Hệ thống Xe Điện Thông Minh cho Các Thành Phố Thông Minh: Ứng Dụng Học Sâu trong Hệ Thống Hỗ Trợ Lái Xe Nâng Cao

Marco Guerrieri1, Giuseppe Parla1
1DICAM, University of Trento, Trento, Italy

Tóm tắt

Công nghệ trí tuệ nhân tạo và các phương pháp học sâu chắc chắn là tương lai của các hệ thống hỗ trợ lái xe nâng cao (ADAS). Bài báo này trình bày một kỹ thuật để phát hiện, nhận diện và theo dõi người đi bộ, phương tiện và xe đạp dọc theo hạ tầng đường ray xe điện trong môi trường đô thị phức tạp bằng cách sử dụng Các phương pháp Thị giác Máy tính, Học sâu và thuật toán YOLOv3. Các thí nghiệm đã được tiến hành trên tuyến xe điện Line 2 "Borgonuovo – Notarbartolo" (Palermo, Ý) tại các đoạn đường ray giao nhau với một vòng xuyến có đường kính ngoài là 24 m. Một xe khảo sát được trang bị camera video đã được sử dụng trong nghiên cứu. Kết quả nghiên cứu cho thấy phương pháp được đề xuất có khả năng tìm kiếm và phát hiện vị trí cũng như tốc độ của người tham gia giao thông gần và trên đường ray trước xe điện một cách rất chính xác, điều này được thể hiện qua các giá trị ước lượng về Độ chính xác, Mất mát và Độ chính xác thu được trong quá trình đào tạo mạng nơ-ron. Việc triển khai phương pháp phát hiện tiên tiến này trong các hệ thống ADAS có thể tăng cường an toàn cho các xe điện tự động mới và các xe điện nhanh tự động (ARTs).

Từ khóa

#trí tuệ nhân tạo #học sâu #hệ thống hỗ trợ lái xe #ADAS #xe điện #thị giác máy tính

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