16.7.2.7 Traffic Flow Models and Analysis, Not Image Based

Chapter Contents (Back)
Traffic Flow. Smart Highways. Applications to traffic flow analysis from other than image data. Predictions:
See also Traffic Flow Prediction, Forecast.
See also Traffic Flow Analysis, GPS, GNSS.
See also Shared Ride Systems, Car Sharing, Taxi, Analysis.
See also Traffic Control, Traffic Analysis, Not Image Analysis.
See also Urban Mobility Analysis.
See also Transit Traffic Analysis, Public Transit, Bus.
See also Surveillance of Vehicles and Occupants, Driver Monitoring.
See also Traffic Surveillance, Analysis of Traffic.
See also Traffic, Routing, Evaluation.
See also Transportation Mode, Travel Mode, Transport Mode Detection. More people than vehicles:
See also Human Activities, Tourist Traffic Flow.

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BibRef

Ma, Y.S.[Yong-Sai], Wang, Y.[Yang], Xu, G.L.[Guang-Luan], Tai, X.Q.[Xian-Qing],
Multilevel Visualization of Travelogue Trajectory Data,
IJGI(7), No. 1, 2018, pp. xx-yy.
DOI Link 1801
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Li, L.C.[Lin-Chao], Zhang, J.[Jian], Yang, F.[Fan], Ran, B.[Bin],
Robust and flexible strategy for missing data imputation in intelligent transportation system,
IET-ITS(12), No. 2, March 2018, pp. 151-157.
DOI Link 1801
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Arguedas, V.F.[V. Fernandez], Pallotta, G., Vespe, M.,
Maritime Traffic Networks: From Historical Positioning Data to Unsupervised Maritime Traffic Monitoring,
ITS(19), No. 3, March 2018, pp. 722-732.
IEEE DOI 1804
Artificial intelligence, Data mining, Navigation, Security, Sensors, Surveillance, AIS, Maritime traffic representation, traffic monitoring BibRef

Samani, Z.N.[Zeinab Neisani], Karimi, M.[Mohammad], Alesheikh, A.A.[Ali Asghar],
A Novel Approach to Site Selection: Collaborative Multi-Criteria Decision Making through Geo-Social Network (Case Study: Public Parking),
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804
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Kong, S.H., Jeon, S.Y.,
Cooperative Positioning Technique With Decentralized Malicious Vehicle Detection,
ITS(19), No. 3, March 2018, pp. 826-838.
IEEE DOI 1804
BibRef
And: Correction to Second author name. ITS(19), No. 5, May 2018, pp. 1676-1676.
IEEE DOI 1805
Delays, Distance measurement, Global Positioning System, Reliability, Satellites, Vehicle detection, malicious vehicle BibRef

Hasan, S., Ukkusuri, S.V.,
Reconstructing Activity Location Sequences From Incomplete Check-In Data: A Semi-Markov Continuous-Time Bayesian Network Model,
ITS(19), No. 3, March 2018, pp. 687-698.
IEEE DOI 1804
Data models, Hidden Markov models, Markov processes, Probabilistic logic, Social network services, Timing, Trajectory, trajectory mining BibRef

Zhang, X.G.[Xiao-Ge], Mahadevan, S.[Sankaran],
A Bio-Inspired Approach to Traffic Network Equilibrium Assignment Problem,
Cyber(48), No. 4, April 2018, pp. 1304-1315.
IEEE DOI 1804
Approximation algorithms, Electron tubes, Heuristic algorithms, Joining processes, Mathematical model, Optimization, user equilibrium BibRef

Stemberk, J.[Josef], Dolejs, J.[Josef], Maresova, P.[Petra], Kuca, K.[Kamil],
Factors Affecting the Number of Visitors in National Parks in the Czech Republic, Germany and Austria,
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Goulet-Langlois, G., Koutsopoulos, H.N., Zhao, Z., Zhao, J.,
Measuring Regularity of Individual Travel Patterns,
ITS(19), No. 5, May 2018, pp. 1583-1592.
IEEE DOI 1805
Entropy, Environmental engineering, Frequency measurement, Intelligent transportation systems, Smart cards, travel behavior BibRef

Bauer, D., Richter, G., Asamer, J., Heilmann, B., Lenz, G., Kölbl, R.,
Quasi-Dynamic Estimation of OD Flows From Traffic Counts Without Prior OD Matrix,
ITS(19), No. 6, June 2018, pp. 2025-2034.
IEEE DOI 1806
Entropy, Estimation, Public transportation, Road transportation, Sensors, Urban areas, Origin-destination flow estimation, quasi-dynamic assumption BibRef

Jiang, H., Luo, W., Zhao, D.,
A Novel Negative Location Collection Method for Finding Aggregated Locations,
ITS(19), No. 6, June 2018, pp. 1741-1753.
IEEE DOI 1806
Aggregates, Cryptography, Intelligent transportation systems, Mobile handsets, Privacy, Servers, Privacy, location privacy, trace privacy BibRef

Hong, Z., Chen, Y., Mahmassani, H.S.,
Recognizing Network Trip Patterns Using a Spatio-Temporal Vehicle Trajectory Clustering Algorithm,
ITS(19), No. 8, August 2018, pp. 2548-2557.
IEEE DOI 1808
Trajectory, Clustering algorithms, Data mining, Algorithm design and analysis, Roads, Spatial databases, shortest path distance BibRef

Tang, T.[Tao], Dong, X.[Xin], Wang, J.Z.[Jin-Zhong], Kong, X.J.[Xiang-Jie], Rahim, A.[Azizur], Yu, X.N.[Xuan-Nian], Li, Y.L.[Yu-Lin],
FISS: function identification of subway stations based on semantics mining and functional clustering,
IET-ITS(12), No. 7, September 2018, pp. 558-567.
DOI Link 1808
BibRef

Zheng, L.[Li], Sun, M.[Meng], Luo, Y.J.[Yue-Jun], Song, X.B.[Xiang-Bo], Yang, C.W.[Chao-Wei], Hu, F.[Fei], Yu, M.Z.[Man-Zhu],
Utilizing MapReduce to Improve Probe-Car Track Data Mining,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link 1808
Probe-car for real-time traffice. BibRef

Zhu, Z.[Zheng], Xiong, C.F.[Chen-Feng], Chen, X.M.[Xiqun Michael], Zhang, L.[Lei],
Calibrating supply parameters of large-scale DTA models with surrogate-based optimisation,
IET-ITS(12), No. 7, September 2018, pp. 642-650.
DOI Link 1808
large-scale dynamic traffic assignment. BibRef

Li, W.[Weizi], Jiang, M.L.[Mei-Lei], Chen, Y.[Yaoyu], Lin, M.C.[Ming C.],
Estimating urban traffic states using iterative refinement and Wardrop equilibria,
IET-ITS(12), No. 8, October 2018, pp. 875-883.
DOI Link 1809
BibRef

Horn, B.K.P., Wang, L.,
Wave Equation of Suppressed Traffic Flow Instabilities,
ITS(19), No. 9, September 2018, pp. 2955-2964.
IEEE DOI 1809
Automobiles, Acceleration, Propagation, Control systems, Perturbation methods, Mathematical model, Stability analysis, damped wave equation BibRef

Lindorfer, M., Mecklenbräuker, C.F., Ostermayer, G.,
Modeling the Imperfect Driver: Incorporating Human Factors in a Microscopic Traffic Model,
ITS(19), No. 9, September 2018, pp. 2856-2870.
IEEE DOI 1809
Vehicles, Human factors, Microscopy, Computational modeling, Acceleration, Vehicle dynamics, Analytical models, Car-following, simulation BibRef

Aghdam, A.H.[Arash Hazeghi], Alesheikh, A.A.[Ali Asghar],
Predicting the future location of cars on urban street network by chaining spatial web services,
IET-ITS(12), No. 8, October 2018, pp. 793-800.
DOI Link 1809
BibRef

Song, T.J.[Tai-Jin], Williams, B.M.[Billy M.], Rouphail, N.M.[Nagui M.],
Data-driven approach for identifying spatiotemporally recurrent bottlenecks,
IET-ITS(12), No. 8, October 2018, pp. 756-764.
DOI Link 1809
BibRef

Demiroluk, S.[Sami], Ozbay, K.[Kaan], Nassif, H.[Hani],
Mapping of truck traffic in New Jersey using weigh-in-motion data,
IET-ITS(12), No. 9, November 2018, pp. 1053-1061.
DOI Link 1810
BibRef

Wen, T.[Tao], Cai, C.[Chen], Gardner, L.[Lauren], Waller, S.T.[Steven Travis], Dixit, V.[Vinayak], Chen, F.[Fang],
Estimation of sparse O-D matrix accounting for demand volatility,
IET-ITS(12), No. 9, November 2018, pp. 1020-1026.
DOI Link 1810
Origin-destination (O-D) demand estimation. BibRef

Cao, P.[Peng], Fan, Q.C.[Qiao-Chu], Liu, X.B.[Xiao-Bo],
Real-time detection of end-of-queue shockwaves on freeways using probe vehicles with spacing equipment,
IET-ITS(12), No. 10, December 2018, pp. 1227-1235.
DOI Link 1812
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Zhu, M.L.[Mei-Ling], Liu, C.[Chen], Han, Y.B.[Yan-Bo],
Approach to discovering companion patterns based on traffic data stream,
IET-ITS(12), No. 10, December 2018, pp. 1351-1359.
DOI Link 1812
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Alesiani, F., Moreira-Matias, L., Faizrahnemoon, M.,
On Learning From Inaccurate and Incomplete Traffic Flow Data,
ITS(19), No. 11, November 2018, pp. 3698-3708.
IEEE DOI 1812
data mining, learning (artificial intelligence), road traffic, traffic engineering computing, incomplete traffic flow data, ensemble learning BibRef

Moriya, K., Matsushima, S., Yamanishi, K.,
Traffic Risk Mining From Heterogeneous Road Statistics,
ITS(19), No. 11, November 2018, pp. 3662-3675.
IEEE DOI 1812
data mining, matrix decomposition, pattern clustering, road traffic, statistical analysis, machine intelligence-pattern analysis BibRef

Chidlovskii, B.,
Mining Smart Card Data for Travellers' Mini Activities,
ITS(19), No. 11, November 2018, pp. 3676-3685.
IEEE DOI 1812
data mining, Markov processes, Monte Carlo methods, public transport, smart cards, travel industry, pattern analysis BibRef

Marzano, V., Papola, A., Simonelli, F., Papageorgiou, M.,
A Kalman Filter for Quasi-Dynamic o-d Flow Estimation/Updating,
ITS(19), No. 11, November 2018, pp. 3604-3612.
IEEE DOI 1812
Kalman filters, nonlinear filters, traffic counts, generalized least squares estimators, corresponding transition, quasi-dynamic estimation BibRef

