "paired" measurements can represent a measurement taken at two different times, a measurement taken under two different conditions or measurements taken from two halves or sides of a subject or experimental unit. The test compares the mean difference between samples (*D*) to the difference that is expected to be found between population means (*μD*), and then takes into account the standard error of the differences (*SD*/ <sup>√</sup>*N*), as shown in the following equation:

$$t = \frac{\overline{D} - \mu\_D}{S\_D / \sqrt{N}}\tag{4}$$

If the null hypothesis is true, then it is expected that there is no difference between the population means (*μ<sup>D</sup>* = 0). The purpose of the test is to determine whether there is statistical evidence that the mean difference between paired observations is significantly different from zero [23].

In both tests (Wilcoxon signed-rank and paired samples *t*-test), the significant level was set at 0.05. IBM SPSS 26 was used for statistical analysis.
