16.7.2.7.2 Traffic Flow Prediction, Forecast

Quek, C., Pasquier, M., Lim, B.L.B.,
POP-TRAFFIC: A Novel Fuzzy Neural Approach to Road Traffic Analysis and Prediction,
ITS(7), No. 2, June 2006, pp. 133-146.
IEEE DOI 0606
BibRef

Sun, S.L.[Shi-Liang], Zhang, C.S.[Chang-Shui], Yu, G.Q.[Guo-Qiang],
A bayesian network approach to traffic flow forecasting,
ITS(7), No. 1, March 2006, pp. 124-132.
IEEE DOI 0604
BibRef

Sun, S., Xu, X.,
Variational Inference for Infinite Mixtures of Gaussian Processes With Applications to Traffic Flow Prediction,
ITS(12), No. 2, June 2011, pp. 466-475.
IEEE DOI 1101
BibRef

Ramezani, A., Moshiri, B., Abdulhai, B., Kian, A.R.,
Distributed maximum likelihood estimation for flow and speed density prediction in distributed traffic detectors with gaussian mixture model assumption,
IET-ITS(6), No. 2, 2012, pp. 215-222.
DOI Link 1206
BibRef

Chang, H., Lee, Y., Yoon, B., Baek, S.,
Dynamic near-term traffic flow prediction: systemoriented approach based on past experiences,
IET-ITS(6), No. 2, 2012, pp. 292-305.
DOI Link 1209
BibRef

Chen, C., Liu, Z., Lin, W.H., Li, S., Wang, K.,
Distributed Modeling in a MapReduce Framework for Data-Driven Traffic Flow Forecasting,
ITS(14), No. 1, March 2013, pp. 22-33.
IEEE DOI 1303
BibRef

Kong, Q.J., Xu, Y., Lin, S., Wen, D., Zhu, F., Liu, Y.C.[Yun-Cai],
UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems,
ITS(14), No. 3, 2013, pp. 1541-1547.
IEEE DOI 1309
CORSIM BibRef

Xu, Y.Y.[Yan-Yan], Kong, Q.J.[Qing-Jie], Klette, R.[Reinhard], Liu, Y.C.[Yun-Cai],
Accurate and Interpretable Bayesian MARS for Traffic Flow Prediction,
ITS(15), No. 6, December 2014, pp. 2457-2469.
IEEE DOI 1412
Markov processes BibRef

Wang, Y.B.[Yu-Bin], van Schuppen, J.H., Vrancken, J.,
Prediction of Traffic Flow at the Boundary of a Motorway Network,
ITS(15), No. 1, February 2014, pp. 214-227.
IEEE DOI 1403
adaptive control BibRef

Asif, M.T., Dauwels, J., Goh, C.Y., Oran, A., Fathi, E., Xu, M., Dhanya, M.M., Mitrovic, N., Jaillet, P.,
Spatiotemporal Patterns in Large-Scale Traffic Speed Prediction,
ITS(15), No. 2, April 2014, pp. 794-804.
IEEE DOI 1404
Accuracy BibRef

Bonnin, S., Weisswange, T.H., Kummert, F., Schmuedderich, J.,
General Behavior Prediction by a Combination of Scenario-Specific Models,
ITS(15), No. 4, August 2014, pp. 1478-1488.
IEEE DOI 1410
behavioural sciences computing BibRef

Tahmasbi, R., Hashemi, S.M.,
Modeling and Forecasting the Urban Volume Using Stochastic Differential Equations,
ITS(15), No. 1, February 2014, pp. 250-259.
IEEE DOI 1403
differential equations BibRef

Lopes, S.B.[Simone Becker], Brondino, N.C.M.[Nair Cristina Margarido], Rodrigues da Silva, A.N.[Antônio Nélson],
GIS-Based Analytical Tools for Transport Planning: Spatial Regression Models for Transportation Demand Forecast,
IJGI(3), No. 2, 2014, pp. 565-583.
DOI Link 1405
BibRef

Hou, Y., Edara, P., Sun, C.,
Traffic Flow Forecasting for Urban Work Zones,
ITS(16), No. 4, August 2015, pp. 1761-1770.
IEEE DOI 1508
Feedforward neural networks BibRef

Abadi, A., Rajabioun, T., Ioannou, P.A.,
Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data,
ITS(16), No. 2, April 2015, pp. 653-662.
IEEE DOI 1504
Estimation BibRef

