Objective To improve the reliability of visible light communication-based metro train positioning technology in narrow and enclosed metro tunnel scenarios and make up for the deficiencies of existing train positioning methods, it is necessary to study the effects of irregular reflections of optical signals from tunnel inner walls and train running speed on positioning accuracy, and further to propose a train positioning method capable of achieving continuous positioning.

Method First, signal modulation technology is employed to encode and modulate the information to be transmitted, making it carry the position data of the tunnel lighting lamps. An irregular channel model for visible light communication that conforms to actual conditions is established. Next, a fingerprint database is established using the light intensity characteristics of transmitting light sources to build a mapping relationship between train position coordinates and signal strength features. Meanwhile, the KNN (k-nearest neighbor) algorithm is used to match train position information with signal strength, thereby achieving train positioning. Finally, a Kalman filter algorithm is applied to optimize the positioning results. The effectiveness and feasibility of the proposed method are verified based on actual line data and equipment parameters from Chengdu Metro Line 1.

Result & Conclusion  When the train runs in a straight line at a constant speed of 40 km/h, the average positioning error of the proposed method is 1.8 m. When the train runs at variable speeds with the maximum speeds of 20 km/h, 100 km/h and 180 km/h respectively, the average positioning error is approximately 2.0 m. The positioning results meet the requirements of the CBTC (communication-based train control) system.