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Modern Condition Monitoring Systems for Railway Wheel set Dynamics: Performance Analysis and Limitations of Existing Techniques

Khakoo Mal, Imtiaz Hussain, Tayab Din Memon, Dileep Kumar, Bhawani Shankar Chowdhry
2022 Sir Syed Research Journal of Engineering & Technology  
The core element of a CMS is the use of suitable algorithms to evaluate system behavior for achieving a solution to avoid accidents involving railway vehicles.  ...  CMS for railway vehicles involves techniques including model-based and signal-based techniques for the detection of faults which assists preventing the system from any major failure.  ...  In the above analysis, model-based CMS techniques using discrete Kalman filter or simple KF, Bucy-Kalman filter (the continuous-time counterpart of Kalman filter), EKF (an extended form of Kalman filter  ... 
doi:10.33317/ssurj.419 fatcat:3l4jcshcwbawnoeflyo4kb5qgu

Vehicle Tracking Using Video Surveillance [chapter]

Sandesh Shrestha
2020 Intelligent System and Computing  
Using computer vision and deep learning algorithms, the project deals with the concept of vehicle tracking in real-time based on continuous video stream from a CCTV camera to track the vehicles.  ...  By implementing and improving the ideas of Deep SORT tracking for better occlusion handling, a better tracking system suitable for real-time vehicle tracking is presented.  ...  Acknowledgements This work is carried out at Internet of Things (IoT) Lab, Industrial Systems Engineering Department, Asian Institute of Technology, Thailand. 17 Vehicle Tracking Using Video Surveillance  ... 
doi:10.5772/intechopen.89405 fatcat:f37xnqq5kbgihmabiqr7xlq6jq

Vehicle State Estimation Based on Strong Tracking Central Different Kalman Filter

Yingjie Liu, Qijiang Xu, Jingxia Sun, Fapeng Shen, Dawei Cui, Yongmin Zhong
2021 Mathematical Problems in Engineering  
central different Kalman filter (CDKF).  ...  Based on the purpose, a 3-DOF nonlinear vehicle dynamics model containing constant noise and a nonlinear tire model were established, and several vehicle key states were estimated by a strong tracking  ...  In research on algorithms of vehicle driving state parameter estimation, most algorithms use Kalman filtering to estimate vehicle states. e advantage of Kalman filtering is that it can solve the linear  ... 
doi:10.1155/2021/4126961 fatcat:rqoqm2xaqveq7clc7hxnmwjfrm

Fluid-inspired field representation for risk assessment in road scenes

Xuanpeng Li, Lifeng Zhu, Qifan Xue, Dong Wang, Yongjie Jessica Zhang
2020 Computational Visual Media  
It proves a promising approach for collision risk assessment in road scenes.  ...  Objects' state spaces are used as the boundary conditions in the simulation of advection and diffusion processes.  ...  Then, the Kalman filter was adopted to track multiple objects and corrected trajectories were used to assess collision risk based on the fluid model.  ... 
doi:10.1007/s41095-020-0190-8 fatcat:gnmdjhlk35dhtpelhvjskqkm2q

Tire Road Friction Coefficient Estimation: Review and Research Perspectives

Yan Wang, Jingyu Hu, Fa'an Wang, Haoxuan Dong, Yongjun Yan, Yanjun Ren, Chaobin Zhou, Guodong Yin
2022 Chinese Journal of Mechanical Engineering  
AbstractMany surveys on vehicle traffic safety have shown that the tire road friction coefficient (TRFC) is correlated with the probability of an accident.  ...  These methods are divided into three main categories: off-board sensors-based, vehicle dynamics-based, and data-driven-based methods.  ...  model inversion [73] 18 Single-track vehicle model High-order sliding mode differentiator. [89] 19 Single-track vehicle model Unscented Kalman filter [83] Table 3 3 Summary of estimation methods based  ... 
doi:10.1186/s10033-021-00675-z fatcat:3zxr5ezxy5djrp6pehoobropxm

Lane Departure Prediction Based on Closed-Loop Vehicle Dynamics [article]

Daofei Li, Siyuan Lin, Guanming Liu
2022 arXiv   pre-print
We use extended Kalman filter to estimate the current vehicle states based on sensing module outputs.  ...  Then a Kalman Predictor with actual lane keeping control law is used to predict steering actions and vehicle states in the future.  ...  Acknowledgements The authors appreciated Anfei Zha for his help in carrying out the real vehicle experiments, and Linhui Chen for his help in preparing the video abstract.  ... 
arXiv:2112.10379v2 fatcat:nw4jbapztfayjp4yjb46jv6c2i

Travel Time Estimation and Prediction using Mobile Phones: A Cost Effective Method for Developing Countries

Satyakumar M., Anil R., Sivakumar B.
2014 Civil Engineering Dimension  
Personnel were employed in public transit vehicles with mobile phones and these mobile phones were tracked continuously.  ...  This project examines the use of mobile phones for travel time prediction of public transit vehicles and develops a dynamic travel time prediction model.  ...  It uses online mapping facilities to track the vehicles and it can also track different vehicles simultaneously.  ... 
doi:10.9744/ced.16.1.33-39 fatcat:4yq6brc3e5dqfctwh54bdsfqd4

Context-Aware Misbehavior Detection Scheme for Vehicular Ad Hoc Networks using Sequential Analysis of the Temporal and Spatial Correlation of the Cooperative Awareness Messages [article]