Chang, Y.J.[Yu-Jiao], Duan, Z.Y.[Zheng-Yu], Yang, D.Y.[Dong-Yuan],
Using ALPR data to understand the vehicle use behaviour under TDM measures,
IET-ITS(12), No. 10, December 2018, pp. 1264-1270.
DOI Link 1812
BibRef

Zhang, W.B.[Wei-Bin], Qi, Y.[Yong], Zhou, Z.[Zhuping], Biancardo, S.A.[Salvatore A.], Wang, Y.[Yinhai],
Method of speed data fusion based on Bayesian combination algorithm and high-order multi-variable Markov model,
IET-ITS(12), No. 10, December 2018, pp. 1312-1321.
DOI Link 1812
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Barik, B.[Biswajit], Bhat, P.K.[Pradeep Krishna], Oncken, J.[Joseph], Chen, B.[Bo], Orlando, J.[Joshua], Robinette, D.[Darrell],
Optimal velocity prediction for fuel economy improvement of connected vehicles,
IET-ITS(12), No. 10, December 2018, pp. 1329-1335.
DOI Link 1812
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Lwin, K.K.[Ko Ko], Sekimoto, Y.[Yoshihide], Takeuchi, W.[Wataru],
Estimation of Hourly Link Population and Flow Directions from Mobile CDR,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link 1812
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Wang, S., Mao, G.,
Missing Data Estimation for Traffic Volume by Searching an Optimum Closed Cut in Urban Networks,
ITS(20), No. 1, January 2019, pp. 75-86.
IEEE DOI 1901
Roads, Detectors, Correlation, Estimation, Probabilistic logic, Tensile stress, Traffic data imputation, optimum closed cut, NHA, k-NN BibRef

Xu, M., Wu, J., Liu, M., Xiao, Y., Wang, H., Hu, D.,
Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories,
ITS(20), No. 2, February 2019, pp. 583-593.
IEEE DOI 1902
Roads, Trajectory, Network topology, Topology, Measurement, Data mining, Vehicle dynamics, Tripartite graph, ranking algorithm, OD entropy BibRef

Gao, J., Tembine, H.,
Distributed Mean-Field-Type Filters for Traffic Networks,
ITS(20), No. 2, February 2019, pp. 507-521.
IEEE DOI 1902
Surveillance, Roads, Sensor systems, Noise measurement, Cameras, Intelligent sensors, Mean-field filter, vehicle tracking BibRef

Lai, X.J.[Xin-Jun], Fu, H.[Hui], Li, J.[Jun], Sha, Z.R.[Zhi-Ren],
Understanding drivers' route choice behaviours in the urban network with machine learning models,
IET-ITS(13), No. 3, March 2019, pp. 427-434.
DOI Link 1903
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Yang, C.[Chao], Ye, W.[Wen], Zhu, R.R.[Rong-Rong], Zhang, T.R.[Tian-Ran],
Resident activity pattern recognition and comparison of six Sino-American metropolises,
IET-ITS(13), No. 3, March 2019, pp. 443-452.
DOI Link 1903
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Zhuang, Y.F.[Yi-Fan], Ke, R.M.[Rui-Min], Wang, Y.H.[Yin-Hai],
Innovative method for traffic data imputation based on convolutional neural network,
IET-ITS(13), No. 4, April 2019, pp. 605-613.
DOI Link 1903
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Di, X., Zhao, Y., Huang, S., Liu, H.X.,
A Similitude Theory for Modeling Traffic Flow Dynamics,
ITS(20), No. 3, March 2019, pp. 900-911.
IEEE DOI 1903
Vehicle dynamics, Aerodynamics, Robot sensing systems, Mathematical model, Analytical models, Automobiles, traffic dynamics BibRef

Wang, Y., Zhang, Y., Piao, X., Liu, H., Zhang, K.,
Traffic Data Reconstruction via Adaptive Spatial-Temporal Correlations,
ITS(20), No. 4, April 2019, pp. 1531-1543.
IEEE DOI 1904
Roads, Correlation, Matrix decomposition, Sparse matrices, Interpolation, Tensile stress, Detectors, adaptive spatial similarity BibRef

Fahad, A.[Adil], Almalawi, A.[Abdulmohsen], Tari, Z.[Zahir], Alharthi, K.[Kurayman], Qahtani, F.S.A.[Fawaz S. Al], Cheriet, M.[Mohamed],
SemTra: A semi-supervised approach to traffic flow labeling with minimal human effort,
PR(91), 2019, pp. 1-12.
Elsevier DOI 1904
Internet traffic classification, Semi-supervised learning, Multiview BibRef

Markovic, N., Sekula, P., Laan, Z.V.[Z. Vander], Andrienko, G., Andrienko, N.,
Applications of Trajectory Data From the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study,
ITS(20), No. 5, May 2019, pp. 1858-1869.
IEEE DOI 1905
Trajectory, Global Positioning System, Road transportation, Data mining, Data models, Bibliographies, Road transportation, big data BibRef

Ni, X.Y.[Xiao-Yong], Huang, H.[Hong], Meng, Y.Y.[Yang-Yang], Zhou, S.W.[Shi-Wei], Su, B.[Boni],
An Urban Road-Traffic Commuting Dynamics Study Based on Hotspot Clustering and a New Proposed Urban Commuting Electrostatics Model,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link 1905
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Zheng, K.N.[Kang-Ning], Yao, E.[Enjian], Zhang, J.[Junyi], Zhang, Y.S.[Yong-Sheng],
Traffic flow estimation on the expressway network using toll ticket data,
IET-ITS(13), No. 5, May 2019, pp. 886-895.
DOI Link 1906
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Bartin, B.[Bekir],
Use of learning classifier systems in microscopic toll plaza simulation models,
IET-ITS(13), No. 5, May 2019, pp. 860-869.
DOI Link 1906
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Ng, K.M.[Kok Mun], Reaz, M.B.I.[Mamun Bin Ibne], Ali, M.A.M.[Mohd Alauddin Mohd],
Model-based control strategy for oversaturated traffic regimes based on the LWR-IM traffic model,
IET-ITS(13), No. 5, May 2019, pp. 896-904.
DOI Link 1906
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Chen, Y.J.[Yu-Jun], Pu, J.[Juhua], Du, J.H.[Jia-Hong], Wang, Y.[Yue], Xiong, Z.[Zhang],
Spatial-temporal traffic outlier detection by coupling road level of service,
IET-ITS(13), No. 6, June 2019, pp. 1016-1022.
DOI Link 1906
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Zhang, L.F.[Lian-Fa], Cheng, J.Q.[Jian-Quan], Jin, C.[Cheng],
Spatial Interaction Modeling of OD Flow Data: Comparing Geographically Weighted Negative Binomial Regression (GWNBR) and OLS (GWOLSR),
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906
Origin-Destination flow data. BibRef

Naveh, K.S.[K. Soltani], Kim, J.,
Urban Trajectory Analytics: Day-of-Week Movement Pattern Mining Using Tensor Factorization,
ITS(20), No. 7, July 2019, pp. 2540-2549.
IEEE DOI 1907
Trajectory, Tensile stress, Bluetooth, Data mining, Smart cards, Urban areas, Feature extraction, Tensor factorization, Bluetooth data BibRef

Yong-dong, W.[Wang], Dong-wei, X.[Xu], Peng, P.[Peng], Yi, L.[Liu], Gui-jun, Z.[Zhang], Xiao, X.M.[Xue-Mei],
Kernel PCA for road traffic data non-linear feature extraction,
IET-ITS(13), No. 8, August 2019, pp. 1291-1298.
DOI Link 1908
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Yang, J.[Jing], Yi, D.[Disheng], Qiao, B.[Bowen], Zhang, J.[Jing],
Spatio-Temporal Change Characteristics of Spatial-Interaction Networks: Case Study within the Sixth Ring Road of Beijing, China,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908
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Wang, S., Zhang, X., Li, F., Yu, P.S., Huang, Z.,
Efficient Traffic Estimation With Multi-Sourced Data by Parallel Coupled Hidden Markov Model,
ITS(20), No. 8, August 2019, pp. 3010-3023.
IEEE DOI 1908
Roads, Probes, Global Positioning System, Hidden Markov models, Estimation, Twitter, Social media, traffic estimation, CHMM BibRef

Li, L., Zhang, J., Wang, Y., Ran, B.,
Missing Value Imputation for Traffic-Related Time Series Data Based on a Multi-View Learning Method,
ITS(20), No. 8, August 2019, pp. 2933-2943.
IEEE DOI 1908
Time series analysis, Logic gates, Sensors, Data models, Road transportation, Learning systems, Databases, temporal and spatial views BibRef

Deng, Y.[Yue], Liu, J.P.[Ji-Ping], Liu, Y.[Yang], Luo, A.[An],
Detecting Urban Polycentric Structure from POI Data,
IJGI(8), No. 6, 2019, pp. xx-yy.
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Urban sub-senters. Peaks of human activity. BibRef

Aalipour, A., Kebriaei, H., Ramezani, M.,
Analytical Optimal Solution of Perimeter Traffic Flow Control Based on MFD Dynamics: A Pontryagin's Maximum Principle Approach,
ITS(20), No. 9, September 2019, pp. 3224-3234.
IEEE DOI 1909
Optimal control, Urban areas, Vehicle dynamics, Mathematical model, Analytical models, Intelligent transportation systems, indirect optimal approach (IOA) BibRef

Wu, J.[Jing], Li, J.W.[Jing-Wen], Ma, Y.[Yue],
A Comparative Study of Spatial and Temporal Preferences for Waterfronts in Wuhan based on Gender Differences in Check-In Behavior,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link 1909
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Karimi, M.[Mohammad], Alecsandru, C.[Ciprian],
Two-fold calibration approach for microscopic traffic simulation models,
IET-ITS(13), No. 10, October 2019, pp. 1507-1517.
DOI Link 1909
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Ji, Y.J.[Yan-Jie], Cao, Y.[Yu], Liu, Y.[Yang], Guo, W.H.[Wei-Hong], Gao, L.P.[Liang-Peng],
Research on classification and influencing factors of metro commuting patterns by combining smart card data and household travel survey data,
IET-ITS(13), No. 10, October 2019, pp. 1525-1532.
DOI Link 1909
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Wang, D., Fan, J., Xiao, Z., Jiang, H., Chen, H., Zeng, F., Li, K.,
Stop-and-Wait: Discover Aggregation Effect Based on Private Car Trajectory Data,
ITS(20), No. 10, October 2019, pp. 3623-3633.
IEEE DOI 1910
Automobiles, Surface acoustic waves, Trajectory, Urban areas, Public transportation, Spatiotemporal phenomena, Roads, trajectory data BibRef