Lv, Y.S.[Yi-Sheng], Duan, Y.J.[Yan-Jie], Kang, W.W.[Wen-Wen], Li, Z.X.[Zheng-Xi], Wang, F.Y.[Fei-Yue],
Traffic Flow Prediction With Big Data: A Deep Learning Approach,
ITS(16), No. 2, April 2015, pp. 865-873.
IEEE DOI 1504
Adaptation models BibRef

Du, W.B.[Wen-Bo], Chen, S.W.[Shen-Wen], Li, H.T.[Hai-Tao], Li, Z.S.[Zhi-Shuai], Cao, X.B.[Xian-Bin], Lv, Y.S.[Yi-Sheng],
Airport Capacity Prediction With Multisource Features: A Temporal Deep Learning Approach,
ITS(24), No. 1, January 2023, pp. 615-630.
IEEE DOI 2301
Airports, Feature extraction, Atmospheric modeling, Predictive models, Prediction algorithms, Clustering algorithms, deep learning BibRef

Chen, Y., Lv, Y., Wang, X., Li, L., Wang, F.,
Detecting Traffic Information From Social Media Texts With Deep Learning Approaches,
ITS(20), No. 8, August 2019, pp. 3049-3058.
IEEE DOI 1908
Data mining, Twitter, Feature extraction, Support vector machines, Predictive models, Real-time systems, Deep learning, text mining BibRef

Oh, S.D.[Se-Do], Kim, Y.J.[Young-Jin], Hong, J.S.[Ji-Sun],
Urban Traffic Flow Prediction System Using a Multifactor Pattern Recognition Model,
ITS(16), No. 5, October 2015, pp. 2744-2755.
IEEE DOI 1511
Gaussian processes BibRef

Dell'Acqua, P., Bellotti, F., Berta, R., de Gloria, A.,
Time-Aware Multivariate Nearest Neighbor Regression Methods for Traffic Flow Prediction,
ITS(16), No. 6, December 2015, pp. 3393-3402.
IEEE DOI 1512
Artificial neural networks BibRef

Oh, S., Byon, Y.J., Yeo, H.,
Improvement of Search Strategy With K-Nearest Neighbors Approach for Traffic State Prediction,
ITS(17), No. 4, April 2016, pp. 1146-1156.
IEEE DOI 1604
Acceleration BibRef

Hou, Z., Li, X.,
Repeatability and Similarity of Freeway Traffic Flow and Long-Term Prediction Under Big Data,
ITS(17), No. 6, June 2016, pp. 1786-1796.
IEEE DOI 1606
Analytical models BibRef

Zhao, J., Sun, S.,
High-Order Gaussian Process Dynamical Models for Traffic Flow Prediction,
ITS(17), No. 7, July 2016, pp. 2014-2019.
IEEE DOI 1608
Gaussian processes BibRef

Abbasi, O.R.[Omid Reza], Alesheikh, A.A.[Ali Asghar], Sharif, M.[Mohammad],
Ranking the City: The Role of Location-Based Social Media Check-Ins in Collective Human Mobility Prediction,
IJGI(6), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Tang, J., Liu, F., Zou, Y., Zhang, W., Wang, Y.,
An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic,
ITS(18), No. 9, September 2017, pp. 2340-2350.
IEEE DOI 1709
Gaussian processes, forecasting theory, fuzzy neural nets, fuzzy reasoning, Takagi-Sugeno type fuzzy rules, BibRef

Xiao, Z., Ponnambalam, L., Fu, X., Zhang, W.,
Maritime Traffic Probabilistic Forecasting Based on Vessels-Waterway Patterns and Motion Behaviors,
ITS(18), No. 11, November 2017, pp. 3122-3134.
IEEE DOI 1711
Artificial intelligence, Data mining, Forecasting, Planning, Prediction algorithms, Stability analysis, Transportation, Data mining, knowledge discovery, knowledge engineering, marine, transportation BibRef

Zhang, Y.[Yaying], Huang, G.[Guan],
traffic flow prediction model based on deep belief network and genetic algorithm,
IET-ITS(12), No. 6, August 2018, pp. 533-541.
DOI Link 1807
BibRef

