Abstract
The paper presents the concept of a system for detecting moving objects on rural road networks. Pedestrians, wild animals and domestic animals are the most common causes of traffic accidents on country roads. The system is designed to warn the driver in a timely manner about the possibility of the movement of living objects on the road, in order to protect the lives and ensure the health of living beings, as well as the driver's property on rural roads.
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Kämmerle, J.-L., Brieger, F., Kröschel, M., Hagen, R., Storch, I., Suchant, R.: Temporal patterns in road crossing behaviour in roe deer (Capreolus capreolus) at sites with wildlife warning reflectors. PLoS ONE 12, e0184761 (2017). https://doi.org/10.1371/journal.pone.0184761
Gagnon, J.W., Theimer, T.C., Dodd, N.L., Manzo, A.L., Schweinsburg, R.E.: Effects of traffic on elk use of wildlife underpasses in Arizona. J. Wildl. Manag. 71, 2324–2328 (2007). https://doi.org/10.2193/2006-445
Garriga, N., Franch, M., Santos, X., Montori, A., Llorente, G.A.: Seasonal variation in vertebrate traffic casualties and its implications for mitigation measures. Landsc. Urban Plan. 157, 36–44 (2017). https://doi.org/10.1016/j.landurbplan.2016.05.029
Pagany, R., Dorner, W.: Do crash barriers and fences have an impact on wildlife–vehicle collisions?—an artificial intelligence and GIS-based analysis. ISPRS Int. J. Geo-Inform. 8 (2019). https://doi.org/10.3390/ijgi8020066
van der Ree, R., Jaeger, J.A.G., van der Grift, E.A., Clevenger, A.P.: Effects of roads and traffic on wildlife populations and landscape function. Ecol. Soc. 16 (2011)
Stjepanović, A., Ćurguz, Z., Kostadinović, M., Jotanović, G., Stojčić, M., Kuzmić, G.: Pedestrian detection in automated vehicles using ultrasonic and passive infrared sensors. Presented at the 21st International Symposium INFOTEH- JAHORINA , Jahorina March 16 (2022)
Chamorro, A., Tighe, S.: Development and application of a sustainable management system for unpaved rural road networks. Transp. Res. Rec. 2673, 891–901 (2019). https://doi.org/10.1177/0361198119864908
Rajović, G., Bulatović, J.: Rural roads-issues and development: overview. J. Manage. Account. Stud. 4, 70–77 (2016)
Krupowicz, W., Sobolewska-Mikulska, K., Burinskienė, M.: Modern trends in road network development in rural areas. Baltic J. Road Bridge Eng. 12, 48–56 (2017)
Zhu, M., Wang, Z., Cui, H., Yao, S.: Rural road network planning based on 5g and traffic big data. J. Adv. Transp. 2022, 1991757 (2022). https://doi.org/10.1155/2022/1991757
Richter, T., Ruhl, S., Ortlepp, J., Bakaba, E.: Causes, consequences and countermeasures of overtaking accidents on two-lane rural roads. Transport. Res. Procedia 25, 1989–2001 (2017). https://doi.org/10.1016/j.trpro.2017.05.395
Jiménez, F., Naranjo, J.E., Anaya, J.J., García, F., Ponz, A., Armingol, J.M.: Advanced driver assistance system for road environments to improve safety and efficiency. Transport. Res. Procedia 14, 2245–2254 (2016). https://doi.org/10.1016/j.trpro.2016.05.240
Dhanush, V.V.S., Reddy, T.S.K., Charan, M.S., Priya, K.H.: IoT based system for detecting and monitoring automobile accidents. Int. Res. J. Modern. Eng. Technol. Sci. 04, 2029–2039 (2022)
Kouonchie, P.K.N., Oduol, V., Nyakoe, G.N.: Roadside units for vehicle-to-infrastructure communication: an overview. Presented at the Proceedings of the Sustainable Research and Innovation Conference (2022)
Mekala, M.S., et al.: Deep learning-influenced joint vehicle-to-infrastructure and vehicle-to-vehicle communication approach for internet of vehicles. Expert. Syst. 39, e12815 (2022). https://doi.org/10.1111/exsy.12815
Pagany, R.: Wildlife-vehicle collisions - Influencing factors, data collection and research methods. Biol. Cons. 251, 108758 (2020). https://doi.org/10.1016/j.biocon.2020.108758
Ma, H., Pljonkin, A., Singh, P.K.: Design and implementation of Internet-of-Things software monitoring and early warning system based on nonlinear technology 11, 355–363 (2022). https://doi.org/10.1515/nleng-2022-0036
Wang, S., Wang, B., Wang, S., Tang, Y.: Feature channel expansion and background suppression as the enhancement for infrared pedestrian detection. Sensors 20 (2020). https://doi.org/10.3390/s20185128
Anson, G.A.J., Huplo, K.C.T., Marin, M.A.V., Rivera, J.A.C., Pinili, M.V.M., Dr. Eric, B.: Blancaflor: TAOAID: pedestrian assistance using car motion detection system. In: Proceedings of the International Conference on Industrial Engineering and Operations Management. pp. 706–714. Nsukka, Nigeria (2022)
Saeidi, M., Arabsorkhi, A.: A novel backbone architecture for pedestrian detection based on the human visual system. Vis. Comput. 38, 2223–2237 (2022). https://doi.org/10.1007/s00371-021-02280-6
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Jotanovic, G., Jausevac, G., Perakovic, D., Stojanov, Z., Brtka, V., Dobrilovic, D. (2024). Internet of Vehicle Moving Objects Detection System for the Rural Road Networks. In: Perakovic, D., Knapcikova, L. (eds) Future Access Enablers for Ubiquitous and Intelligent Infrastructures. FABULOUS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-031-50051-0_4
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