Russian Federation
Voronezh, Voronezh, Russian Federation
The article provides an overview of modern vision systems used in the transportation industry. The architectural components of such systems are considered: sensor suite (cameras, LiDARs, radars), computing platforms, and artificial intelligence algorithms. A classification of vision systems by functional purpose is presented-from active safety systems (ADAS) to highly automated solutions for autonomous driving. The features of vision system application in various modes of transport (automotive, railway, warehouse logistics, intelligent infrastructure) are analyzed. The main technical, regulatory, and economic challenges are identified, as well as promising areas of development, including sensor fusion, the transition to solid-state LiDARs, and integration with V2X technologies.
vision systems, advanced driver-assistance systems (ADAS), autonomous driving, sensor fusion, LiDARs, computer vision, transportation industry
1. Evgen'ev V.P., Kotov V.V., Smirnov A.L. Sistemy tehnicheskogo zreniya v avtomobilestroenii: sovremennoe sostoyanie i perspektivy // Avtomobil'naya promyshlennost', №3, 2023. – S. 12–19.
2. SAE International. Klassifikaciya urovney avtomatizacii dlya dorozhnyh transportnyh sredstv (SAE J3016). – Warrendale, PA: SAE International, 2021. – 42 s.
3. Euro NCAP. Dorozhnaya karta Euro NCAP 2025: dostizhenie Vision Zero s pomosch'yu sistem pomoschi voditelyu. – Bryussel', 2020. – 58 s.
4. Mezhdunarodnaya organizaciya po standartizacii. ISO 26262: Dorozhnye transportnye sredstva – Funkcional'naya bezopasnost'. – Zheneva, 2018. – 350 s.
5. Ivanov A.A., Petrov S.V., Sidorov I.N. Analiz arhitektur sistem tehnicheskogo zreniya dlya bespilotnyh avtomobiley // Sbornik trudov XII Mezhdunarodnoy nauchno-tehnicheskoy konferencii «Intellektual'nye transportnye sistemy». – M.: MADI, 2024. – 320 s. ISBN 978-5-7962-0321-9. – S. 45–52.
6. NVIDIA Corporation. Platforma NVIDIA DRIVE dlya avtonomnyh transportnyh sredstv. Tehnicheskiy otchet. – Santa-Klara, 2024. – 35 s.
7. Mobileye (Intel). Sistema na kristalle EyeQ dlya sistem pomoschi voditelyu. Obzor produkta. – Ierusalim, 2023. – 28 s.
8. Tesla Inc. Den' iskusstvennogo intellekta 2023: arhitektura avtonomnogo vozhdeniya na osnove kamer. Materialy prezentacii. – Ostin, 2023. – 67 s.
9. Waymo LLC. Otchet o bezopasnosti Waymo: sozdanie samogo opytnogo voditelya v mire. Tehnicheskiy otchet. – Mauntin-V'yu, 2023. – 89 s.
10. Baranov A.E., Kuznecov D.S. Primenenie sistem tehnicheskogo zreniya na zheleznodorozhnom transporte // Transport Urala, №4 (71), 2022. – S. 23–30.
11. Lebedev M.V., Frolov N.A. Sensornaya fuziya v sistemah avtonomnogo vozhdeniya: sovremennoe sostoyanie i vyzovy // Intellektual'nye sistemy na transporte. Sbornik nauchnyh trudov. – SPb: Peterburgskiy gosudarstvennyy universitet putey soobscheniya, 2023. – 210 s. ISBN 978-5-7641-1547-8. – S. 112–120.
12. Vasil'ev R.Yu., Grigor'ev S.A. Metody glubokogo obucheniya dlya raspoznavaniya ob'ektov v transportnyh sistemah tehnicheskogo zreniya // Vestnik komp'yuternyh i informacionnyh tehnologiy, №6 (228), 2024. – S. 34–42.