Zhang, D.[Da], Kabuka, M.R.[Mansur R.],
Combining weather condition data to predict traffic flow: A GRU-based deep learning approach,
IET-ITS(12), No. 7, September 2018, pp. 578-585.
DOI Link 1808
BibRef

Besse, P.C., Guillouet, B., Loubes, J.M., Royer, F.,
Destination Prediction by Trajectory Distribution-Based Model,
ITS(19), No. 8, August 2018, pp. 2470-2481.
IEEE DOI 1808
Trajectory, Public transportation, Predictive models, Roads, Data models, Markov processes, Vehicles, Trajectory classification, final destination prediction BibRef

Huang, W., Jia, W., Guo, J., Williams, B.M., Shi, G., Wei, Y., Cao, J.,
Real-Time Prediction of Seasonal Heteroscedasticity in Vehicular Traffic Flow Series,
ITS(19), No. 10, October 2018, pp. 3170-3180.
IEEE DOI 1810
Predictive models, Adaptation models, Data models, Forecasting, Analytical models, Real-time systems, Transportation, adaptive Kalman filter BibRef

Maeda, T.N.[Takashi Nicholas], Mori, J.[Junichiro], Ochi, M.[Masanao], Sakimoto, T.[Tetsuo], Sakata, I.[Ichiro],
Measurement of Opportunity Cost of Travel Time for Predicting Future Residential Mobility Based on the Smart Card Data of Public Transportation,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Zhan, H., Gomes, G., Li, X.S., Madduri, K., Sim, A., Wu, K.,
Consensus Ensemble System for Traffic Flow Prediction,
ITS(19), No. 12, December 2018, pp. 3903-3914.
IEEE DOI 1812
Predictive models, Computational modeling, Forecasting, Time series analysis, Data models, traffic flow prediction BibRef

Xue, Z.L.[Ze-Long], Xue, Y.[Yang],
Multi Long-Short Term Memory Models for Short Term Traffic Flow Prediction,
IEICE(E101-D), No. 12, December 2018, pp. 3272-3275.
WWW Link. 1812
BibRef

Guo, S.N.[Sheng-Nan], Lin, Y.F.[You-Fang], Li, S.J.[Shi-Jie], Chen, Z.M.[Zhao-Ming], Wan, H.Y.[Huai-Yu],
Deep Spatial-Temporal 3D Convolutional Neural Networks for Traffic Data Forecasting,
ITS(20), No. 10, October 2019, pp. 3913-3926.
IEEE DOI 1910
Correlation, Forecasting, Data models, Feature extraction, Predictive models, Solid modeling, recalibration block BibRef

Zhao, Y.J.[Yi-Ji], Lin, Y.F.[You-Fang], Wen, H.M.[Hao-Min], Wei, T.L.[Tong-Long], Jin, X.Y.[Xi-Yuan], Wan, H.Y.[Huai-Yu],
Spatial-Temporal Position-Aware Graph Convolution Networks for Traffic Flow Forecasting,
ITS(24), No. 8, August 2023, pp. 8650-8666.
IEEE DOI 2308
Correlation, Convolution, Forecasting, Predictive models, Feature extraction, Roads, Data models, Traffic flow forecasting, graph convolution networks BibRef

Song, Y., Wang, X., Wright, G., Thatcher, D., Wu, P., Felix, P.,
Traffic Volume Prediction With Segment-Based Regression Kriging and its Implementation in Assessing the Impact of Heavy Vehicles,
ITS(20), No. 1, January 2019, pp. 232-243.
IEEE DOI 1901
Roads, Maintenance engineering, Predictive models, Australia, Correlation, Estimation, Sociology, Geostatistics, road maintenance BibRef

Chu, K., Saigal, R., Saitou, K.,
Real-Time Traffic Prediction and Probing Strategy for Lagrangian Traffic Data,
ITS(20), No. 2, February 2019, pp. 497-506.
IEEE DOI 1902
Data models, Real-time systems, Predictive models, Adaptation models, Computational modeling, Stochastic processes, adaptive data collection BibRef

Pamula, T.,
Impact of Data Loss for Prediction of Traffic Flow on an Urban Road Using Neural Networks,
ITS(20), No. 3, March 2019, pp. 1000-1009.
IEEE DOI 1903
Roads, Neurons, Neural networks, Machine learning, Predictive models, Data models, Adaptation models, Deep learning, sensitivity to loss of data BibRef

