## 7 Conclusions  
The main problem with counting vehicles in rest areas in Europe and America is the overflowing of parking lots in the rest areas. Thus, it is impossible to count parked vehicles with traditional, direct methods which use cameras and Lidar (light detection and ranging) to detect the presence of vehicles in individual parking spots. This makes it impossible, e.g., to meet United Europa (EU) recommendations regarding information about parking occupancy information, among others [3]. At the beginning of this paper, we showed different approaches for car park occupancy measurements. There were two different types of measurements, namely:  
1. The direct method gives the number of vehicles in the parking lot by using cameras and Lidar (light detection and ranging) that focus on the parked cars. 2. The indirect method gives parameters for the entire lot using cameras that count cars entering and exiting the lot. We stated that our proposed solution to resolve the problem of counting vehicles in overflowing parking lots would be the presented indirect method of counting vehicles. The indirect method presented in the article is based on precise, indirect measurements of car park occupancy. In contrast to the generally followed direct methods, this proposed method is insensitive to overflowing parking lots. Due to this, the exhibited measurement method can be more reliable. Additionally, certainty measurement improvement should increase after implementation of the virtual calibration method presented in Section 6. The indirect method presented in the paper has two main advantages:  
1. The first advantage is a minimal number of measuring points. In the case of a rest area, only two are needed because rest areas on highways usually have one entry and one exit way. This property improves secure traffic. Although in Section 3 we presented a system for measuring more than two points, which we used in the RID project [35]. This measuring system makes it possible to use more than two measurement points. 2. The second advantage is that we can calculate the number of vehicles in the parking lot without any data about where the vehicles park. The currently used method, based on the detection of parking place occupancy, does not give these results because, in an overcrowded parking lot, truck drivers will park on whatever surface is available. In this case, car parks are often overcrowded by up to 70% [34]. The main disadvantage of the method presented in this article is the possibility of grave relative errors stemming from counting errors regarding the number of vehicles using the car park and the number of parking spaces. However, Section 6 presented a method that eliminates this error and improves the accuracy of determining parking space occupancy in rest areas. In future research:  
1. We will try to implement our own system for the measurement of parking lot occupation by presenting an indirect method using AI, based on over 200,000 verified entrances and exits and the classification of the vehicles in the parking lots within project RID [34]. We need to note that most of the data used for preparing this article came from this project, in which the authors participated. 2. In another project, we (at the beginning of the year 2023) installed our mains-free supply measurement points (cameras with internet access and an independent power source of a solar panel and battery) in the rest area of North Brwinow near Warsaw. We will detect and classify the vehicles entering and exiting this rest area until the end of 2025. 3. The third part of our future research is to use unattended and mains-free supply autonomously charging drones for measurement calibration. 4. In the future, we will try using information quality management (IQM) for the optimization of measurement quality using uncertainty modeling methods [37; 38] created by the main author. Conceptualization, M.S. and K.P. ; methodology, M.S. and T.C. ; software, M.S. and G.W. ; validation, M.S., A.R., K.P. and T.C. ; formal analysis, M.S. and G.W.