Ishikawa, K.[Kazuki], Nakayama, D.[Daichi],
Estimation of Origin-Destination Flows of Passenger Cars in 1925 in Old Tokyo City, Japan,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912
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Wang, P.X.[Pei-Xiao], Wu, S.[Sheng], Zhang, H.C.[Heng-Cai], Lu, F.[Feng],
Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912
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Xiang, Q.L.[Qiu-Liang], Wu, Q.Y.[Qun-Yong],
Tree-Based and Optimum Cut-Based Origin-Destination Flow Clustering,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912
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Huang, Y.[Yang], Shi, K.F.[Kai-Fang], Zong, H.M.[Hui-Ming], Zhou, T.G.[Ting-Gang], Shen, J.W.[Jing-Wei],
Exploring Spatial and Temporal Connection Patterns among the Districts in Chongqing Based on Highway Passenger Flow,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
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Zhou, T.[Tong], Liu, X.[Xintao], Qian, Z.[Zhen], Chen, H.X.[Hao-Xuan], Tao, F.[Fei],
Automatic Identification of the Social Functions of Areas of Interest (AOIs) Using the Standard Hour-Day-Spectrum Approach,
IJGI(9), No. 1, 2020, pp. xx-yy.
DOI Link 2001
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Wang, S., Mao, G.,
Fundamental Limits of Missing Traffic Data Estimation in Urban Networks,
ITS(21), No. 3, March 2020, pp. 1191-1203.
IEEE DOI 2003
Cramer-Rao lower bound (CRLB), squared flow error bound (SFEB), fisher matrix, spatial-temporal kriging BibRef

Rizwan, M.[Muhammad], Wan, W.G.[Wang-Gen], Gwiazdzinski, L.[Luc],
Visualization, Spatiotemporal Patterns, and Directional Analysis of Urban Activities Using Geolocation Data Extracted from LBSN,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
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Jung, I.[Inhwan],
An IoT-based smart parking management system,
IJCVR(10), No. 2, 2020, pp. 122-132.
DOI Link 2003
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Chen, Y., Lv, Y., Wang, F.,
Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks,
ITS(21), No. 4, April 2020, pp. 1624-1630.
IEEE DOI 2004
Generators, Data models, Generative adversarial networks, Training, Loss measurement, deep learning BibRef

Nassrullah, Z., Yousif, S.,
Development of a Microsimulation Model for Motorway Roadworks With Narrow Lanes,
ITS(21), No. 4, April 2020, pp. 1536-1546.
IEEE DOI 2004
Vehicles, Acceleration, Roads, Accidents, Layout, Calibration, Lane closure, microsimulation, modeling, narrow lanes, roadwork, traffic management BibRef

Rettore, P.H.L.[Paulo H. L.], Santos, B.P.[Bruno P.], Lopes, R.R.F.[Roberto Rigolin F.], Maia, G.[Guilherme], Villas, L.A.[Leandro A.], Loureiro, A.A.F.[Antonio A. F.],
Road Data Enrichment Framework Based on Heterogeneous Data Fusion for ITS,
ITS(21), No. 4, April 2020, pp. 1751-1766.
IEEE DOI 2004
ITS, heterogeneous data fusion, data enrichment, LBSM, incident detection, VANETs BibRef

Zißner, P.[Philipp], Rettore, P.H.L.[Paulo H. L.], Santos, B.P.[Bruno P.], Loevenich, J.F.[Johannes F.], Lopes, R.R.F.[Roberto Rigolin F.],
DataFITS: A Heterogeneous Data Fusion Framework for Traffic and Incident Prediction,
ITS(24), No. 10, October 2023, pp. 11466-11478.
IEEE DOI 2310
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Li, T.L.[Teng-Long], Hui, F.[Fei], Zhao, X.M.[Xiang-Mo], Liu, C.[Ce], Ngoduy, D.[Dong],
Modelling heterogeneous traffic dynamics by considering the influence of V2V safety messages,
IET-ITS(14), No. 4, April 2020, pp. 220-227.
DOI Link 2004
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Wang, Q.[Qi], Li, L.[Li], Hou, D.[Dezao], Li, Z.H.[Zhi-Heng], Hu, J.M.[Jian-Ming],
Simulation study on the effect of automated driving in a road network environment,
IET-ITS(14), No. 4, April 2020, pp. 228-232.
DOI Link 2004
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Mühl, K.[Kristin], Stoll, T.[Tanja], Baumann, M.[Martin],
Look ahead: understanding cognitive anticipatory processes based on situational characteristics in dynamic traffic situations,
IET-ITS(14), No. 4, April 2020, pp. 233-240.
DOI Link 2004
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Novovic, O.[Olivera], Brdar, S.[Sanja], Mesaroš, M.[Minucer], Crnojevic, V.[Vladimir], Papadopoulos, A.N.[Apostolos N.],
Uncovering the Relationship between Human Connectivity Dynamics and Land Use,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link 2004
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Tao, R.[Ran], Gong, Z.Y.[Zhao-Ya], Ma, Q.W.[Qi-Wei], Thill, J.C.[Jean-Claude],
Boosting Computational Effectiveness in Big Spatial Flow Data Analysis with Intelligent Data Reduction,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link 2005
spatial origin-destination (OD) flow data. BibRef

Tanveer, H.[Hashir], Balz, T.[Timo], Cigna, F.[Francesca], Tapete, D.[Deodato],
Monitoring 2011-2020 Traffic Patterns in Wuhan (China) with COSMO-SkyMed SAR, Amidst the 7th CISM Military World Games and COVID-19 Outbreak,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
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Mohan, R.[Ranju], Ramadurai, G.[Gitakrishnan],
Field data application of a non-lane-based multi-class traffic flow model,
IET-ITS(14), No. 7, July 2020, pp. 657-667.
DOI Link 2006
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Duran, D.[David], Sacristán, V.[Vera], Silveira, R.I.[Rodrigo I.],
Map construction algorithms: a local evaluation through hiking data,
GeoInfo(24), No. 3, July 2020, pp. 633-681.
WWW Link. 2006
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Rossi, A., Barlacchi, G., Bianchini, M., Lepri, B.,
Modelling Taxi Drivers' Behaviour for the Next Destination Prediction,
ITS(21), No. 7, July 2020, pp. 2980-2989.
IEEE DOI 2007
Public transportation, Urban areas, Trajectory, Predictive models, Recurrent neural networks, Task analysis, Vehicles, smart cities BibRef

Chu, K., Lam, A.Y.S., Li, V.O.K.,
Deep Multi-Scale Convolutional LSTM Network for Travel Demand and Origin-Destination Predictions,
ITS(21), No. 8, August 2020, pp. 3219-3232.
IEEE DOI 2008
Deep learning, Public transportation, Correlation, Predictive models, Data models, Travel demand prediction, origin-destination tensor BibRef

Li, Z., Khasawneh, F., Yin, X., Li, A., Song, Z.,
A New Microscopic Traffic Model Using a Spring-Mass-Damper-Clutch System,
ITS(21), No. 8, August 2020, pp. 3322-3331.
IEEE DOI 2008
Data models, Vehicles, Computational modeling, Numerical models, Lead, Vehicle dynamics, Microscopy, Car-following (CF) model, stability of time-delay system BibRef

Zhou, L., Zhang, S., Yu, J., Chen, X.,
Spatial-Temporal Deep Tensor Neural Networks for Large-Scale Urban Network Speed Prediction,
ITS(21), No. 9, September 2020, pp. 3718-3729.
IEEE DOI 2008
Roads, Predictive models, Stacking, Neural networks, Time series analysis, Detectors, Speed prediction, deep learning BibRef

Duan, P., Mao, G., Kang, J., Huang, B.,
Estimation of Link Travel Time Distribution With Limited Traffic Detectors,
ITS(21), No. 9, September 2020, pp. 3730-3743.
IEEE DOI 2008
Estimation, Detectors, Roads, Tomography, Cameras, Bluetooth, Global Positioning System, Link travel time distribution, expectation maximization (EM) algorithm BibRef

Rao, W.M.[Wen-Ming], Xia, J.X.[Jing-Xin], Wang, C.[Chen], Lu, Z.B.[Zhen-Bo], Chen, Q.[Qian],
Investigating impact of the heterogeneity of trajectory data distribution on origin-destination estimation: A spatial statistics approach,
IET-ITS(14), No. 10, October 2020, pp. 1218-1227.
DOI Link 2009
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Xu, C.Y.[Chen-Yang], Xu, C.Q.[Chang-Qing], Truong, T.K.[Trieu-Kien],
Mining the spatio-temporal pattern using matrix factorisation: A case study of traffic flow,
IET-ITS(14), No. 10, October 2020, pp. 1328-1337.
DOI Link 2009
BibRef

Cui, H.F.[Hai-Fu], Wu, L.[Liang], Hu, S.[Sheng], Lu, R.J.[Ru-Juan], Wang, S.L.[Shan-Lin],
Recognition of Urban Functions and Mixed Use Based on Residents' Movement and Topic Generation Model: The Case of Wuhan, China,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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Ortega, J.[Jairo], Tóth, J.[János], Péter, T.[Tamás],
Mapping the Catchment Area of Park and Ride Facilities within Urban Environments,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
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Liu, A.Q.[An-Qi], Kelobonye, K.[Keone], Zhou, Z.Q.[Zhen-Qi], Xu, Q.X.[Qiu-Xia], Xu, Z.[Zhen], Han, L.Y.[Ling-Yun],
School Commuting Mode Shift: A Scenario Analysis for Active School Commuting Using GIS and Online Map API,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Di, Z.[Zhen], Yang, L.X.[Li-Xing], Wang, L.[Li], Qi, J.G.[Jian-Guo],
A Robust Network Design Problem Based on the Spatiotemporal Attributes of Activities,
ITS(21), No. 10, October 2020, pp. 4294-4307.
IEEE DOI 2010
Stochastic processes, Roads, Linear programming, Biological system modeling, Heuristic algorithms, Programming, stochastic scenarios BibRef