Ghanim, M.S.[Mohammad S.], Abu-Lebdeh, G.[Ghassan],
Projected state-wide traffic forecast parameters using artificial neural networks,
IET-ITS(13), No. 4, April 2019, pp. 661-669.
DOI Link 1903
BibRef

Chen, X., Zhang, S., Li, L., Li, L.,
Adaptive Rolling Smoothing With Heterogeneous Data for Traffic State Estimation and Prediction,
ITS(20), No. 4, April 2019, pp. 1247-1258.
IEEE DOI 1904
State estimation, Smoothing methods, Time measurement, Vehicle dynamics, Cameras, Microwave measurement, urban expressway BibRef

Lin, Y., Dai, X., Li, L., Wang, F.,
Pattern Sensitive Prediction of Traffic Flow Based on Generative Adversarial Framework,
ITS(20), No. 6, June 2019, pp. 2395-2400.
IEEE DOI 1906
Predictive models, Biological system modeling, Data models, Automation, Machine learning, Industries, Traffic flow prediction, generative adversarial network BibRef

Ganapathy, J.[Jayanthi], Paramasivam, J.[Jothilakshmi],
Prediction of traffic volume by mining traffic sequences using travel time based PrefixSpan,
IET-ITS(13), No. 7, July 2019, pp. 1199-1210.
DOI Link 1906
BibRef

Yang, D.[Di], Li, S.J.[Song-Jiang], Peng, Z.[Zhou], Wang, P.[Peng], Wang, J.H.[Jun-Hui], Yang, H.M.[Hua-Min],
MF-CNN: Traffic Flow Prediction Using Convolutional Neural Network and Multi-Features Fusion,
IEICE(E102-D), No. 8, August 2019, pp. 1526-1536.
WWW Link. 1908
BibRef

Liu, Y.[Yu], Liu, Z.[Zhao], Li, X.G.[Xiu-Gang], Huang, W.[Wei], Wei, Y.[Yun], Cao, J.[Jinde], Guo, J.H.[Jian-Hua],
Dynamic traffic demand uncertainty prediction using radio-frequency identification data and link volume data,
IET-ITS(13), No. 8, August 2019, pp. 1309-1317.
DOI Link 1908
BibRef

Zheng, Z., Yang, Y., Liu, J., Dai, H., Zhang, Y.,
Deep and Embedded Learning Approach for Traffic Flow Prediction in Urban Informatics,
ITS(20), No. 10, October 2019, pp. 3927-3939.
IEEE DOI 1910
Meteorology, Predictive models, Urban areas, Deep learning, Sensors, Roads, Informatics, Urban informatics, traffic flow prediction, deep learning BibRef

Chang, B., Chiou, J.,
Cloud Computing-Based Analyses to Predict Vehicle Driving Shockwave for Active Safe Driving in Intelligent Transportation System,
ITS(21), No. 2, February 2020, pp. 852-866.
IEEE DOI 2002
Cloud computing, Microscopy, Real-time systems, Delays, 5G mobile communication, Roads, Sensors, VCC, MEC, macroscopic and microscopic analyses BibRef

Zheng, C.P.[Chuan-Pan], Fan, X.L.[Xiao-Liang], Wen, C.L.[Cheng-Lu], Chen, L.B.[Long-Biao], Wang, C.[Cheng], Li, J.[Jonathan],
DeepSTD: Mining Spatio-Temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction,
ITS(21), No. 9, September 2020, pp. 3744-3755.
IEEE DOI 2008
Neural networks, Meteorology, Predictive models, Deep learning, Urban areas, Intelligent transportation systems, intelligent transportation systems BibRef

Zhao, L.[Ling], Song, Y.J.[Yu-Jiao], Zhang, C.[Chao], Liu, Y.[Yu], Wang, P.[Pu], Lin, T.[Tao], Deng, M.[Min], Li, H.F.[Hai-Feng],
T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction,
ITS(21), No. 9, September 2020, pp. 3848-3858.
IEEE DOI 2008
Predictive models, Forecasting, Roads, Data models, Task analysis, Logic gates, Kalman filters, Traffic forecasting, temporal dependence BibRef

