Performance and Challenges in Utilizing Non-Intrusive Sensors for Traffic Data Collection

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Advances in Remote Sensing

ISSN Print: 2169-267X
ISSN Online: 2169-2688
www.scirp.org/journal/ars
E-mail: ars@scirp.org

Google-based Impact Factor: 1.94
Citations

Journals Menu

"Performance and Challenges in Utilizing Non-Intrusive Sensors for Traffic Data Collection"
written by Xin Yu, Panos D. Prevedouros,
published by Advances in Remote Sensing, Vol.2 No.2, 2013

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Combining Deep Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification
	ACM Transactions on Computing for …, 2024

[2]	Collaborative Parking Vacancy Prediction for Cities With Partial Sensors Missing
	IEEE Transactions on …, 2024

[3]	Roadside Sensors for Traffic Management
	IEEE Intelligent Transportation Systems Magazine, 2024

[4]	Visual Sensing for Comprehensive Granular Traffic Data Collection in Support of Intelligent Transportation Applications
	2023

[5]	Machine Learning-Based Classification of Digital Media Traffic
	2023

[6]	An improved tucker decomposition‐based imputation method for recovering lane‐level missing values in traffic data
	IET Intelligent Transport …, 2022

[7]	Towards Data-Supported Urban Mobility Management
	2022

[8]	Lane-level heterogeneous traffic flow prediction: A spatiotemporal attention-based encoder–decoder model
	IEEE Intelligent …, 2022

[9]	A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification.
	Comput. Syst. Sci …, 2022

[10]	Identification of Road Traffic from Multiple Sources Using Modern Gaussian Approach
	Proceedings of the …, 2022

[11]	Sensing technologies for traffic flow characterization: From heterogeneous traffic perspective
	Journal of Applied …, 2022

[12]	ITSs for Transnational Road Traffic Detection: An Opportunity for More Reliable Data
	International Conference on …, 2021

[13]	Dynamically Collected Local Density using Low-Cost Lidar and its Application to Traffic Models
	2021

[14]	Tangible fidgeting interfaces for mental wellbeing recognition using deep learning applied to physiological sensor data
	2021

[15]	Weakly Supervised Performance Evaluation of Trajectory Clustering
	2021

[16]	Traffic Volume Prediction: A Fusion Deep Learning Model Considering Spatial–Temporal Correlation
	Sustainability, 2021

[17]	A novel hybrid model for predicting traffic flow via improved ensemble learning combined with deep belief networks
	Mathematical Problems in …, 2021

[18]	Impedance measures in evaluating accessibility change
	2020

[19]	Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification
	2020

[20]	Freeway Short-Term Travel Speed Prediction Based on Data Collection Time-Horizons: A Fast Forest Quantile Regression Approach
	2020

[21]	Evaluation of Short-Term Freeway Speed Prediction Based on Periodic Analysis Using Statistical Models and Machine Learning Models
	2020

[22]	ROAD TRAFFIC SPEED PREDICTION: A PROBABILISTIC MODEL FUSING MULTISOURCE DATA
	2020

[23]	Data Fusion for Multi-Source Sensors Using GA-PSO-BP Neural Network
	2020

[24]	Capturing vehicular headway using low-cost LIDAR and processing through ARIMA prediction modeling
	2019

[25]	Prediction of Road Traffic using Naive Bayes Algorithm
	International journal of engineering research and technology, 2019

[26]	Role of Data Fusion Prediction of Road Traffic Speed
	2019

[27]	Characterizing Driving Behavior by using LIDAR and GPS through Traffic Stream Models.
	2019

[28]	Characterizing Driving Behavior by Using LIDAR and GPS Through Traffic Stream Models
	2019

[29]	Capturing vehicular space headway using low-cost LIDAR and processing through ARIMA prediction modeling
	2019

[30]	Truck Body-Type Classification using Single-Beam Lidar Sensors
	2019

[31]	Short-term prediction of lane-level traffic speeds: A fusion deep learning model
	2019

[32]	Evaluation of Accuracy of the Infra-Red Traffic Logger Under Mix Traffic Condition
	2019

[33]	Capturing vehicular headway using low-cost LIDAR and processing through ARIMA prediction
	2019

[34]	Developing an algorithm to assess the rear-end collision risk under fog conditions using real-time data
	Transportation Research Part C: Emerging Technologies, 2018

[35]	Road traffic speed prediction: a probabilistic model fusing multi-source data
	2018

[36]	On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels
	Sensors, 2018

[37]	Guidance for Field and Sensor-Based Measurement of HCM and Simulation Performance Measures
	2018

[38]	Crowdsourced traffic information in traffic management: Evaluation of traffic information from Waze
	2018

[39]	An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic
	2017

[40]	Short-Term Speed Prediction Using Remote Microwave Sensor Data: Machine Learning versus Statistical Model
	Mathematical Problems in Engineering, 2016

[41]	Information-Aided Smart Schemes for Vehicle Flow Detection Enhancements of Traffic Microwave Radar Detectors
	Applied Sciences, 2016

[42]	Virtual Reality (VR)–A Better View for Visualizing the Flats
	International Journal of Science Technology & Engineering, 2016

[43]	MOŽNOST UVEDBE SODOBNIH TEHNOLOGIJ V IZREDNO ŠTETJE PROMETA
	2015

[44]	Data Mining of Social Media for Traffic Monitoring
	IJSRD - International Journal for Scientific Research & Development, 2015

[45]	Long short-term memory neural network for traffic speed prediction using remote microwave sensor data
	Transportation Research Part C: Emerging Technologies, 2015

[46]	The Study of Vehicle Classification Equipment with Solutions to Improve Accuracy in Oklahoma
	2014