Karam, A.[Ahmed], Illemann, T.M.[Thorbjørn M.], Reinau, K.H.[Kristian Hegner], Vuk, G.[Goran], Hansen, C.O.[Christian O.],
Towards Deriving Freight Traffic Measures from Truck Movement Data for State Road Planning: A Proposed System Framework,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link 2010
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Wang, Y.D.[Yong-Dong], Xu, D.W.[Dong-Wei], Peng, P.[Peng], Zhang, G.J.[Gui-Jun],
Analysis of road travel behaviour based on big trajectory data,
IET-ITS(14), No. 12, December 2020, pp. 1691-1703.
DOI Link 2011
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Mitra, A.[Anna], Attanasi, A.[Alessandro], Meschini, L.[Lorenzo], Gentile, G.[Guido],
Methodology for O-D matrix estimation using the revealed paths of floating car data on large-scale networks,
IET-ITS(14), No. 12, December 2020, pp. 1704-1711.
DOI Link 2011
BibRef

Huang, Y., Xiao, Z., Wang, D., Jiang, H., Wu, D.,
Exploring Individual Travel Patterns Across Private Car Trajectory Data,
ITS(21), No. 12, December 2020, pp. 5036-5050.
IEEE DOI 2012
Automobiles, Trajectory, Public transportation, Smart cards, Mobile handsets, Entropy, Urban areas, Private car, trajectory data, frequently-visit place BibRef

Nugroho, S.A., Taha, A.F., Claudel, C.G.,
A Control-Theoretic Approach for Scalable and Robust Traffic Density Estimation Using Convex Optimization,
ITS(22), No. 1, January 2021, pp. 64-78.
IEEE DOI 2012
Observers, Road transportation, Computational modeling, Vehicle dynamics, Sensors, Traffic networks, L8 observer BibRef

Wu, L.[Lin], Xu, Y.J.[Yong-Jun], Wang, F.[Fei],
Identifying Port Calls of Ships by Uncertain Reasoning with Trajectory Data,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Khan, N.U.[Naimat Ullah], Wan, W.G.[Wang-Gen], Yu, S.[Shui], Muzahid, A.A.M., Khan, S.[Sajid], Hou, L.[Li],
A Study of User Activity Patterns and the Effect of Venue Types on City Dynamics Using Location-Based Social Network Data,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Blais, P.[Philippe], Badard, T.[Thierry], Duchesne, T.[Thierry], Côté, M.P.[Marie-Pier],
From Massive Trajectory Data to Traffic Modeling for Better Behavior Prediction in a Usage-Based Insurance Context,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Fang, S.[Shen], Pan, X., Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Meta-MSNet: Meta-Learning Based Multi-Source Data Fusion for Traffic Flow Prediction,
SPLetters(28), 2021, pp. 6-10.
IEEE DOI 2101
Data fusion, deep learning, graph convolution, meta-learning, traffic flow prediction, traffic network BibRef

Fang, S.[Shen], Prinet, V.[Véronique], Chang, J.L.[Jian-Long], Werman, M.[Michael], Zhang, C.X.[Chun-Xia], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
MS-Net: Multi-Source Spatio-Temporal Network for Traffic Flow Prediction,
ITS(23), No. 7, July 2022, pp. 7142-7155.
IEEE DOI 2207
Feature extraction, Convolution, Predictive models, Data models, Correlation, Roads, Kernel, Graph convolution, deep learning BibRef

Fang, S.[Shen], Zhang, C.X.[Chun-Xia], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
AutoMSNet: Multi-Source Spatio-Temporal Network via Automatic Neural Architecture Search for Traffic Flow Prediction,
ITS(24), No. 3, March 2023, pp. 2827-2841.
IEEE DOI 2303
Feature extraction, Task analysis, Semantics, Decoding, Predictive models, Adaptation models, Deep learning, traffic flow prediction BibRef

Chen, Y.[Yulu], Qin, R.J.[Rong-Jun], Zhang, G.X.[Gui-Xiang], Albanwan, H.[Hessah],
Spatial Temporal Analysis of Traffic Patterns during the COVID-19 Epidemic by Vehicle Detection Using Planet Remote-Sensing Satellite Images,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Du, B., Hu, X., Sun, L., Liu, J., Qiao, Y., Lv, W.,
Traffic Demand Prediction Based on Dynamic Transition Convolutional Neural Network,
ITS(22), No. 2, February 2021, pp. 1237-1247.
IEEE DOI 2102
Convolution, Feature extraction, Spatiotemporal phenomena, Predictive models, Convolutional neural networks, deep learning BibRef

Chen, C., Liu, B., Wan, S., Qiao, P., Pei, Q.,
An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System,
ITS(22), No. 3, March 2021, pp. 1840-1852.
IEEE DOI 2103
Image edge detection, Cloud computing, Real-time systems, Machine learning, Object detection, traffic flow detection BibRef

Kaziyeva, D.[Dana], Loidl, M.[Martin], Wallentin, G.[Gudrun],
Simulating Spatio-Temporal Patterns of Bicycle Flows with an Agent-Based Model,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Zeng, X.[Xing], Guan, X.F.[Xue-Feng], Wu, H.Y.[Hua-Yi], Xiao, H.P.[He-Ping],
A Data-Driven Quasi-Dynamic Traffic Assignment Model Integrating Multi-Source Traffic Sensor Data on the Expressway Network,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Li, C.M.[Cheng-Ming], Wu, Z.[Zheng], Zhu, L.[Lining], Liu, L.[Li], Zhang, C.C.[Cheng-Cheng],
Changes of Spatiotemporal Pattern and Network Characteristic in Population Flow under COVID-19 Epidemic,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhang, W.J.[Wen-Jia], Ji, C.H.[Chun-Han], Yu, H.[Hao], Zhao, Y.[Yi], Chai, Y.W.[Yan-Wei],
Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Sobral, T., Galvão, T., Borges, J.,
Knowledge-Assisted Visualization of Multi-Level Origin-Destination Flows Using Ontologies,
ITS(22), No. 4, April 2021, pp. 2168-2177.
IEEE DOI 2104
Ontologies, Data visualization, Stakeholders, Semantics, Data models, Urban areas, Tools, Ontologies, origin-destination matrices, Semantic Web BibRef

Sun, M.Q.[Meng-Qi], Fan, H.C.[Hong-Chao],
Detecting and Analyzing Urban Centers Based on the Localized Contour Tree Method Using Taxi Trajectory Data: A Case Study of Shanghai,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhang, Y.[Yan], Zheng, X.[Xiang], Chen, M.[Min], Li, Y.B.[Ying-Bing], Yan, Y.X.[Ying-Xue], Wang, P.Y.[Pei-Ying],
Urban Fine-Grained Spatial Structure Detection Based on a New Traffic Flow Interaction Analysis Framework,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Phu, C.N.V.[Cyril Nguyen Van], Farhi, N.[Nadir],
Estimation of Urban Traffic State With Probe Vehicles,
ITS(22), No. 5, May 2021, pp. 2797-2808.
IEEE DOI 2105
Probes, Junctions, Estimation, Roads, Queueing analysis, Global Positioning System, Intelligent transportation systems, queuing systems BibRef

Wang, Z.H.[Zhi-Heng], Fan, H.K.[Hong-Kui], Wang, D.K.[Dai-Kun], Xing, T.[Tao], Wang, D.C.[Dong-Chuan], Guo, Q.Z.[Qiao-Zhen], Xiu, L.[Lina],
Spatial Pattern of Highway Transport Dominance in Qinghai-Tibet Plateau at the County Scale,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Chen, H.B.[Hai-Bo], Chen, X.[Xin],
A Trajectory Ensemble-Compression Algorithm Based on Finite Element Method,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
Location based services BibRef

Mullakkal-Babu, F.A.[Freddy Antony], Wang, M.[Meng], van Arem, B.[Bart], Shyrokau, B.[Barys], Happee, R.[Riender],
A Hybrid Submicroscopic-Microscopic Traffic Flow Simulation Framework,
ITS(22), No. 6, June 2021, pp. 3430-3443.
IEEE DOI 2106
Vehicle dynamics, Microscopy, Trajectory, Safety, Acceleration, Dynamics, Adaptation models, Traffic model, submicroscopic, multilane BibRef

Wang, W.[Wei], Xia, F.[Feng], Nie, H.S.[Han-Song], Chen, Z.K.[Zhi-Kui], Gong, Z.G.[Zhi-Guo], Kong, X.J.[Xiang-Jie], Wei, W.[Wei],
Vehicle Trajectory Clustering Based on Dynamic Representation Learning of Internet of Vehicles,
ITS(22), No. 6, June 2021, pp. 3567-3576.
IEEE DOI 2106
Trajectory, Vehicle dynamics, Heuristic algorithms, Data mining, Internet of Things, Measurement, Clustering methods, vehicle trajectory clustering BibRef

Sollén, S., Casselgren, J.,
Large-scale implementation of floating car data monitoring road friction,
IET-ITS(15), No. 6, 2021, pp. 727-739.
DOI Link 2106
BibRef

Hu, G.J.[Guo-Jing], Lu, W.[Weike], Whalin, R.W.[Robert W.], Wang, F.[Feng], Kwembe, T.A.[Tor A.],
Analytical approximation for macroscopic fundamental diagram of urban corridor with mixed human and connected and autonomous traffic,
IET-ITS(15), No. 2, 2021, pp. 261-272.
DOI Link 2106
BibRef

Moradi, A.[Amin], Shahbahrami, A.[Asadollah], Akoushideh, A.[Alireza],
An unsupervised approach for traffic motion patterns extraction,
IET-IPR(15), No. 2, 2021, pp. 428-442.
DOI Link 2106
BibRef

Qiu, H.[Han], Zheng, Q.[Qinkai], Msahli, M.[Mounira], Memmi, G.[Gerard], Qiu, M.K.[Mei-Kang], Lu, J.L.[Jia-Liang],
Topological Graph Convolutional Network-Based Urban Traffic Flow and Density Prediction,
ITS(22), No. 7, July 2021, pp. 4560-4569.
IEEE DOI 2107
Vehicle-to-everything, Urban areas, Convolution, Reliability, Servers, Communication standards, V2X communication, flash crowd, graph convolutional network BibRef

Li, Y.H.[Yi-Hang], Xu, L.Y.[Li-Yan],
The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs: An Example from Beijing,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Yu, Q.Y.[Qing-Ying], Chen, C.M.[Chuan-Ming], Sun, L.P.[Li-Ping], Zheng, X.Y.[Xiao-Yao],
Urban Hotspot Area Detection Using Nearest-Neighborhood-Related Quality Clustering on Taxi Trajectory Data,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Costa, M.[Miguel], Marques, M.[Manuel], Moura, F.[Filipe],
A Circuity Temporal Analysis of Urban Street Networks Using Open Data: A Lisbon Case Study,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Chen, L.[Long], Moore, A.B.[Antoni B.], Mandic, S.[Sandra],
Using Exploratory Spatial Analysis to Understand the Patterns of Adolescents' Active Transport to School and Contributory Factors,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Li, J.[Jing], Guo, W.Y.[Wen-Yue], Liu, H.Y.[Hai-Yan], Chen, X.[Xin], Yu, A.Z.[An-Zhu], Li, J.[Jia],
Predicting User Activity Intensity Using Geographic Interactions Based on Social Media Check-In Data,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Wan, S.H.[Shao-Hua], Ding, S.T.[Song-Tao], Chen, C.[Chen],
Edge computing enabled video segmentation for real-time traffic monitoring in internet of vehicles,
PR(121), 2022, pp. 108146.
Elsevier DOI 2109
Video segmentation, Key frames extraction, Edge computing, YOLOv3 BibRef

