Digital transport traseology based on Agisoft Metashape and unmanned aerial vehicle

Introduction. A vehicle and trace evidence analysis is one of the most requested types of examinations performed within the framework of criminal cases on road traffic accidents. The main methodical guidelines for traffic and trace evidence analyses were developed in the past century, while nowadays the fourth industrial revolution is on the rise. The industrial revolution is based on computer and information technologies, various software and hardware tools. Hence there is a vital necessity in update of the vehicle and trace evidence analysis methodology in order to conform to current-day realities.

Materials and methods. Results of use of the unmanned aerial vehicle and Agisoft Metashape software are presented in the article in the context of specific road traffic accidents. It was made clear that application of this method has the following advantages: firstly, time of fixation of objects of the roadway network, vehicles and their traces on traffic ways is significantly reduced; secondly, fixation accuracy is improved; thirdly, use of the method makes it possible to establish all actual facts needed to perform analysis of the mechanism of a road traffic accident. Digital models obtained using this method could be used for 3D modeling, what offers an opportunity for more accurate determination of a mode and an angle of approach of vehicles before an accident with significant reduction of financial and time expenditures.

Results. It was shown that digital models of road traffic accident sites and vehicles could be entered into the case file in general as well as into an expert’s statement in particular. Such entering will improve objectivity and believability of the conducted examination. Digital models of road traffic accident sites (digital twins) could be stored for an indefinitely long time and could contain the entire information on physical accident scene. Therefore such digital models are considered as valuable information while performing additional or repeated examinations.

Conclusion. The proposed method for creating a digital model of a vehicle or a site of a traffic accident can be used in digital transport traceology.

1. Kulagin A. D. Vozmozhnosti i problemy avtotehnicheskoj i transportno-trasologicheskoj jekspertizy pri rassledovanii prestuplenij, svjazannyh s inscenirovkoj ili fal’sifikaciej dorozhno-transportnyh proisshestvij [Opportunities and Problems of Autotechnical and Transport-traceological Expertise in the Investigation of Crimes Related to Staging or Falsification of Road Traffic Accidents]. Integracija nauk. 2018; T. 23. no 8: 336-340. (in Russ.)

2. Beljaev M. V., Chetvergov M. A. K voprosu o sovremennyh sposobah modelirovanija dorozhnotransportnyh proisshestvij [On the Question of Modern Modeling Methods Road Traffic Accidents]. Vestnik Moskovskogo universiteta MVD Rossii. 2018; 4: 5-11. (in Russ.)

3. Beljaev M. V. K voprosu o metodicheskih polozhenijah transportno-trasologicheskoj jekspertizy [To the Question About the Methodological Provisions of the Transport-Technical Expertise.]. Vestnik Moskovskogo universiteta MVD Rossii. 2019; 1:9-12. (in Russ.)

4. Demidova T. V., Beljaev M. V. Primenenie innovacionnyh tehnologij pri osmotre mest dorozhno-transportnyh proisshestvij [Application of Innovative Technologies When Inspecting Places of Road Traffic Accidents]. Vestnik Akademii jekonomicheskoj bezopasnosti MVD Rossii. 2015; 2: 72-76. (in Russ.)

5. Bondarenko A. A. Primenenie fotogrammetricheskih metodov dlja fiksacii obstanovki dorozhno-transportnogo proisshestvija [Application of Photogrammetric Methods for Recording the Situation of a Road Traffic Accident]. Sudebnaja jekspertiza: nauchno-prakticheskij zhurnal. 2005; 3: 36-38. (in Russ.)

6. Dobromirov V. N., Evtjukov S. S. Golov E. V. Sovremennye tehnologii pervichnogo osmotra mesta dorozhno-transportnogo proisshestvija [Modern Technologies of the Primary Inspection of the Road Accident Place]. Vestnik grazhdanskih inzhenerov. 2017; T. 61. № 2: 232-239. (in Russ.)

7. Saraev A. V., Danec S. V. Metody issledovanija dorozhno-transportnyh proisshestvij s ispol’zovaniem sovremennyh avtomatizirovannyh sredstv [Methods for Investigating Road Traffic Accidents Using ModernAutomated Means]. Nauka i tehnika. 2019; T. 18. no. 3: 256–264. https://doi.org/10.21122/2227-1031-2019-18-3-256-264 (in Russ.)

8. Dumnov S.N. K voprosu o primenenii metoda lazernogo 3D-skanirovanija pri proizvodstve sudebnoj avtotehnicheskoj jekspertizy [To the Question of the Application of the Method of Laser 3D Scanning in the Manufacture of Judicial Auto-Technical Examination]. Vestnik Vostochno-Sibirskogo instituta MVD Rossii. 2019; T. 90. no. 3: 133-145. DOI: 10.24411/2312-3184-2019-00037 (in Russ.)

9. Graça N., Mitishita E., Gonçalves J. Photogrammetric Mapping Using Unmanned Aerialvehicle. ISPRS Technical Commission I Symposium: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (17–20 November 2014). Denver, Colorado, USA, 2014; Vol. XL–1: P. 129–133.

10. Gandor F., Rehak M., Skaloud J. Photogrammetric Mission Planner for RPAS. 2015 International Conference on Unmanned Aerial Vehicles in Geomatics: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (30 Aug–02 Sep 2015). Toronto, Canada, 2015; Vol. XL–1/ W4: P. 61–65.