[47]	Vehicle classification accuracy of AVC and WIM sites in Oklahoma
	Intelligent Vehicles Symposium Proceedings, 2014 IEEE, 2014

[48]	Road Traffic Congestion Monitoring in Social Media with Hinge-Loss Markov Random Fields
	Data Mining (ICDM), 2014 IEEE International Conference on, 2014

[49]	A multifaceted relationship between congestion and accidents on highways: evidence from D-100 highway in Istanbul
	2014

[50]	THE STUDY OF VEHICLE CLASSIFICATION EQUIPMENT WITH SOLUTIONS TO IMPROVE ACCURACY IN OKLAHOMA–PHASE (2)
	2014

[51]	The study of vehicle classification equipment with solutions to improve accuracy in Oklahoma.
	2014

[1]	Combining Deep Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification ACM Transactions on Computing for Healthcare, 2024 DOI:10.1145/3631618

[2]	Research on the algorithm of helmet-wearing detection based on the optimized yolov4 The Visual Computer, 2023 DOI:10.1007/s00371-022-02471-9

[3]	Lane-Level Heterogeneous Traffic Flow Prediction: A Spatiotemporal Attention-Based Encoder–Decoder Model IEEE Intelligent Transportation Systems Magazine, 2023 DOI:10.1109/MITS.2022.3224218

[4]	An improved tucker decomposition‐based imputation method for recovering lane‐level missing values in traffic data IET Intelligent Transport Systems, 2022 DOI:10.1049/itr2.12148

[5]	Research on the algorithm of helmet-wearing detection based on the optimized yolov4 The Visual Computer, 2022 DOI:10.1007/s00371-022-02471-9

[6]	Impedance measures in evaluating accessibility change Geocarto International, 2022 DOI:10.1080/10106049.2020.1869327

[7]	Proceedings of the International Conference on Cognitive and Intelligent Computing Cognitive Science and Technology, 2022 DOI:10.1007/978-981-19-2350-0_35

[8]	A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification Computer Systems Science and Engineering, 2022 DOI:10.32604/csse.2022.018430

[9]	Dynamically Collected Local Density using Low-Cost Lidar and its Application to Traffic Models Transportation Research Record: Journal of the Transportation Research Board, 2021 DOI:10.1177/03611981211010184

[10]	Computational Science and Its Applications – ICCSA 2021 Lecture Notes in Computer Science, 2021 DOI:10.1007/978-3-030-86960-1_25

[11]	Traffic Volume Prediction: A Fusion Deep Learning Model Considering Spatial–Temporal Correlation Sustainability, 2021 DOI:10.3390/su131910595

[12]	Data Fusion for Multi-Source Sensors Using GA-PSO-BP Neural Network IEEE Transactions on Intelligent Transportation Systems, 2021 DOI:10.1109/TITS.2020.3010296

[13]	A Novel Hybrid Model for Predicting Traffic Flow via Improved Ensemble Learning Combined with Deep Belief Networks Mathematical Problems in Engineering, 2021 DOI:10.1155/2021/7328056

[14]	Freeway Short-Term Travel Speed Prediction Based on Data Collection Time-Horizons: A Fast Forest Quantile Regression Approach Sustainability, 2020 DOI:10.3390/su12020646

[15]	Evaluation of Short-Term Freeway Speed Prediction Based on Periodic Analysis Using Statistical Models and Machine Learning Models Journal of Advanced Transportation, 2020 DOI:10.1155/2020/9628957

[16]	Distributed Computing for Emerging Smart Networks Communications in Computer and Information Science, 2020 DOI:10.1007/978-3-030-65810-6_1

[17]	Truck Body-Type Classification using Single-Beam Lidar Sensors Transportation Research Record: Journal of the Transportation Research Board, 2019 DOI:10.1177/0361198118821847

[18]	Short-term prediction of lane-level traffic speeds: A fusion deep learning model Transportation Research Part C: Emerging Technologies, 2019 DOI:10.1016/j.trc.2019.07.003

[19]	Evaluation of Accuracy of the Infra-Red Traffic Logger Under Mix Traffic Condition 2019 Moratuwa Engineering Research Conference (MERCon), 2019 DOI:10.1109/MERCon.2019.8818936

[20]	Developing an algorithm to assess the rear-end collision risk under fog conditions using real-time data Transportation Research Part C: Emerging Technologies, 2018 DOI:10.1016/j.trc.2017.12.012

[21]	On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels Sensors, 2018 DOI:10.3390/s18030837

[22]	Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data IEEE Transactions on Knowledge and Data Engineering, 2018 DOI:10.1109/TKDE.2017.2718525

[23]	An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic IEEE Transactions on Intelligent Transportation Systems, 2017 DOI:10.1109/TITS.2016.2643005

[24]	Short-Term Speed Prediction Using Remote Microwave Sensor Data: Machine Learning versus Statistical Model Mathematical Problems in Engineering, 2016 DOI:10.1155/2016/9236156

[25]	Information-Aided Smart Schemes for Vehicle Flow Detection Enhancements of Traffic Microwave Radar Detectors Applied Sciences, 2016 DOI:10.3390/app6070196

[26]	Long short-term memory neural network for traffic speed prediction using remote microwave sensor data Transportation Research Part C: Emerging Technologies, 2015 DOI:10.1016/j.trc.2015.03.014

[27]	Road Traffic Congestion Monitoring in Social Media with Hinge-Loss Markov Random Fields 2014 IEEE International Conference on Data Mining, 2014 DOI:10.1109/ICDM.2014.139

[28]	Vehicle classification accuracy of AVC and WIM sites in Oklahoma 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014 DOI:10.1109/IVS.2014.6856438

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Advances in Remote Sensing

Advances in Remote Sensing

Journals Menu

Home

About SCIRP

Service

Policies