Lee, J.[Jongsang], Seo, D.[Ducksu],
Accuracy of Regional Centrality Using Social Network Analysis: Evidence from Commuter Flow in South Korea,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

He, W.W.[Wen-Wen], Ren, F.[Fu],
Predicting the Place Visited of Floating Car: A Three-Layer Framework Using Spatiotemporal Probability,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Wang, P.[Ping], Hao, W.[Wenbang], Jin, Y.[Yinli],
Fine-Grained Traffic Flow Prediction of Various Vehicle Types via Fusion of Multisource Data and Deep Learning Approaches,
ITS(22), No. 11, November 2021, pp. 6921-6930.
IEEE DOI 2112
Roads, Detectors, Predictive models, Data models, Microwave sensors, Forecasting, Data integration, Toll collection, vehicle detector, multisource information BibRef

Wang, X.[Xing], Zeng, R.H.[Rui-Hao], Zou, F.M.[Fu-Min], Huang, F.L.[Fa-Liang], Jin, B.[Biao],
A highly efficient framework for outlier detection in urban traffic flow,
IET-ITS(15), No. 12, 2021, pp. 1494-1507.
DOI Link 2112
Outlier detection, Road traffic flow pattern, Nonnegative matrix factorization (NMF), PSO-BP neural network BibRef

Zheng, H.F.[Hai-Feng], Lin, F.[Feng], Feng, X.X.[Xin-Xin], Chen, Y.[Youjia],
A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction,
ITS(22), No. 11, November 2021, pp. 6910-6920.
IEEE DOI 2112
Feature extraction, Predictive models, Deep learning, Data models, Forecasting, Neural networks, Transportation, Bi-LSTM BibRef

Yao, X.[Xin], Gao, Y.[Yong], Zhu, D.[Di], Manley, E.[Ed], Wang, J.[Jiaoe], Liu, Y.[Yu],
Spatial Origin-Destination Flow Imputation Using Graph Convolutional Networks,
ITS(22), No. 12, December 2021, pp. 7474-7484.
IEEE DOI 2112
Spatial databases, Gravity, Convolution, Biological system modeling, Data models, Predictive models, graph convolution BibRef

Behara, K.N.S.[Krishna N. S.], Bhaskar, A.[Ashish], Chung, E.[Edward],
A Novel Methodology to Assimilate Sub-Path Flows in Bi-Level OD Matrix Estimation Process,
ITS(22), No. 11, November 2021, pp. 6931-6941.
IEEE DOI 2112
Trraffic origin-destination. Estimation, Trajectory, Bluetooth, Matrices, Linear programming, Australia, Mathematical model, OD matrix estimation, Brisbane BibRef

Gao, Q.G.[Qing-Gang], Molloy, J.[Joseph], Axhausen, K.W.[Kay W.],
Trip Purpose Imputation Using GPS Trajectories with Machine Learning,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Pravitasari, A.E.[Andrea Emma], Rustiadi, E.[Ernan], Priatama, R.A.[Rista Ardy], Murtadho, A.[Alfin], Kurnia, A.A.[Adib Ahmad], Mulya, S.P.[Setyardi Pratika], Saizen, I.[Izuru], Widodo, C.E.[Candraningratri Ekaputri], Wulandari, S.[Siti],
Spatiotemporal Distribution Patterns and Local Driving Factors of Regional Development in Java,
IJGI(10), No. 12, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Lu, W.Q.[Wen-Qi], Zhou, T.[Tian], Li, L.H.[Lin-Heng], Gu, Y.L.[Yuan-Li], Rui, Y.K.[Yi-Kang], Ran, B.[Bin],
An improved tucker decomposition-based imputation method for recovering lane-level missing values in traffic data,
IET-ITS(16), No. 3, 2022, pp. 363-379.
DOI Link 2202
BibRef

Liu, Z.C.[Zhong-Cheng], Sun, D.[Dihua], Zhao, M.[Min], Zhao, H.[Hang], Wang, S.H.[Shi-Hui], Liao, X.Y.[Xiao-Yong],
Cyber-physical description and CPS-based pinning approach of mixed traffic,
IET-ITS(16), No. 3, 2022, pp. 344-362.
DOI Link 2202
BibRef

Liu, Y.[Yusi], Gao, X.[Xiang], Yi, D.[Disheng], Jiang, H.P.[He-Ping], Zhao, Y.X.[Yu-Xin], Xu, J.[Jun], Zhang, J.[Jing],
Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Agriesti, S.[Serio], Roncoli, C.[Claudio], Nahmias-Biran, B.H.[Bat-Hen],
Assignment of a Synthetic Population for Activity-Based Modeling Employing Publicly Available Data,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Xia, Y.J.[Ying-Jie], Zhang, F.[Fan], Ou, J.[Jing],
STAP: A Spatio-Temporal Correlative Estimating Model for Improving Quality of Traffic Data,
ITS(23), No. 3, March 2022, pp. 1746-1754.
IEEE DOI 2203
Data models, Roads, Feature extraction, Estimation, Data mining, Predictive models, Correlation, Spatio-temporal correlation, anomalies detection BibRef

Wang, J.Q.[Jia-Qin], Wang, S.C.[Sheng-Chu],
Geographical Information Enhanced Recognition of Traffic Modes and Behavior Patterns,
ITS(23), No. 4, April 2022, pp. 3777-3782.
IEEE DOI 2204
Global navigation satellite system, Trajectory, Kinematics, Acceleration, Task analysis, Roads, Rail transportation, traffic mode BibRef

Yang, B.[Bowen], Liu, Z.[Zunhao], Cai, Z.[Zhi], Li, D.Z.[Dong-Ze], Su, X.[Xing], Guo, L.M.[Li-Min], Ding, Z.M.[Zhi-Ming],
A Novel Traffic Flow Reduction Method Based on Incomplete Vehicle History Spatio-Temporal Trajectory Data,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Su, H.Y.[Hai-Yang], Chen, C.[Chaolong],
Is One-Way Multi-Station Feasible? Influence of Value and Cost on Travel Intention of Urban Agglomeration in the Guangdong-Hong Kong-Macao Greater Bay Area,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Sun, Z.[Ziwen], Scott, I.[Iain], Bell, S.[Simon], Yang, Y.F.[Yu-Feng], Yang, Z.[Zichu],
Exploring Dynamic Street Vendors and Pedestrians through the Lens of Static Spatial Configuration in Yuncheng, China,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Joelianto, E.[Endra], Fathurrahman, M.F.[Muhammad Farhan], Sutarto, H.Y.[Herman Yoseph], Semanjski, I.[Ivana], Putri, A.[Adiyana], Gautama, S.[Sidharta],
Analysis of Spatiotemporal Data Imputation Methods for Traffic Flow Data in Urban Networks,
IJGI(11), No. 5, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Wang, S.[Shaofan], Zhao, Y.[Yongbo], Zhang, Y.[Yong], Hu, Y.L.[Yong-Li], Yin, B.C.[Bao-Cai],
Spatiotemporal traffic data imputation via tensorial weighted Schatten-p norm minimization,
IET-ITS(16), No. 7, 2022, pp. 926-939.
DOI Link 2206
BibRef

Sroczynski, A.[Andrzej], Kurowski, A.[Adam], Zaporowski, S.[Szymon], Czyzewski, A.[Andrzej],
Examining Impact of Speed Recommendation Algorithm Operating in Autonomous Road Signs on Minimum Distance between Vehicles,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Li, Z.P.[Zhi-Peng], Niu, X.Y.[Xin-Yi],
Exploring Spatial Nonstationarity in Determinants of Intercity Commuting Flows: A Case Study of Suzhou-Shanghai, China,
IJGI(11), No. 6, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Zhang, Y.N.[Yong-Nan], Zhou, Y.H.[Yong-Hua], Lu, H.[Huapu], Fujita, H.[Hamido],
Spark Cloud-Based Parallel Computing for Traffic Network Flow Predictive Control Using Non-Analytical Predictive Model,
ITS(23), No. 7, July 2022, pp. 7708-7720.
IEEE DOI 2207
Predictive models, Roads, Sparks, Computational modeling, Cloud computing, Predictive control, Optimization, hierarchical parallel genetic algorithm BibRef

Hu, L.S.[Lin-Shu], Zhang, F.[Feng], Qin, M.J.[Meng-Jiao], Fu, Z.Y.[Zhi-Yi], Chen, Z.[Zhende], Du, Z.H.[Zhen-Hong], Liu, R.Y.[Ren-Yi],
A Dynamic Pyramid Tilling Method for Traffic Data Stream Based on Flink,
ITS(23), No. 7, July 2022, pp. 6679-6688.
IEEE DOI 2207
Real-time systems, Tiles, Monitoring, Data processing, Distributed databases, Spatial databases, Scalability, Flink, ITS, real-time traffic data BibRef

Zhang, W.B.[Wei-Bin], Zhang, P.[Pulin], Yu, Y.H.[Ying-Hao], Li, X.Y.[Xi-Ying], Biancardo, S.A.[Salvatore Antonio], Zhang, J.[Junyi],
Missing Data Repairs for Traffic Flow With Self-Attention Generative Adversarial Imputation Net,
ITS(23), No. 7, July 2022, pp. 7919-7930.
IEEE DOI 2207
Data models, Time series analysis, Maintenance engineering, Training, Task analysis, Generative adversarial networks, self-attention BibRef

Cui, S.H.[Shao-Hua], Cao, F.[Feng], Yu, B.[Bin], Yao, B.Z.[Bao-Zhen],
Modeling Heterogeneous Traffic Mixing Regular, Connected, and Connected-Autonomous Vehicles Under Connected Environment,
ITS(23), No. 7, July 2022, pp. 8579-8594.
IEEE DOI 2207
Numerical stability, Vehicles, Numerical models, Analytical models, Memory, Stability criteria, Communications technology, heterogeneous traffic BibRef

