Kristaps Greitans. A study on Automated railway level crossing control system using FMCW radar for accident prevention. 2023 International Conference on Applied Electronics (AE), Pilsen, Czech Republic, 2023, 2023.
Bibtex citation:
Bibtex citation:
@inproceedings{15804_2023,
author = {Kristaps Greitans},
title = {A study on Automated railway level crossing control system using FMCW radar for accident prevention},
journal = {2023 International Conference on Applied Electronics (AE), Pilsen, Czech Republic, 2023},
year = {2023}
}
author = {Kristaps Greitans},
title = {A study on Automated railway level crossing control system using FMCW radar for accident prevention},
journal = {2023 International Conference on Applied Electronics (AE), Pilsen, Czech Republic, 2023},
year = {2023}
}
Abstract: This study paper explores the implementation of Intelligent Transportation Systems (ITS) in railway transportation, with a focus on level crossings, which have been a significant issue in railway safety. The paper discusses the limitations of current technologies such as laser technology and video surveillance and presents a novel solution utilizing a 79GHz Frequency Modulated Continuous Wave (FMCW) radar in combination with a CCTV camera for a dual sensor module. The FMCW radar is shown to be more accurate and cost-effective than previous technologies and can detect both large and small objects in the defined area at level crossings and difficult weather situations. The paper also presents a system architecture that takes into account vehicle detection time, which is crucial in reducing the risk of accidents and improving the safety of level crossings. This study aimed to compare the performance of different object detection modules under varying weather conditions. Three object detection methods were tested: a camera with the object detection algorithm Yolov5, FMCW radar with a built-in tracker, and manual observation. Four measurement sessions were conducted, each with a different combination of weather and time of day. The results showed that all modules performed similarly well under clear weather conditions, with the camera and radar modules detecting all vehicles approaching. However, under rainy and dark conditions, the radar module outperformed the camera, detecting 5 more objects.