## 2 Research Background
For this reason, the proposal submitted in this article is more economically effective and, at the same time, the estimation of the number of vehicles is accurate. In another publication, the authors paid particular attention to the vehicle location accuracy obtained from satellite global navigation systems in built-up areas [17]. These areas were characterized by a multipath propagation of radio signals, which resulted in inaccuracies in determining the position of vehicles. They proposed the use of a classifier to distinguish between multipath and direct GNSS signals. As a result, the accuracy of the vehicle location increased. This then enabled the location data to be used to identify the vehicle in the car park and, moreover, in which exact parking space. The use of data from global navigation satellite systems was studied by another team [18]. To reduce the inaccuracy of the location, the authors proposed smartphone inertial sensors be used. As a result, it was possible to determine the vehicle's location in real-time via GNSS and increase accuracy by tracking it with the phone's inertial sensors. This solution is advantageous, especially in multi-story car parks. The use of [PERSON]'s and [PERSON]'s theory to determine the occupancy of the space in front of the vehicle was presented in one of the papers by the authors of [19]. Thus, obtaining information about the available space and using it efficiently became possible. However, the authors did not carry out a broader analysis that would have allowed the use of the obtained information to assess the occupancy of parking spaces. In the field of parking spaces, researchers' studies are not only focused on the assessment of the occupancy of parking spaces but also on the development of new methods for planning geometric paths that will be used for parking autonomous vehicles [20]. Thanks to these, it is possible to enhance the use of space in a car park and thus park more vehicles. Such solutions will reduce the uncertainty of measuring the number of vehicles in a car park, as the human factor will be eliminated in parking. In another study, the authors used satellite images to determine the occupancy of parking spaces. This is a relatively new approach requiring high-resolution photos [21]. In this type of analysis, it is necessary to distinguish between moving and parked vehicles. Issues in this area were presented by the authors of the following study [22]. This team tried to resolve problems in vehicle-type detection in the previous study caused by processing video data using the Digital Surface Model (DSM) [23]. In this section, we have referenced many approaches that have been proposed for resolving the problem of counting vehicles in parking lots. This problem is more minor in parking areas where there is no additional surface for vehicles to stop. However, the parking lots of motorway rest areas, which we examined, have many areas without parking stands (e.g., access roads, gas stations, dedicated parking spaces for service vehicles, and parking in a space for other types of vehicles). Drivers park their vehicles in these areas, and it causes an overflowing of the rest area. Thus, there is no good solution for counting how many vehicles are on a rest area's surface. A UE publication in ITS Directive 2010/40/EU supplements from 15 May 2013 [3] recommended delivering certain and precise information for drivers in the Datex system about parking spaces close to their travel path. Still, we do not have a good measurement method ten years later. Thus, we propose using an indirect measurement to determine car park occupancy in rest areas. As the introduction mentioned, the first method is the direct method shown in Figure 1. The second method is the indirect method. Figure 2 shows the vehicle detector localization for the indirect method as presented in [24; 25]. Video cameras were used as vehicle detectors. We used mains-free supply video cameras with solar panels and batteries.