Chang, M.M.[Meng-Meng], Ding, Z.M.[Zhi-Ming], Cai, Z.[Zhi], Zhao, Z.[Zilin], Yuan, L.[Lei],
Prediction of Evolution Behaviors of Transportation Hubs Based on Spatiotemporal Neural Network,
ITS(23), No. 7, July 2022, pp. 9171-9183.
IEEE DOI 2207
Spatiotemporal phenomena, Feature extraction, Correlation, Predictive models, Convolution, Transportation, traffic evolution behaviors BibRef

Zhou, J.W.[Jun-Wei], Qin, X.Z.[Xi-Zhong], Yu, K.[Kun], Jia, Z.H.[Zhen-Hong], Du, Y.[Yan],
STSGAN: Spatial-Temporal Global Semantic Graph Attention Convolution Networks for Urban Flow Prediction,
IJGI(11), No. 7, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Xu, H.[Haowen], Berres, A.[Anne], Tennille, S.A.[Sarah A.], Ravulaparthy, S.K.[Srinath K.], Wang, C.[Chieh], Sanyal, J.[Jibonananda],
Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data,
ITS(23), No. 8, August 2022, pp. 10530-10541.
IEEE DOI 2208
Data visualization, Roads, Vehicle dynamics, Emulation, Transportation, Monitoring, Radar detection, traffic monitoring BibRef

Yang, F.[Fan], Vereshchaka, A.[Alina], Lepri, B.[Bruno], Dong, W.[Wen],
Optimizing City-Scale Traffic Through Modeling Observations of Vehicle Movements,
ITS(23), No. 8, August 2022, pp. 10492-10503.
IEEE DOI 2208
Vehicle dynamics, Vehicles, Statistics, Sociology, Prediction algorithms, Urban areas, Roads, machine learning BibRef

Zhang, Z.[Zhao], Zhang, S.[Siyao], Mo, L.[Lei], Guo, M.[Mengdi], Liu, F.[Feng], Qi, X.[Xin],
Traffic Volume Estimate Based on Low Penetration Connected Vehicle Data at Signalized Intersections: A Bayesian Deduction Approach,
ITS(23), No. 8, August 2022, pp. 10596-10609.
IEEE DOI 2208
Global Positioning System, Trajectory, Detectors, Estimation, Volume measurement, Roads, Probes, Traffic volume, time boundary BibRef

Wang, Y.[Yang], Zhang, Y.[Yong], Wang, L.[Lixun], Hu, Y.L.[Yong-Li], Yin, B.C.[Bao-Cai],
Urban Traffic Pattern Analysis and Applications Based on Spatio-Temporal Non-Negative Matrix Factorization,
ITS(23), No. 8, August 2022, pp. 12752-12765.
IEEE DOI 2208
Roads, Transportation, Pattern analysis, Data models, Data mining, Analytical models, Autoregressive processes, spatio-temporal characteristics BibRef

Xiao, Z.[Zhu], Fang, H.[Hui], Jiang, H.B.[Hong-Bo], Bai, J.[Jing], Havyarimana, V.[Vincent], Chen, H.Y.[Hong-Yang],
Understanding Urban Area Attractiveness Based on Private Car Trajectory Data Using a Deep Learning Approach,
ITS(23), No. 8, August 2022, pp. 12343-12352.
IEEE DOI 2208
Automobiles, Trajectory, Urban areas, Spatiotemporal phenomena, Public transportation, Training, Deep learning, point-of-stop BibRef

Maffiola, D.[Davide], Longari, S.[Stefano], Carminati, M.[Michele], Tanelli, M.[Mara], Zanero, S.[Stefano],
GOLIATH: A Decentralized Framework for Data Collection in Intelligent Transportation Systems,
ITS(23), No. 8, August 2022, pp. 13372-13385.
IEEE DOI 2208
Blockchains, Real-time systems, Data collection, Vehicle dynamics, Robustness, Peer-to-peer computing, traffic management BibRef

He, Y.L.[Ying-Long], Mattas, K.[Konstantinos], Dona, R.[Riccardo], Albano, G.[Giovanni], Ciuffo, B.[Biagio],
Introducing the Effects of Road Geometry Into Microscopic Traffic Models for Automated Vehicles,
ITS(23), No. 8, August 2022, pp. 13604-13613.
IEEE DOI 2208
Slope and curvature. Roads, Microscopy, Geometry, Turning, Adaptation models, Data models, Vehicle dynamics, Microscopic traffic model, road geometry, automated vehicle BibRef

Li, T.[Tao], Han, X.[Xu], Ma, J.Q.[Jia-Qi],
Cooperative Perception for Estimating and Predicting Microscopic Traffic States to Manage Connected and Automated Traffic,
ITS(23), No. 8, August 2022, pp. 13694-13707.
IEEE DOI 2208
Estimation, Trajectory, Microscopy, Real-time systems, Detectors, Vehicle dynamics, Traffic control, high-definition (HD) microscopic traffic states BibRef

Yuan, Y.[Yun], Wang, Q.Z.[Qin-Zheng], Yang, X.F.T.[Xian-Feng Terry],
Traffic Flow Modeling With Gradual Physics Regularized Learning,
ITS(23), No. 9, September 2022, pp. 14649-14660.
IEEE DOI 2209
Mathematical models, Data models, Physics, Training, Computational modeling, Gaussian processes, Estimation, multivariate Gaussian process BibRef

Lu, S.F.[Shou-Feng],
Modeling Isotropic Traffic Flow Under Vehicle-to-Vehicle Communication: A Kinetic Approach,
ITS(23), No. 9, September 2022, pp. 16237-16248.
IEEE DOI 2209
Kinetic theory, Mathematical models, Roads, Vehicular ad hoc networks, Microscopy, Vehicle dynamics, kinetic BibRef

Bramich, D.M.[Daniel M.], Menéndez, M.[Mónica], Ambühl, L.[Lukas],
Fitting Empirical Fundamental Diagrams of Road Traffic: A Comprehensive Review and Comparison of Models Using an Extensive Data Set,
ITS(23), No. 9, September 2022, pp. 14104-14127.
IEEE DOI 2209
Roads, Data models, Urban areas, Detectors, Density measurement, Mathematical models, Time measurement, model comparisons BibRef

Huang, X.L.[Xin-Long], Chen, J.[Jian], Cai, M.[Ming], Wang, W.[Wei], Hu, X.P.[Xi-Ping],
Traffic Node Importance Evaluation Based on Clustering in Represented Transportation Networks,
ITS(23), No. 9, September 2022, pp. 16622-16631.
IEEE DOI 2209
Roads, Representation learning, Indexes, Measurement, Transportation, Topology, Entropy, Traffic node importance, cooperative intelligent transportation systems BibRef

Cooper, C.H.V.[Crispin H. V.],
Exploring Potential Applications of Quantum Computing in Transportation Modelling,
ITS(23), No. 9, September 2022, pp. 14712-14720.
IEEE DOI 2209
Quantum computing, Quantum mechanics, Computational modeling, Transportation, Quantum annealing, Annealing, Logic gates, tour models BibRef

Liu, Q.L.[Qi-Liang], Hou, Z.Y.[Zhao-Yi], Yang, J.[Jie],
Detecting Spatial Communities in Vehicle Movements by Combining Multi-Level Merging and Consensus Clustering,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Luo, G.Y.[Gui-Yang], Zhang, H.[Hui], Yuan, Q.[Quan], Li, J.L.[Jing-Lin], Wang, F.Y.[Fei-Yue],
ESTNet: Embedded Spatial-Temporal Network for Modeling Traffic Flow Dynamics,
ITS(23), No. 10, October 2022, pp. 19201-19212.
IEEE DOI 2210
Roads, Correlation, Feature extraction, Sensors, Deep learning, Convolution, Sensor phenomena and characterization, spatial-temporal networks BibRef

Yu, Z.Y.[Zhao-Yuan], Li, D.S.[Dong-Shuang], Hu, X.[Xu], Zhou, X.X.[Xin-Xin], Luo, W.[Wen], Yuan, L.W.[Lin-Wang], Zhu, A.X.[A-Xing],
Modeling Small-Granularity Expressway Traffic Volumes With Quantum Walks,
ITS(23), No. 10, October 2022, pp. 17077-17086.
IEEE DOI 2210
Vehicles, Data models, Oscillators, Solid modeling, Probability distribution, Predictive models, Vehicle dynamics, traffic simulation BibRef

Feng, X.X.[Xin-Xin], Zhang, H.T.[Hai-Tao], Wang, C.[Can], Zheng, H.F.[Hai-Feng],
Traffic Data Recovery From Corrupted and Incomplete Observations via Spatial-Temporal TRPCA,
ITS(23), No. 10, October 2022, pp. 17835-17848.
IEEE DOI 2210
Tensors, Anomaly detection, Data models, Principal component analysis, Roads, Discrete Fourier transforms, anomaly detection BibRef

Lei, M.Y.[Meng-Ying], Labbe, A.[Aurelie], Wu, Y.K.[Yuan-Kai], Sun, L.J.[Li-Jun],
Bayesian Kernelized Matrix Factorization for Spatiotemporal Traffic Data Imputation and Kriging,
ITS(23), No. 10, October 2022, pp. 18962-18974.
IEEE DOI 2210
Spatiotemporal phenomena, Kernel, Data models, Computational modeling, Task analysis, Correlation, Bayes methods, Markov chain Monte Carlo BibRef

Jiang, H.C.[Hong-Chao], Dong, L.[Lin], Qiu, B.[Bing],
How Are Macro-Scale and Micro-Scale Built Environments Associated with Running Activity? The Application of Strava Data and Deep Learning in Inner London,
IJGI(11), No. 10, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Lai, L.G.[Lu-Guang], Zhao, D.Q.[Dong-Qing], Xu, T.H.[Tian-He], Cheng, Z.H.[Zhen-Hao], Guo, W.Z.[Wen-Zhuo], Li, L.Y.[Lin-Yang],
Improving Vehicle Positioning Performance in Urban Environment with Tight Integration of Multi-GNSS PPP-RTK/INS,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Yin, R.[Ruyang], Liu, Z.Y.[Zhi-Yuan], Zheng, N.[Nan],
A Simulation-Based Model for Continuous Network Design Problem Using Bayesian Optimization,
ITS(23), No. 11, November 2022, pp. 20352-20367.
IEEE DOI 2212
Heuristic algorithms, Computational modeling, Analytical models, Bayes methods, Behavioral sciences, Transportation, Metaheuristics, simulation-based optimization BibRef