Bai, J.D.[Jian-Dong], Zhu, J.W.[Jia-Wei], Song, Y.J.[Yu-Jiao], Zhao, L.[Ling], Hou, Z.X.[Zhi-Xiang], Du, R.H.[Rong-Hua], Li, H.F.[Hai-Feng],
A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Zhu, J.W.[Jia-Wei], Han, X.[Xing], Deng, H.[Hanhan], Tao, C.[Chao], Zhao, L.[Ling], Wang, P.[Pu], Lin, T.[Tao], Li, H.F.[Hai-Feng],
KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting,
ITS(23), No. 9, September 2022, pp. 15055-15065.
IEEE DOI 2209
Roads, Forecasting, Predictive models, Data models, Semantics, Correlation, Mathematical models, Traffic flow forecasting, spatial-temporal graph convolutional networks BibRef

Sun, B.[Bo], Sun, T.[Tuo], Zhang, Y.J.[Yu-Jia], Jiao, P.P.[Peng-Peng],
Urban traffic flow online prediction based on multi-component attention mechanism,
IET-ITS(14), No. 10, October 2020, pp. 1249-1258.
DOI Link 2009
BibRef

Xu, D.W.[Dong-Wei], Peng, P.[Peng], Wei, C.C.[Chen-Chen], He, D.F.[De-Feng], Xuan, Q.[Qi],
Road traffic network state prediction based on a generative adversarial network,
IET-ITS(14), No. 10, October 2020, pp. 1286-1294.
DOI Link 2009
BibRef

Cui, Z., Henrickson, K., Ke, R., Wang, Y.,
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting,
ITS(21), No. 11, November 2020, pp. 4883-4894.
IEEE DOI 2011
Convolution, Forecasting, Predictive models, Roads, Machine learning, Feature extraction, Artificial neural networks, recurrent neural network BibRef

Zhang, Y., Wang, S., Chen, B., Cao, J., Huang, Z.,
TrafficGAN: Network-Scale Deep Traffic Prediction With Generative Adversarial Nets,
ITS(22), No. 1, January 2021, pp. 219-230.
IEEE DOI 2012
Roads, Predictive models, Correlation, Data models, Deep learning, Forecasting, Traffic prediction, deep learning 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

Guo, K.[Kan], Hu, Y.L.[Yong-Li], Qian, Z.[Zhen], Liu, H.[Hao], Zhang, K.[Ke], Sun, Y.F.[Yan-Feng], Gao, J.B.[Jun-Bin], Yin, B.C.[Bao-Cai],
Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction,
ITS(22), No. 2, February 2021, pp. 1138-1149.
IEEE DOI 2102
Roads, Convolution, Recurrent neural networks, Training, Graph convolution network, recurrent neural network, traffic prediction BibRef

Sun, Y.F.[Yan-Feng], Jiang, X.H.[Xiang-Heng], Hu, Y.L.[Yong-Li], Duan, F.Q.[Fu-Qing], Guo, K.[Kan], Wang, B.Y.[Bo-Yue], Gao, J.B.[Jun-Bin], Yin, B.C.[Bao-Cai],
Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction,
ITS(23), No. 12, December 2022, pp. 23680-23693.
IEEE DOI 2212
Roads, Convolution, Predictive models, Correlation, Data models, Vehicle dynamics, Transportation, Graph convolution network, intelligent transportation systems BibRef

Low, R., Cheah, L., You, L.,
Commercial Vehicle Activity Prediction With Imbalanced Class Distribution Using a Hybrid Sampling and Gradient Boosting Approach,
ITS(22), No. 3, March 2021, pp. 1401-1410.
IEEE DOI 2103
Frequency modulation, Predictive models, Vehicles, Boosting, Data models, Prediction algorithms, Feature extraction, imbalanced dataset BibRef

Wang, Y., Yu, X., Zhang, S., Zheng, P., Guo, J., Zhang, L., Hu, S., Cheng, S., Wei, H.,
Freeway Traffic Control in Presence of Capacity Drop,
ITS(22), No. 3, March 2021, pp. 1497-1516.
IEEE DOI 2103
Traffic control, Optimal control, Data models, Analytical models, Merging, Mathematical model, Feedback control, macroscopic traffic flow modeling BibRef