Fuad A. Ghaleb
2019 arXiv   pre-print
Firstly, the Kalman filter algorithm is used to track the mobility information received from neighboring vehicles.  ...  Then, the innovation errors of the Kalman filter are utilized to construct a temporal consistency assessment model for each vehicle using Box-plot.  ...  Kalman Filter to track the messages of all neighbouring vehicles.  ... 
arXiv:1904.01392v1 fatcat:dqtd4mn6rvhjne7r3hx7mqruoy

Data Fusion for ITS: Techniques and Research Needs

Nour-Eddin El Faouzi, Lawrence A. Klein
2016 Transportation Research Procedia  
Data fusion techniques applied to date include Bayesian inference, Dempster-Shafer evidential reasoning, artificial neural networks, fuzzy logic, and Kalman filtering.  ...  sensors, and in the future, connected vehicles enable multisource data fusion to be exploited to produce an enhanced interpretation of the monitored or observed situation.  ...  Cremer and Schrieber (1996) studied the integration of in-vehicle information and loop detector data using the extended Kalman filter.  ... 
doi:10.1016/j.trpro.2016.06.042 fatcat:eyw3hlcnn5c3fnlig2i5gvsshe

Vision-Based Approaches of the Small Satellites Relative Navigation

Tuncay Yunus Erkec, Chingiz Hajiyev
2021 WSEAS Transactions on Computer Research  
Advancements dependent on this technique are utilized separately or joined with oneanother to deal with relative position issues.  ...  Various strategies and approaches exist andneed distinctive assessment and advanced algorithms for variation, control, and sensor combination.  ...  In a sensor-fusion, an Extended Kalman Filter (EKF) is improved for the speed position and conduct assessment of a satellite/flying vehicle utilizing minimal expense sensors made by a sensorcombination  ... 
doi:10.37394/232018.2021.9.3 fatcat:j2arbguobzcvfazbhbw5u75aim

Extraction and Assessment of Naturalistic Human Driving Trajectories from Infrastructure Camera and Radar Sensors [article]

Dominik Notz, Felix Becker, Thomas Kühbeck, Daniel Watzenig
2020 arXiv   pre-print
We improve a state-of-the-art object tracker by combining the tracking in image coordinates with a Kalman filter in road coordinates.  ...  For that, we equip our test vehicle with a differential GPS sensor and use it to collect ground truth trajectories. With this data we compute the measurement errors.  ...  ACKNOWLEDGMENT We would like to thank Anthony Acker, Andrew Dickens, Mehmet Inönü, Sebastian Kienitz, Florian Münch, and Brad Siedner for their support with the construction of the hardware prototype and  ... 
arXiv:2004.01288v1 fatcat:oitbgzsonnbl7nl7madverj5xy

Fusion of heterogeneous sensors for the guidance of an autonomous vehicle

J.C. Becker
2000 Proceedings of the Third International Conference on Information Fusion  
An adaptive information filter is used for the fusion of the associated targets from different sensors.  ...  The sensor system is designed to totally cover the vehicle environment with a high redundancy in front of the vehicle.  ...  A target which has already been associated with another track (case 1) is used to update the existing track.  ... 
doi:10.1109/ific.2000.859865 fatcat:idnavyv4draqpotye5c3m2tf64

Towards Autonomous Driving: a Multi-Modal 360^∘ Perception Proposal [article]

Jorge Beltrán, Carlos Guindel, Irene Cortés, Alejandro Barrera, Armando Astudillo, Jesús Urdiales, Mario Álvarez, Farid Bekka, Vicente Milanés, Fernando García
2020 arXiv   pre-print
Lastly, a tracking stage based on Unscented Kalman Filter is used to track the agents along time.  ...  A wide variety of tests of the system, deployed in an autonomous vehicle, have successfully assessed the suitability of the proposed perception stack in a real autonomous driving application.  ...  Most tracking approaches for onboard perception are based on particle [14] or Kalman [15] filters.  ... 
arXiv:2008.09672v1 fatcat:ugky2irhlzadvcsdsfe2f2sv7u

Modern techniques for condition monitoring of railway vehicle dynamics

R W Ngigi, C Pislaru, A Ball, F Gu
2012 Journal of Physics, Conference Series  
Section two presents the model-based techniques (Kalman filters; extended Kalman filter; sequential Monte Carlo method (Rao-Blackwellised particle filter)) used to estimate the dynamics of the rail vehicle  ...  They examined the validity of the approach by investigating the secondary lateral damper and spring failure in railway vehicles using Kalman filter as a mode-matching filter.  ... 
doi:10.1088/1742-6596/364/1/012016 fatcat:dmruuygndfdurkgktmbhpchht4

A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

Zizhou Lao, Bizhong Xia, Wei Wang, Wei Sun, Yongzhi Lai, Mingwang Wang
2018 Energies  
Combined with an unscented Kalman filter (UKF) algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation.  ...  Energies 2018, 11, 1358 2 of 15 nonlinear Kalman filter [4-9], particle filtering (PF) [10, 11] , sliding mode observer (SMO) [12, 13] , the H ∞ filter [14, 15] , and so on [16] .  ...  recursive least squares unscented Kalman filter (FFRLS-UKF) 3 variable forgetting factor recursive least squares unscented Kalman filter (VFF-RLS-UKF) 4 root-mean-square error (RMSE)  ... 
doi:10.3390/en11061358 fatcat:hanau5o4fnbs5p5datevaec2me
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