Liu, C.X.[Chen-Xi], Yang, H.[Hao], Ke, R.[Ruimin], Wang, Y.[Yinhai],
Toward a Dynamic Reversible Lane Management Strategy by Empowering Learning-Based Predictive Assignment Scheme,
ITS(23), No. 12, December 2022, pp. 23311-23323.
IEEE DOI 2212
Optimization, Roads, Predictive models, Heuristic algorithms, Real-time systems, Computational modeling, Traffic control, traffic flow prediction BibRef

Zhu, Y.T.[Yi-Ting], Wang, J.[Jiyu], Wang, J.[Junbo], He, Z.C.[Zhao-Cheng],
Multitask Neural Tensor Factorization for Road Traffic Speed-Volume Correlation Pattern Learning and Joint Imputation,
ITS(23), No. 12, December 2022, pp. 24550-24560.
IEEE DOI 2212
Tensors, Correlation, Task analysis, Roads, Solid modeling, Detectors, Data models, Multi-task learning, neural tensor factorization, automatic vehicle identification BibRef

Owais, M.[Mahmoud], Shahin, A.I.[Ahmed I.],
Exact and Heuristics Algorithms for Screen Line Problem in Large Size Networks: Shortest Path-Based Column Generation Approach,
ITS(23), No. 12, December 2022, pp. 24829-24840.
IEEE DOI 2212
Traffic sensors location problem. Sensors, Estimation, Observability, Heuristic algorithms, Surveillance, Image sensors, Transportation, Heuristics, information, traffic sensors BibRef

Chen, D.L.[Dong-Liang], Huang, H.Y.[Hong-Yong], Zheng, Y.C.[Yu-Chao], Gawkowski, P.[Piotr], Lv, H.B.[Hai-Bin], Lv, Z.H.[Zhi-Han],
The Scanner of Heterogeneous Traffic Flow in Smart Cities by an Updating Model of Connected and Automated Vehicles,
ITS(23), No. 12, December 2022, pp. 25361-25370.
IEEE DOI 2212
Laser radar, Sensors, Transportation, Meters, Detectors, Cameras, Automobiles, Connected and automated vehicles, scanner, swarm intelligence BibRef

Song, H.[Heng], Zhu, J.[Junwu], Jiang, Y.[Yi],
Two-Stage Merging Network for Describing Traffic Scenes in Intelligent Vehicle Driving System,
ITS(23), No. 12, December 2022, pp. 25509-25520.
IEEE DOI 2212
Visualization, Merging, Adaptation models, Intelligent vehicles, Semantics, Feature extraction, Object oriented modeling, neural networks BibRef

Cai, L.[Li], Sha, C.[Cong], He, J.[Jing], Yao, S.W.[Shao-Wen],
Spatial-Temporal Data Imputation Model of Traffic Passenger Flow Based on Grid Division,
IJGI(12), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Florin, R.[Ryan], Olariu, S.[Stephan],
Real-Time Traffic Density Estimation: Putting on-Coming Traffic to Work,
ITS(24), No. 1, January 2023, pp. 1374-1383.
IEEE DOI 2301
Probes, Real-time systems, Task analysis, Observers, Sensitivity analysis, Roads, Radar, traffic density BibRef

Lyu, S.X.[Su-Xing], Han, T.Y.[Tian-Yang], Li, P.R.[Pei-Ran], Luo, X.Y.[Xing-Yu], Kusakabe, T.[Takahiko],
A Dual-Flow Attentive Network With Feature Crossing for Chained Trip Purpose Inference,
ITS(24), No. 1, January 2023, pp. 631-644.
IEEE DOI 2301
Task analysis, Hidden Markov models, Neural networks, Feature extraction, Deep learning, Data models, Urban planning, intelligent transportation systems BibRef

Liu, Z.Y.[Zhi-Yuan], Lyu, C.[Cheng], Wang, Z.L.[Ze-Lin], Wang, S.[Shuaian], Liu, P.[Pan], Meng, Q.[Qiang],
A Gaussian-Process-Based Data-Driven Traffic Flow Model and Its Application in Road Capacity Analysis,
ITS(24), No. 2, February 2023, pp. 1544-1563.
IEEE DOI 2302
Roads, Data models, Mathematical models, Analytical models, Solid modeling, Sensors, Predictive models, Traffic flow, hyperparameter optimisation BibRef

Kyriacou, V.[Victor], Englezou, Y.[Yiolanda], Panayiotou, C.G.[Christos G.], Timotheou, S.[Stelios],
Bayesian Traffic State Estimation Using Extended Floating Car Data,
ITS(24), No. 2, February 2023, pp. 1518-1532.
IEEE DOI 2302
Data models, Bayes methods, Sensors, Roads, State estimation, Density measurement, Automobiles, Traffic density, probabilistic inference BibRef

van den Ende, M.[Martijn], Ferrari, A.[André], Sladen, A.[Anthony], Richard, C.[Cédric],
Deep Deconvolution for Traffic Analysis With Distributed Acoustic Sensing Data,
ITS(24), No. 3, March 2023, pp. 2947-2962.
IEEE DOI 2303
Automobiles, Strain, Sensors, Roads, Deconvolution, Temperature measurement, Frequency measurement, traffic analysis BibRef

Yuan, S.Y.[Si-Yuan], van den Ende, M.[Martijn], Liu, J.X.[Jing-Xiao], Noh, H.Y.[Hae Young], Clapp, R.[Robert], Richard, C.[Cédric], Biondi, B.[Biondo],
Spatial Deep Deconvolution U-Net for Traffic Analyses With Distributed Acoustic Sensing,
ITS(25), No. 2, February 2024, pp. 1913-1924.
IEEE DOI 2402
Optical fiber sensors, Sensors, Optical fiber cables, Signal resolution, Monitoring, Automobiles, Time-domain analysis, U-Net BibRef

Li, Y.C.[Yao-Chen], Hou, H.C.[Hao-Chuan], Dong, Z.[Zikun], Zang, Y.J.[Yu-Jie], Zhang, Y.[Ying], Song, Y.H.[Yong-Hong],
Spatiotemporal Analysis of Static and Dynamic Traffic Elements From Road Scenes,
ITS(24), No. 3, March 2023, pp. 3297-3311.
IEEE DOI 2303
Roads, Feature extraction, Image sequences, Spatiotemporal phenomena, Hidden Markov models, Vehicle dynamics, spatiotemporal analysis BibRef

Hussain, S.A.[Syed Adil], Hassan, M.U.[Muhammad Umair], Nasar, W.[Wajeeha], Ghorashi, S.[Sara], Jamjoom, M.M.[Mona M.], Abdel-Aty, A.H.[Abdel-Haleem], Parveen, A.[Amna], Hameed, I.A.[Ibrahim A.],
Efficient Trajectory Clustering with Road Network Constraints Based on Spatiotemporal Buffering,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Xiao, Z.[Zhu], Fang, H.[Hui], Jiang, H.B.[Hong-Bo], Bai, J.[Jing], Havyarimana, V.[Vincent], Chen, H.Y.[Hong-Yang], Jiao, L.C.[Li-Cheng],
Understanding Private Car Aggregation Effect via Spatio-Temporal Analysis of Trajectory Data,
Cyber(53), No. 4, April 2023, pp. 2346-2357.
IEEE DOI 2303
Automobiles, Spatiotemporal phenomena, Trajectory, Kernel, Correlation, Predictive models, Data models, Aggregation effect, trajectory data BibRef

Kim, J.[Jongho], Lim, D.H.[Dong-Hyun], Seo, Y.[Younghoon], So, J.J.[Jaehyun Jason], Kim, H.[Hyungjoo],
Influence of dedicated lanes for connected and automated vehicles on highway traffic flow,
IET-ITS(17), No. 4, 2023, pp. 678-690.
DOI Link 2304
BibRef

Sun, C.[Chao], Jing, H.D.[Hao-Dong], Chen, T.[Taolüe], Li, M.H.[Meng-Hui], Zhang, P.[Peng],
Incremental equilibrium assignment and applications to traffic network model,
IET-ITS(17), No. 4, 2023, pp. 794-803.
DOI Link 2304
incremental equilibrium assignment, reliability-based user equilibrium, route-based algorithm, user equilibrium BibRef

Xie, F.J.[Feng-Jie], Wang, X.[Xiao], Ren, C.P.[Cui-Ping],
Identify Important Cities in the Belt and Road Comprehensive Traffic Network,
IJGI(12), No. 4, 2023, pp. 154.
DOI Link 2305
BibRef

Liu, J.[Jing], Liu, Y.[Yang], Zhu, W.[Wei], Zhu, X.G.[Xiao-Guang], Song, L.[Liang],
Distributional and spatial-temporal robust representation learning for transportation activity recognition,
PR(140), 2023, pp. 109568.
Elsevier DOI 2305
Transportation activity recognition, Multimodal sensing, Deep learning, Statistical feature, Spatial-temporal feature BibRef

Jafaripournimchahi, A.[Ammar], Cai, Y.F.[Ying-Feng], Wang, H.[Hai], Sun, L.[Lu], Tang, Y.[Yili], Babadi, A.A.[Arman Amani],
A viscous continuum traffic flow model based on the cooperative car-following behaviour of connected and autonomous vehicles,
IET-ITS(17), No. 5, 2023, pp. 973-991.
DOI Link 2305
autonomous driving, congestion evaluation, environmental, management and control, traffic modelling BibRef

Zhou, Y.[Yi], Hu, M.H.[Ming-Hua], Yang, L.[Lei], Wang, Y.[Yuchi],
Autonomous and collaborative trajectory planning for traffic complexity management,
IET-ITS(17), No. 5, 2023, pp. 992-1008.
DOI Link 2305
air traffic management, autonomous trajectory planning, collaborative decision-making, traffic complexity management BibRef

Sun, B.F.[Bao-Feng], Nie, L.[Liaodong], Wang, W.[Wei], Sun, Y.[Yu], Li, H.[Han],
Dynamic identification of logistics critical roads based on BeiDou trajectory data,
IET-ITS(17), No. 7, 2023, pp. 1467-1481.
DOI Link 2307
BeiDou trajectory data, industrial parks, KANN-DBSCAN algorithm, logistics attractiveness, logistics critical roads BibRef

Luo, Q.[Qin], Lin, B.[Bin], Lyu, Y.T.[Yi-Tong], He, Y.X.[Yu-Xin], Zhang, X.C.[Xiao-Chun], Zhang, Z.Q.[Zhi-Qing],
Spatiotemporal path inference model for urban rail transit passengers based on travel time data,
IET-ITS(17), No. 7, 2023, pp. 1395-1414.
DOI Link 2307
passenger detention, passenger flow assignment, path inference, travel time, urban rail transit BibRef

