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A Dynamic Data Driven Application System for Vehicle Tracking

Richard Fujimoto, Angshuman Guin, Michael Hunter, Haesun Park, Gaurav Kanitkar, Ramakrishnan Kannan, Michael Milholen, SaBra Neal, Philip Pecher
2014 Procedia Computer Science  
A dynamic data driven application system (DDDAS) is described to track a vehicle's movements by repeatedly identifying the vehicle under investigation from live image and video data, predicting probable  ...  Tracking the movement of vehicles in urban environments using fixed position sensors, mobile sensors, and crowd-sourced data is a challenging but important problem in applications such as law enforcement  ...  Acknowledgement Funding for this project was provided by AFOSR Grant FA9550-13-1-0100.  ... 
doi:10.1016/j.procs.2014.05.108 fatcat:ujy32vhi5rfbhhjmuisxdfivma

Special Issue: Dynamic Data-Driven Applications Systems (DDDAS) Concepts in Signal Processing

Erik Blasch, Shashi Phoha
2017 Journal of Signal Processing Systems  
Dynamic Data Driven Applications Systems (DDDAS) is a transformative framework for incorporating evolving data into a dynamic system to adapt to operational conditions, and recursively to steer its measurement  ...  New insights have been developed for measurement systems with unobservable data, such as new architectures to emulate data collections for missing data.  ...  Dynamic Data Driven Applications Systems (DDDAS) is a transformative framework for incorporating evolving data into a dynamic system to adapt to operational conditions, and recursively to steer its measurement  ... 
doi:10.1007/s11265-017-1253-7 fatcat:4gnderwjibgupiudcq5aedqkxi

Advanced Estimation Techniques for Vehicle System Dynamic State: A Survey

Jin, Yin, Chen
2019 Sensors  
In order to improve handling stability performance and active safety of a ground vehicle, a large number of advanced vehicle dynamics control systems—such as the direct yaw control system and active front  ...  This paper presents a comprehensive technical survey of the development and recent research advances in vehicle system dynamic state estimation.  ...  Moreover, the data-driven-based estimation possesses the potential to enhance vehicle dynamics state estimation, and the additional attention on developments and applications of data-driven-based estimation  ... 
doi:10.3390/s19194289 fatcat:orxcpccbx5bqtorvfumxjcdguu

Tests of Monitoring of Motion Variables of Unmanned Vehicle Convoy

2019 International journal of recent technology and engineering  
This work analyzes test results of motion control system of unmanned cargo vehicles convoy with manned master vehicle developed by NAMI Institute.  ...  State coordinates of vehicles were determined by virtual data sensors based on indirect measurements using mathematical models and solution algorithms of ill-posed problems.  ...  Application of computer vision systems for monitoring vehicle position on the road, determination of distance to obstacles, and recognition of road markings is restricted by illumination, precipitations  ... 
doi:10.35940/ijrte.d9526.118419 fatcat:wttadjy2nbez3djlhf4czjsfjm

Cloud-Based Information Technology Framework for Data Driven Intelligent Transportation Systems

Arshdeep Bahga, Vijay K. Madisetti
2013 Journal of Transportation Technologies  
We present a novel cloud based IT framework, CloudTrack, for data driven intelligent transportation systems.  ...  A dynamic vehicle routing approach is adopted where the alerts trigger the generation of new routes.  ...  Cloud-Track can support a wide variety of dynamic vehicle routing algorithms; 4) A cloud-based vehicle location and container conditions tracking Software as a Service (SaaS).  ... 
doi:10.4236/jtts.2013.32013 fatcat:kg4skrndljgsnmzq47vfhkko24

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing

John P. Kerekes, Michael D. Presnar, Kenneth D. Fourspring, Zoran Ninkov, David R. Pogorzala, Alan D. Raisanen, Andrew C. Rice, Juan R. Vasquez, Jeffrey P. Patel, Robert T. MacIntyre, Scott D. Brown, Sylvia S. Shen (+1 others)
2009 Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV  
Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor.  ...  Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.  ...  DYNAMIC SCENE MODELING Hyperspectral image modeling in DIRSIG The object tracking algorithms for this study were tested on a data set consisting of a series of synthetically-generated image frames encoded  ... 
doi:10.1117/12.819265 fatcat:ocjrelp5yvfynnpshs3lrrbaw4

V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures [article]

Hossein Nourkhiz Mahjoub, Behrad Toghi, S M Osman Gani, Yaser P. Fallah
2019 arXiv   pre-print
In this work, based on the MBC notion, a technology-agnostic hybrid model selection policy for Vehicle-to-Everything (V2X) communication is proposed which benefits from the characteristics of the non-parametric  ...  the proper operation of the critical cooperative safety applications.  ...  Gaussian Processes: A Fully Data Driven non-parametric Bayesian Modeling Approach The record of different vehicle dynamics could be regarded as separate time-series which should be regressed using an appropriate  ... 
arXiv:1903.01576v2 fatcat:sxcdhjjddbctvd4nekb4vdz2xe

A Deep-Learning Framework to Predict the Dynamics of a Human-Driven Vehicle Based on the Road Geometry [article]