Ma, D.F.[Dong-Fang], Song, X.[Xiang], Li, P.[Pu],
Daily Traffic Flow Forecasting Through a Contextual Convolutional Recurrent Neural Network Modeling Inter- and Intra-Day Traffic Patterns,
ITS(22), No. 5, May 2021, pp. 2627-2636.
IEEE DOI 2105
Forecasting, Machine learning, Time series analysis, Data mining, Predictive models, Recurrent neural networks, Context modeling, long short-term memory BibRef

Jia, T.[Tao], Yan, P.G.[Peng-Gao],
Predicting Citywide Road Traffic Flow Using Deep Spatiotemporal Neural Networks,
ITS(22), No. 5, May 2021, pp. 3101-3111.
IEEE DOI 2105
BibRef
And: Correction: ITS(22), No. 6, June 2021, pp. 3900-3900.
IEEE DOI 2106
Roads, Spatiotemporal phenomena, Predictive models, Neural networks, Autoregressive processes, Image segmentation, trajectory data BibRef

Lv, M.Q.[Ming-Qi], Hong, Z.X.[Zhao-Xiong], Chen, L.[Ling], Chen, T.M.[Tie-Ming], Zhu, T.T.[Tian-Tian], Ji, S.[Shouling],
Temporal Multi-Graph Convolutional Network for Traffic Flow Prediction,
ITS(22), No. 6, June 2021, pp. 3337-3348.
IEEE DOI 2106
Correlation, Roads, Semantics, Predictive models, Machine learning, Convolution, Analytical models, Traffic flow prediction, graph fusion BibRef

Chen, L.[Ling], Shao, W.[Wei], Lv, M.Q.[Ming-Qi], Chen, W.Q.[Wei-Qi], Zhang, Y.D.[You-Dong], Yang, C.H.[Cheng-Hu],
AARGNN: An Attentive Attributed Recurrent Graph Neural Network for Traffic Flow Prediction Considering Multiple Dynamic Factors,
ITS(23), No. 10, October 2022, pp. 17201-17211.
IEEE DOI 2210
Correlation, Sensors, Data models, Roads, Predictive models, Sensor phenomena and characterization, Semantics, urban computing BibRef

Chen, C.[Chen], Liu, Z.Y.[Zi-Ye], Wan, S.H.[Shao-Hua], Luan, J.T.[Jin-Tai], Pei, Q.Q.[Qing-Qi],
Traffic Flow Prediction Based on Deep Learning in Internet of Vehicles,
ITS(22), No. 6, June 2021, pp. 3776-3789.
IEEE DOI 2106
Roads, Predictive models, Machine learning, Feature extraction, Prediction algorithms, Computational modeling, Urban areas, traffic compression BibRef

Bhanu, M.[Manish], Mendes-Moreira, J.[João], Chandra, J.[Joydeep],
Embedding Traffic Network Characteristics Using Tensor for Improved Traffic Prediction,
ITS(22), No. 6, June 2021, pp. 3359-3371.
IEEE DOI 2106
Tensile stress, Urban areas, Matrix decomposition, Forecasting, Public transportation, Predictive models, Traffic prediction, reciprocity BibRef

Chen, M.[Meng], Zuo, Y.X.[Yi-Xuan], Jia, X.Y.[Xiao-Yi], Liu, Y.[Yang], Yu, X.H.[Xiao-Hui], Zheng, K.[Kai],
CEM: A Convolutional Embedding Model for Predicting Next Locations,
ITS(22), No. 6, June 2021, pp. 3349-3358.
IEEE DOI 2106
Trajectory, Predictive models, Data models, Roads, Recurrent neural networks, Context modeling, Convolution, traffic trajectory data BibRef

Liu, J.[Jin], Wu, N.Q.[Nai-Qi], Qiao, Y.[Yan], Li, Z.W.[Zhi-Wu],
A scientometric review of research on traffic forecasting in transportation,
IET-ITS(15), No. 1, 2021, pp. 1-16.
DOI Link 2106
BibRef

Tian, C.Y.[Chen-Yu], Chan, W.K.V.[Wai Kin Victor],
Spatial-temporal attention wavenet: A deep learning framework for traffic prediction considering spatial-temporal dependencies,
IET-ITS(15), No. 4, 2021, pp. 549-561.
DOI Link 2106
BibRef