Tran, D.N.N.[Duong Nguyen-Ngoc], Pham, L.H.[Long Hoang], Nguyen, H.H.[Huy-Hung], Jeon, J.W.[Jae Wook],
A Vision-Based Method for Real-Time Traffic Flow Estimation on Edge Devices,
ITS(24), No. 8, August 2023, pp. 8038-8052.
IEEE DOI 2308
Estimation, Trajectory, Tracking, Roads, Image edge detection, Real-time systems, Vehicle detection, real-time performance BibRef

Zou, S.S.[Song-Shang], Chen, H.[Hao], Feng, H.[Hui], Xiao, G.Y.[Guang-Yi], Qin, Z.[Zhen], Cai, W.W.[Wei-Wei],
Traffic Flow Video Image Recognition and Analysis Based on Multi-Target Tracking Algorithm and Deep Learning,
ITS(24), No. 8, August 2023, pp. 8762-8775.
IEEE DOI 2308
Roads, Real-time systems, Estimation, Streaming media, Wireless sensor networks, Spatiotemporal phenomena, Sensors, feature recognition BibRef

Dey, S.[Subhrasankha], Winter, S.[Stephan], Tomko, M.[Martin], Ganguly, N.[Niloy],
Traffic Count Estimation at Basis Links Without Path Flow and Historic Data,
ITS(24), No. 10, October 2023, pp. 11410-11423.
IEEE DOI 2310
BibRef

Fu, Y.M.[Yan-Ming], Qin, X.Q.[Xiao-Qiong], Zhang, X.[Xian], Jia, Y.Q.[You-Quan],
Hybrid Recruitment Scheme Based on Deep Learning in Vehicular Crowdsensing,
ITS(24), No. 10, October 2023, pp. 10735-10748.
IEEE DOI 2310
BibRef

Wu, P.L.[Peng-Ling], Ding, M.[Meng], Zheng, Y.B.[Yu-Bang],
Spatiotemporal traffic data imputation by synergizing low tensor ring rank and nonlocal subspace regularization,
IET-ITS(17), No. 9, 2023, pp. 1908-1923.
DOI Link 2310
data analysis, intelligent transportation systems, interpolation, management and control, traffic modeling BibRef

Su, X.[Xing], Sun, W.J.[Wen-Jie], Song, C.[Chenting], Cai, Z.[Zhi], Guo, L.M.[Li-Min],
A Latent-Factor-Model-Based Approach for Traffic Data Imputation with Road Network Information,
IJGI(12), No. 9, 2023, pp. 378.
DOI Link 2310
BibRef

Ding, X.[Xiaoe], Liu, W.K.[Wen-Ke], Wang, C.C.[Cheng-Cheng], Kong, D.[Delan], Tang, W.[Wei], Xu, R.[Run], Zhang, C.Y.[Chang-Yong],
Trend analysis of traffic management based on literature data mining and graph analysis tools,
IET-ITS(17), No. 11, 2023, pp. 2115-2130.
DOI Link 2311
data mining, long term evolution, traffic management and control BibRef

Xing, J.P.[Ji-Ping], Liu, R.H.[Rong-Hui], Anish, K.[Khadka], Liu, Z.Y.[Zhi-Yuan],
A Customized Data Fusion Tensor Approach for Interval-Wise Missing Network Volume Imputation,
ITS(24), No. 11, November 2023, pp. 12107-12122.
IEEE DOI 2311
fill in missing data. BibRef

Alonso, B.[Borja], Musolino, G.[Giuseppe], Rindone, C.[Corrado], Vitetta, A.[Antonino],
Estimation of a Fundamental Diagram with Heterogeneous Data Sources: Experimentation in the City of Santander,
IJGI(12), No. 10, 2023, pp. 418.
DOI Link 2311
Analyzing the traffic conditions on an urban road link. Goal to reduce urban congestion. BibRef

Mi, H.N.[Han-Ning], Chen, S.[Sijie], Ping, J.[Jian], Yan, Z.[Zheng],
Traffic Equilibrium Considering Heterogeneity Across Electric Vehicles,
ITS(24), No. 12, December 2023, pp. 14944-14956.
IEEE DOI 2312
BibRef

Zong, R.X.[Rui-Xue], Deng, W.W.[Wei-Wen], Bai, X.S.[Xue-Song], Wang, Y.[Ying], Ding, J.[Juan],
Traffic Modeling Based on Data-Driven Method for Simulation Test of Autonomous Driving,
ITS(24), No. 12, December 2023, pp. 14076-14085.
IEEE DOI 2312
Model traffic to test autonomous driving. BibRef

Olariu, S.[Stephan],
A Theoretical Validation of the Moving Observer Method,
ITS(24), No. 12, December 2023, pp. 14633-14641.
IEEE DOI 2312
Moving observer to measure traffic vs. stationary. BibRef

Wang, Z.[Zhiyu], Li, L.H.[Lin-Heng], Qu, X.[Xu], Mao, P.P.[Pei-Pei], Ran, B.[Bin],
Research on prediction method of expressway section traffic flow considering anomaly detection probability,
IET-ITS(18), No. 1, 2024, pp. 16-28.
DOI Link 2401
Anomaly Detection Probability, Attention Mechanism, Recurrent Neural Network, Traffic Flow Prediction BibRef

Gao, F.[Fengkun], Yang, B.[Bo], Chen, C.[Cailian], Guan, X.P.[Xin-Ping], Tang, Y.L.[Yu-Liang],
Distributionally Robust Optimization Based Model Predictive Control for Stochastic Mixed Traffic Flow,
ITS(25), No. 2, February 2024, pp. 1491-1502.
IEEE DOI 2402
Stochastic processes, Uncertainty, Roads, Predictive models, Optimization, Mathematical models, Computer architecture, stochastic model predictive control BibRef

Zhao, D.[De], Zhou, W.[Wei], Wang, W.[Wei], Hua, X.D.[Xue-Dong],
Trip purpose prediction using travel survey data with POI information via gradient boosting decision trees,
IET-ITS(18), No. 2, 2024, pp. 269-289.
DOI Link 2402
behavioural sciences, data mining, decision trees, demand forecasting, traveller information BibRef


Zhou, Y.X.[Yi-Xuan], Zhang, L.[Lei], Xu, Q.[Qin], Liu, Y.X.[Yi-Xiao], Fu, W.[Wen],
Characteristics Exploration of Hospitals in Shanghai through Spatial Relationship Using Taxi Data,
ICIVC22(287-292)
IEEE DOI 2301
Pediatrics, Hospitals, Clustering methods, Government, Clustering algorithms, Feature extraction, spatial relationship BibRef

Sun, T.[Tao], Xu, Y.J.[Yong-Jun], Wang, F.[Fei], Wu, L.[Lin], Qian, T.[Tangwen], Shao, Z.Z.[Ze-Zhi],
Trajectory-User Link with Attention Recurrent Networks,
ICPR21(4589-4596)
IEEE DOI 2105
Location based service Weight measurement, Training, Recurrent neural networks, Semantics, Graphics processing units, Trajectory BibRef

Moyo, T., Kibangou, A., Musakwa, W.,
Exploring the Potential of Traffic Index Data to Analyze Essential Traffic Impact In Developing Cities,
ISPRS20(B4:137-141).
DOI Link 2012
BibRef

Bharadwaj, S., Dubey, R., Zafar, M.I., Biswas, S.,
Raster Data Based Automated Noise Data Integration for Noise Mapping Limiting Data Dependency,
ISPRS21(B4-2021: 159-166).
DOI Link 2201
BibRef
And: A3, A1, A2, A4:
Different Scales of Urban Traffic Noise Prediction,
ISPRS20(B2:1181-1188).
DOI Link 2012
BibRef

Davoudi, N., Taleai, M., Molavi, M.,
Spatio-temporal Assessment of Mixed Land-use Impact On Travel Demand,
SMPR19(299-303).
DOI Link 1912
BibRef

Javanmard, R., Esmaeili, R., Malekzadeh, M., Karimipour, F.,
Investigating The Rhythms of Human Movements in Geneva Lake Region Using MDC Data,
SMPR19(583-588).
DOI Link 1912
BibRef

Zhang, X., Zhang, X., Zhang, H.,
Application Research of Lod Technology and The Shortest Path Algorithm In Trafic Geographic Information System,
SmartGeoApps19(1369-1374).
DOI Link 1912
BibRef

Zhang, Y., Cheng, T., Aslam, N.S.,
Exploring The Relationship Between Travel Pattern And Social-demographics Using Smart Card Data and Household Survey,
SmartGeoApps19(1375-1382).
DOI Link 1912
BibRef

Lee, M., Nam, H., Jun, C.,
Origin-destination-based Public Transport Service Gap,
GeoDisast18(283-290).
DOI Link 1901
BibRef

Du, J.H.[Jia-Hong], Chen, Y.J.[Yu-Jun], Wang, Y.[Yue], Pu, J.[Juhua],
Zone2Vec: Distributed Representation Learning of Urban Zones,
ICPR18(880-885)
IEEE DOI 1812
Urban zones separated by major roads. learning (artificial intelligence), pattern classification, pattern clustering, urban zones, Roads BibRef

Selzer, S., Asteriadis, S., Politze, M.,
Prediction of learning space occupation through WLAN access point data using Kalman filter and gradient boosting regression,
AVSS17(1-6)
IEEE DOI 1806
Kalman filters, computer aided instruction, educational institutions, learning (artificial intelligence), Wireless LAN BibRef

Biedermann, D., Ochs, M., Mester, R.,
COnGRATS: Realistic simulation of traffic sequences for autonomous driving,
ICVNZ15(1-6)
IEEE DOI 1701
image sequences BibRef

Hollenstein, D., Bleisch, S.,
Walkability For Different Urban Granularities,
ISPRS16(B2: 703-708).
DOI Link 1610
BibRef

Huang, W., Li, S., Xu, S.,
A Three-step Spatial-temporal-semantic Clustering Method For Human Activity Pattern Analysis,
ISPRS16(B2: 549-552).
DOI Link 1610
BibRef

Busch, S., Schindler, T., Klinger, T., Brenner, C.,
Analysis Of Spatio-temporal Traffic Patterns Based On Pedestrian Trajectories,
ISPRS16(B2: 497-503).
DOI Link 1610
BibRef

Haworth, J.,
Investigating The Potential of Activity Tracking App Data to Estimate Cycle Flows In Urban Areas,
ISPRS16(B2: 515-519).
DOI Link 1610
BibRef

Zhao, P.X., Zhao, S.M.,
Understanding Urban Traffic Flow Characteristics From The Network Centrality Perspective At Different Granularities,
ISPRS16(B2: 263-268).
DOI Link 1610
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Urban Mobility Analysis .


Last update:Mar 16, 2024 at 20:36:19