Review and Selection of Methods for Automated Passenger Counting on Public Land Transport for Effective Transportation Management - Andrei D. Plakhtii; Denis S. Korchagin (Вестник СибАДИ)
Introduction. The study aims to analyze modern automatic passenger counting methods in public transport. The study addresses the pressing issue of passenger flow counting in public transport using modern technologies such as video surveillance, infrared sensors, and LiDAR.Materials and Methods. An overview of technologies is provided, including sensors, cameras, LiDAR, and RFID, along with analysis methods based on theoretical and empirical approaches. Information from development companies is used to compare the accuracy of technologies in real-world conditions.Results. The comparison results indicate that LiDAR and cameras with machine learning offer the highest accuracy, particularly in high passenger density scenarios. Wi-Fi and Bluetooth-based technologies have limited accuracy, but combined solutions can overcome their drawbacks.Discussions and Conclusions. The conclusion emphasizes that LiDAR and video surveillance with machine learning are the most effective for accurate passenger counting. Further testing of combined technologies and the development of flexible systems are recommended, along with innovative approaches in neural network training to enhance accuracy.