Pre-scanning Algorithm of Railway Track Curvature and Analysis of Geometric Lag Principle

doi:10.3901/JME.2023.10.301

Abstract

Abstract: Obtaining the railway track curvature in real time can provide key input parameters for many active control technologies of railway vehicles. It is an effective way to completely solve the problem of signal lag to obtain the image of the front track line through camera and pre-scanning the curvature. Therefore, some reasonable assumptions based on the existing machine vision technology is made and a pre-scanning algorithm is proposed to map the track curvature through the lateral offset of the track center line. Then, the lag principle of the measured curvature relative to the curvature at the pre-scanning point is further analyzed. The results show that the virtual vehicle body formed by the pre-scanning point introduces geometric inertia. On this basis, the spatial correction formula between the measured curvature and the actual curvature of the vehicle position is given. Finally, the above conclusions are verified by Simpack and Matlab simulation. The above research results can provide some theoretical reference for the application of vision technology in the field of railway vehicle active control.

Key words: railway vehicle, railway track curvature, real-time detection, pre-scanning, geometric inertia effect

CLC Number:

TG156

XIAO Chunyu, TIAN Shiqiao, LUO Xiangping, GONG Dao, ZHOU Jinsong. Pre-scanning Algorithm of Railway Track Curvature and Analysis of Geometric Lag Principle[J]. Journal of Mechanical Engineering, 2023, 59(10): 301-310.

References

[1] MEI T X,GOODALL R M. Recent development in active steering of railway vehicles[J]. Vehicle System Dynamics,2003,39(6):415-436.
[2] PEREZ J,BUSTURIA J M,GOODALL R M. Control strategies for active steering of bogie-based railway vehicles[J]. Control Engineering Practice,2002,10(9):1005-1012.
[3] SHEN G,GOODALL R. Active yaw relaxation for improved bogie performance[J]. Vehicle System Dynamics,1997,28(4-5):273-289.
[4] TIAN S Q,LUO X P,REN L H,et al. Active steering control strategy for rail vehicle based on minimum wear number[J]. Vehicle System Dynamics,2020,59(8):1256-1281.
[5] 王雪梅. 摆式列车线路信息检测系统关键技术研究[D].成都:西南交通大学,2007. WANG Xuemei. Researches on the key technologies of railway line information measurement system of tilting train[D]. Chengdu:Southwest Jiaotong University,2007.
[6] 曹新苗. 基于GPS_DR的列车定位系统研究[D]. 成都:西南交通大学,2012. CAO Xinmiao. Research on train positioning system based on GPS_DR[D]. Chengdu:Southwest Jiaotong University,2012.
[7] 周达天. 基于多传感器信息融合的列车定位方法研究[D]. 北京:北京交通大学,2007. ZHOU Datian. Research on multi-sensor information fusion based train location method[D]. Beijing:Beijing Jiaotong University,2007.
[8] 王雪梅,倪文波,李芾. 基于陀螺平台的摆式列车线路信息检测系统研究[J]. 中国铁道科学,2004(1):42-46. WANG Xuemei,NI Wenbo,LI Fei. Research on gyroscope platform based tilting train railway line information inspection system[J]. China Railway Science,2004(1):42-46.
[9] 王雪梅,倪文波,李芾,等. 摆式列车线路检测信号的动态自适应滤波研究[J]. 中国铁道科学,2005(5):76-81. WANG Xuemei,NI Wenbo,LI Fei,et al. Kalman dynamic adaptive filtering to railway line measurement signals of tilting train[J]. China Railway Science,2005(5):76-81.
[10] SIM K S,HUR H M,SONG H S,et al. Study of the active radial steering of a railway vehicle using the curvature measuring method[J]. Journal of Mechanical Science and Technology,2014,28(11):4583-4591.
[11] TIAN S Q,LUO X P,REN L H,et al. Active radial system of railway vehicles based on secondary suspension rotation angle sensing[J]. Vehicle System Dynamics,2020,59(5):765-784.
[12] TIAN S Q,LUO X P,XIAO C Y,et al. Real time measurement of track curvature based on vehicle attitude perception[J]. Vehicle System Dynamics,2022,DOI:10.1080/00423114.2022.2047211.
[13] KALELI F,AKGUL Y S. Vision-based railroad track extraction using dynamic programming[C]//International IEEE Conference on Intelligent Transportation Systems. St. Louis,MO,New York:IEEE,2009.
[14] QI Z Q,TIAN Y J,SHI Y. Efficient railway tracks detection and turnouts recognition method using HOG features[J]. Neural Computing & Applications,2013,23(1):245-254.
[15] 张蕾. 红外图像中铁轨识别技术的研究[D]. 成都:电子科技大学,2012. ZHANG Lei. Research on rail recognition technology in infrared image[D]. Chengdu:University of Electronic Science and Technology of China,2012.
[16] 黄凯. 基于红外图像的铁轨提取及运动目标的检测[D]. 成都:电子科技大学,2013. HUANG Kai. The tracks extraction and moving target detection in infrared images[D]. Chengdu:University of Electronic Science and Technology of China,2013.
[17] NASSU B T,UKAI M. Rail extraction for driver support in railways[C]//Intelligent Vehicles Symposium (IV),2011 IEEE. New York:IEEE,2011.
[18] ROSS R. Track and turnout detection in video-signals using probabilistic spline curves[C]//International IEEE Conference on Intelligent Transportation Systems. New York:IEEE,2012.
[19] FAN G,BO L I,HAN Q,et al. Robust lane detection and tracking based on machine vision[J]. ZTE Communications,2020,18(4):69-77.
[20] BERG A,ÖFJÄLL K,AHLBERG J,et al. Detecting rails and obstacles using a train-mounted thermal camera[M]. Image Analysis. Berlin:Springer International Publishing,2015.
[21] 王云泽. 列车前方轨道识别算法的设计与实现[D]. 杭州:浙江大学,2017. WANG Yunze. Design and implementation of an algorithm to recognize the rail ahead of the train[D]. Hangzhou:Zhejiang University,2017.
[22] RAM K,KHARVAL C,HARITHAS S S,et al. RP-VIO:Robust plane-based visual-inertial odometry for dynamic environments[C]//2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). New York:IEEE,2021:9198-9205.
[23] VON STUMBERG L,CREMERS D. DM-VIO:Delayed marginalization visual-inertial odometry[J]. IEEE Robotics and Automation Letters,2022,7(2):1408-1415.
[24] 娄平,曾庆元. 利用缓和曲线的曲率确定其方程式的通用方法[J]. 铁道学报,2003,25(3):104-106. LOU Ping,ZENG Qingyuan. A general method for determining transition curve equations by means of the curvature of transition curve[J]. Journal of the China Railway Society,2003,25(3):104-106.
[25] 中华人民共和国住房与城乡建设部,中华人民共和国国家质量监督检验检疫总局. GB 50157-2013 地铁设计规范[S]. 北京:中国标准出版社,2013. Ministry of Housing and Urban-Rural Development of the People's Republic of China,General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China. GB 50157-2013 Code for design of metro[S]. Beijing:Standards Press of China,2013.