Luca Paparusso, Stefano Melzi, Francesco Braghin
2021 arXiv   pre-print
In this work, a deep-learning framework is proposed to model and predict the evolution of the coupled driver-vehicle system dynamics.  ...  It fuses the information on the road geometry and the past driver-vehicle system dynamics to produce context-aware predictions.  ...  This choice forces the network to learn the driver-vehicle system dynamics, and infuses a natural generalisation into the data-driven approach.  ... 
arXiv:2103.03825v1 fatcat:lhb25m5tffe2xk45nao44ir5yi

Hybrid Prognosis for Railway Health Assessment: An Information Fusion Approach for PHM Deployment

D. Galar, U. Kumar, R. Villarejo, C.A. Johansson
2013 Chemical Engineering Transactions  
As there are many prognostic techniques, usage must be attuned to particular applications. Broadly stated, prognostic methods are either data-driven or model-based.  ...  Therefore, hybrid models are extremely useful for accurately estimating the Remaining Useful Life (RUL) of railway systems.  ...  This paper is a modified version of a plenary keynote presented in CM 2013 and MFPT 2013, The Tenth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies.  ... 
doi:10.3303/cet1333129 doaj:94c2d745f63e40ce896419d51597a0fe fatcat:t5ygpvite5gwjfvjhru27t6fdq

A data-driven dynamics simulation framework for railway vehicles

Yinyu Nie, Zhao Tang, Fengjia Liu, Jian Chang, Jianjun Zhang
2017 Vehicle System Dynamics  
To maintain the advantages of both the two methods, this paper proposes a data-driven simulation framework to model the dynamic behaviours of railway vehicles.  ...  Sophisticated finite element (FE) model are usually critical for the research and simulation of vehicle dynamics, especially for train crash cases.  ...  For instance, the application of scaled roller rigs for railway vehicle bogies has got a widespread development in studying the dynamics since an early age, and now it still shows prospects in designing  ... 
doi:10.1080/00423114.2017.1381981 fatcat:grulabet45bm7dlcjlneqsv5s4

Contents

2021 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)  
Control of 3-DOF Helicopter Based on Command Filter and Neural Network Techniques ……………………………………………………………………………… Liang Liu, Yibo Su, Jiaming Lu 613 Data-driven Tracking Control for a Class of Unknown  ...  Optoelectronic Tracking System……………………………………………………………Kang Nie, Zhijun Li, Tong Guo, Yao Mao 360 Manufacturing Big Data Modeling Based on KNN-LR Algorithm and Its Application in Product Design Business  ... 
doi:10.1109/ddcls52934.2021.9455485 fatcat:7n7tpgqsuvg55og6dwwuj6g2xe

Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design

Yifeng Wang, Ping Wang, Zihan Li, Zhengxing Chen, Qing He
2020 Journal of Advanced Transportation  
In this study, a data-driven interior noise prediction model is developed for vehicles on an urban rail transit system based on random forest (RF) and a vehicle/track coupling dynamic model (VTCDM).  ...  First, a data collection framework via embedded sensors of onboard smartphones was developed.  ...  track system.  ... 
doi:10.1155/2020/5896739 fatcat:3ecgeuq26bapbb23ei6ycrpqfy

Scanning the Issue

Petros Ioannou, A. V. Bal Balakrishnan
2018 IEEE transactions on intelligent transportation systems (Print)  
The authors build a general model to optimally allocate power tracks and determine the vehicle battery size for each route.  ...  The dynamic wireless charging (DWC) technology, a novel way of supplying vehicles with electric energy, allows the vehicle battery to be recharged remotely while it is moving over power tracks, which are  ...  A data-driven dynamic management mechanism is then proposed, which is highly effective on realizing resilient fleet management.  ... 
doi:10.1109/tits.2018.2837698 fatcat:lkfmjyqrunbvfc5gohu4nyar4e

Mission-driven autonomous perception and fusion based on UAV swarm

He You
2020 Chinese Journal of Aeronautics  
Considering the application environment being usually characterized by strong confrontation, high dynamics, and deep uncertainty, the distributed situational awareness system based on UAV swarm needs to  ...  Distributed autonomous situational awareness is one of the most important foundation for Unmanned Aerial Vehicle (UAV) swarm to implement various missions.  ...  Mission-driven Autonomous Perception and Fusion (MAPF) In a complex and highly dynamic network environment, the autonomous perception and fusion system based on UAV swarm needs to guarantee optimization  ... 
doi:10.1016/j.cja.2020.02.027 fatcat:dlhxm3nig5gntldxw6fyhgwiam

2020 Index IEEE Transactions on Control Systems Technology Vol. 28

2020 IEEE Transactions on Control Systems Technology  
., +, TCST Jan. 2020 208-223 Robust Calibration of High Dimension Nonlinear Dynamical Models for Omics Data: An Application in Cancer Systems Biology.  ...  ., +, TCST Jan. 2020 106-117 Robust Calibration of High Dimension Nonlinear Dynamical Models for Omics Data: An Application in Cancer Systems Biology.  ...  Optimal Detection Schemes for Multiplicative Faults in Uncertain Systems With Application to Rolling Mill Processes. Li, L., +, 2432 -2444  ... 
doi:10.1109/tcst.2020.3047034 fatcat:iin2gzukmbadhbln2qf25c4v6a
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