11. Mah S. B., Cryderman C. S. Implementation of an Unmanned Aerial Vehicle System for Large Scale Mapping. International Conference on Unmanned Aerial Vehicles in Geomatics: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (30 Aug–02 Sep 2015). Toronto, Canada, 2015; Vol. XL–1/W4: 47–54.

12. Digital Elevation Model from Non-metric Camera in UAS Compared with Lidar Technology/ O. M. Dayamit, M. F. Pedro, R. R. Ernestoa, B. L. Fernandoa. International Conference on Unmanned Aerial Vehicles in Geomatics: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (30 Aug–02 Sep 2015). Toronto, Canada, 2015; Vol. XL–1/W4: 411–413.

13. Ardestani S. M., Jin, P. J., Volkmann, O., Gong, J., Zhou, Z., Feeley, C., 2016. 3D Accident Site Reconstruction Using Unmanned Aerial Vehicles (UAV). In: Presented in 95th Annual Meeting, Transportation Research Board, Washington DC, USA. Paper No. 16-5703.

14. Liu, X., Guan, Z., Fan, Q., Chen, Q., Gao T. Remote Sensing and Scene Reconstruction of Traffic Accident Based on Unmanned Aerial Vehicle Platform. In Proceedings of the 19th COTA International Conference of Transportation Professionals, Nanjing, China, 6–8 July 2019; 3331–3342.

15. Liu X., Zou H., Niu W., Song Y., He, W., 2019b. An Approach of Traffic Accident Scene Reconstruction Using Unmanned Aerial Vehicle Photogrammetry. In: Proceedings of the 2019 2nd International Conference on Sensors, Signal and Image Processing. 2019: 31–34.

16. Škorput P., Mandžuka S., Greguri´c, M., Vrancic, M.T. Applying Unmanned Aerial Vehicles (UAV) in Traffic Investigation. Process. Lect. Notes. Netw. Syst. 2020. 76. 401–405.

17. Pérez J. A.; Gonçalves G. R.; Rangel J. M. G.; Ortega, P.F. Accuracy and Effectiveness of Orthophotos Obtained from Low Cost UASs Video Imagery for Traffic Accident Scenes Documentation. Adv. Eng. Softw. 2019, 132, 47–54.

18. Nedobitkov A. I., Ohotenko A. I. Ispol’zovanie Agisoft PhotoScan i bespilotnogo letatel’nogo apparata v celjah ustanovlenija obstojatel’stv dorozhno-transportnyh proisshestvij [Agisoft PhotoScan and Unmanned Aerial Vehicle Use for the Purposes of Establishment of Circumstances of a Traffic Accident.]. Vestnik KazGJuIU. 2020; 45. no. 1:130-134. (in Russ.)

19. Hlebnikova T. A., Opritova O. A. Jeksperimental’nye issledovanija tochnosti postroenija plotnoj cifrovoj modeli po materialam bespilotnoj aviacionnoj sistemy [Experimental Studies of the Dense Digital Model Accuracy by Using]. Vestnik SGUGiT. 2018; 23. no. 2:119-129. (in Russ.)

20. Krutov S. A. Videoregistrator kak ob’ekt issledovanija sudebnyh jekspertiz [Video Recorder as an Object of Forensic Expert Analysis]. Teorija i praktika sudebnoj jekspertizy. 2021; 16. № 1:114–123. https://doi.org/10.30764/1819-2785-2021-1-114-123 (in Russ.)

21. Majlis N. P. Metody modelirovanija pri proizvodstve sudebnyh jekspertiz, kak jeffektivnoe sred¬stvo v dokazyvanii [Methods of Modeling in the Production of Forensic Examinations as an Effective Tool in Proving]. Vestnik Moskovskogo universiteta MVD Rossii. 2018; 4: 71-73. (in Russ.)

22. Majlis N. P. Rol’ innovacionnyh tehnologij v razvitii cifrovoj trasologii [The Role of Innovative Technologies in the Development of Digital Traceology]. Teorija i praktika sudebnoj jekspertizy. 2022; T. 17. no. 2:18–22. https://doi.org/10.30764/1819-2785-2022-2-18-22 (in Russ.)

23. Grigorjan V. G. Novye ob’ekty issledovanija sudebnyh avtotehnicheskih jekspertiz [The New Objects of Forensic Vehicle Examinations]. Teorija i praktika sudebnoj jekspertizy. 2019; 14. no. 2: 84–91. https://doi.org/10.30764/1819-2785-2019-14-2-84-91 (in Russ.)

24. Il’in N. N. Zadachi sudebnyh transportno-tehnicheskih jekspertiz. Teorija i praktika sudebnoj jekspertizy. 2019; t. no. 14. 2: 35–42. https://doi.org/10.30764/1819-2785-2019-14-2-35-42 (in Russ.)

25. Kokin A. V. Sudebnaja jekspertiza v jepohu chetvertoj industrial’noj revoljucii (Industrii 4.0) [Forensic Expertise in the Era of the Fourth Industrial Revolution (Industry 4.0)]. Teorija i praktika sudebnoj jekspertizy. 2021; 16. no. 2: 29–36. https://doi.org/10.30764/1819-2785-2021-2-29-36 (in Russ.)