Detection of Safe Passage for Trains at Rail Level Crossings Using Deep Learning

Abstract

The detection of obstacles at rail level crossings (RLC) is an important task for ensuring the safety of train traffic. Traffic control systems require reliable sensors for determining the state of anRLC. Fusion of information from a number of sensors located at the site increases the capability for reacting to dangerous situations. One such source is video from monitoring cameras. This paper presents a method for processing video data, using deep learning, for the determination of the state of the area (region of interest—ROI) vital for a safe passage of the train. The proposed approach is validated using video surveillance material from a number of RLC sites in Poland. The films include 24/7 observations in all weather conditions and in all seasons of the year. Results show that the recall values reach 0.98 using significantly reduced processing resources. The solution can be used as an auxiliary source of signals for train control systems, together with other sensor data, and the fused dataset can meet railway safety standards.

Design and Characterization of an Active Cooling System for Temperature-Sensitive Sample Delivery Applications Using Unmanned Aerial Vehicles

“…Though a refrigerator can be put on a UAV, the weight and power requirements that significantly cut down the range do not make this an attractive solution [15]. While there are multiple cooling methods [28] (see Table A1), thermoelectric modules using the Peltier effect are ideally suited because they are solid-state and light weight [29][30][31][32]. Furthermore, since a heavier battery would be required to drive the Peltier over longer flying distances, cooling requirements can often result in a tradeoff with the achievable flying time.…”

A New Form of Train Detection as a Solution to Improve Level Crossing Closing Time

“…Recent proposed safety measures in level crossings consider the use of strobe lights on train locomotives [ 1 ]. Many studies have been conducted on obstacle detection at level crossings; for example, in [ 2 ], using surveillance cameras already mounted on level crossings to detect road vehicles in the collision area. In [ 3 ], the authors suggest using CCTV cameras and radars directed into the crossing area as a secondary safety tool for detecting pedestrians.…”