# Fast and High Precise Spatial Documentation of Traffic Accident Site Using Only Low-Cost RPAS
## 2 Materials and Methods
### Proposed RPAS Method  
We propose that traffic officers, during traffic accident site documentation, should use a multi-rotor RPAS with a 4K digital camera using an optical sensor. This type of RPAS would be small, well equipped, easy to control, and economically available. For proof of concept, we used a DJI Mavic 2 Pro quadcopter, which is equipped with an L1D-20c camera (physical focal length is 10.37 mm = 28 mm in 35 mm format equivalent). It has 20 million effective pixels and a 1\" CMOS sensor mounted on a 3-axis gimbal. GNSS sensors utilize signals from the global positioning system (GPS) and the Global\(\cdot\)naja Navigacionnaja Sputnikovaja Sistema (GLONASS). The maximum flight time is about 31 min [12]. This RPAS and its data are the only input, which we used to create the final model. No more hardware tools or data entered the whole process. During the proof of concept, we also used a steel tapeline, a laser rangefinder, and some objects with known dimensions--but only to assess the accuracy of the final product. Testing this proposed method during a real traffic accident was not feasible due to legislation restrictions. Therefore, an experiment took place inside a closed area in Opava in the Moravian-Silesian region of the Czech Republic. We arranged a traffic accident, involving three cars (due to the reason mentioned earlier) and reference objects. Buildings, trees, wires, fences, and construction materials were present quite close to the site. The arranged traffic accident surroundings were rather complicated compared to usual real traffic accidents. The day of the flight was sunny, with a temperature around 25 \({}^{\circ}\)C, and the wind speed was 3.6 m\(\cdot\)s\({}^{-1}\). Including site reconnaissance, it took us approx. five minutes to prepare the RPAS--unfolding the RPAS, inserting the accumulator, turning on the remote controller and DJI GO 4 application, turning on the RPAS, connecting the remote controller and the RPAS, calibrating the compass and inertial measurement unit (IMU), and waiting for the signal capture from the GNSS and home point setting. The flight time itself took approx. two minutes (the automatic flight would take approx. four minutes). The preparation time is not overly dependent on the extent of the traffic accident site. The flight time is slightly prolonged for more extensive traffic accident sites. No reference objects, like GCPs, are needed for subsequent georeferencing because we obtain the necessary spatial information from the onboard GNSS sensor. The absolute coordinates accuracy is not so important for this purpose; on the other hand, local coordinate accuracy is crucial. Due to the presence of obstacles, we could not use the automatic flight. We conducted four single-grid manual flights, during which we acquired still images and videos. Images obtained during the third flight gave the most suitable results after processing. The flight and camera parameters are shown in Table 1.  
A general overview is depicted in Figure 2. We positioned three cars (A, B, C) to simulate a real traffic accident, around which we set rectangular (1, 2, 3, 4) and round (8) objects with known dimensions and three points designated to the distance measurements (5, 6, 7). After each of the flights, we measured three distances between given points (5, 6, 7). The trajectory of the third flight is also depicted. To assess the accuracy of the final model,