Azad, A.[Abul], Wang, X.[Xin],
Land Use Change Ontology and Traffic Prediction through Recurrent Neural Networks: A Case Study in Calgary, Canada,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Liu, M.H.[Meng-Hang], Li, L.N.[Lu-Ning], Li, Q.[Qiang], Bai, Y.[Yu], Hu, C.[Cheng],
Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Ren, C.[Chang], Tang, L.[Luliang], Long, J.[Jed], Kan, Z.H.[Zi-Han], Yang, X.[Xue],
Modelling Place Visit Probability Sequences during Trajectory Data Gaps Based on Movement History,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Shi, X.M.[Xiao-Ming], Qi, H.[Heng], Shen, Y.M.[Yan-Ming], Wu, G.[Genze], Yin, B.C.[Bao-Cai],
A Spatial-Temporal Attention Approach for Traffic Prediction,
ITS(22), No. 8, August 2021, pp. 4909-4918.
IEEE DOI 2108
Correlation, Neural networks, Predictive models, Roads, Convolution, Semantics, Time series analysis, Attention mechanism, neural networks BibRef

Giammarino, V.[Vittorio], Baldi, S.[Simone], Frasca, P.[Paolo], Monache, M.L.D.[Maria Laura Delle],
Traffic Flow on a Ring With a Single Autonomous Vehicle: An Interconnected Stability Perspective,
ITS(22), No. 8, August 2021, pp. 4998-5008.
IEEE DOI 2108
Asymptotic stability, Autonomous vehicles, Stability criteria, Numerical stability, Transfer functions, Structural rings, ring roadway BibRef

Yi, H.[Hongsuk], Bui, K.H.N.[Khac-Hoai Nam],
An Automated Hyperparameter Search-Based Deep Learning Model for Highway Traffic Prediction,
ITS(22), No. 9, September 2021, pp. 5486-5495.
IEEE DOI 2109
Road transportation, Predictive models, Training, Tuning, Optimization, Bayes methods, Deep learning, meta learning BibRef

Xiao, X.[Xiao], Jin, Z.L.[Zhi-Ling], Hui, Y.L.[Yi-Long], Xu, Y.[Yueshen], Shao, W.[Wei],
Hybrid Spatial-Temporal Graph Convolutional Networks for On-Street Parking Availability Prediction,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Chen, K.Q.[Kai-Qi], Deng, M.[Min], Shi, Y.[Yan],
A Temporal Directed Graph Convolution Network for Traffic Forecasting Using Taxi Trajectory Data,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Das, A.[Arindam], Gangwar, M.K.[Manoj Kumar], Ghosh, D.[Devleena], Mandal, C.[Chittaranjan], Sengupta, A.[Anirban], Waris, M.M.[M. Mubashshir],
Automatic Generation of Route Control Chart From Validated Signal Interlocking Plan,
ITS(22), No. 10, October 2021, pp. 6516-6525.
IEEE DOI 2110
Rail transportation, Layout, Tools, Graphical user interfaces, Safety, Control charts, Standards, Railway signalling, validation and verification (V&V) BibRef

Wang, Z.M.[Zhu-Mei], Su, X.[Xing], Ding, Z.M.[Zhi-Ming],
Long-Term Traffic Prediction Based on LSTM Encoder-Decoder Architecture,
ITS(22), No. 10, October 2021, pp. 6561-6571.
IEEE DOI 2110
Predictive models, Forecasting, Deep learning, Calibration, Neural networks, Prediction algorithms, attention BibRef

Guo, Z.G.[Zhen-Gang], Zhang, Y.F.[Ying-Feng], Lv, J.X.[Jing-Xiang], Liu, Y.[Yang], Liu, Y.[Ying],
An Online Learning Collaborative Method for Traffic Forecasting and Routing Optimization,
ITS(22), No. 10, October 2021, pp. 6634-6645.
IEEE DOI 2110
Roads, Real-time systems, Forecasting, Routing, Optimization, Predictive models, Collaboration, Online learning, cyber-physical systems BibRef

He, Z.X.[Zhi-Xiang], Chow, C.Y.[Chi-Yin], Zhang, J.D.[Jia-Dong],
STNN: A Spatio-Temporal Neural Network for Traffic Predictions,
ITS(22), No. 12, December 2021, pp. 7642-7651.
IEEE DOI 2112
Roads, Predictive models, Time series analysis, Neural networks, Data models, Computational modeling, Decoding, Traffic predictions, attention model BibRef

Liu, L.B.[Ling-Bo], Zhen, J.J.[Jia-Jie], Li, G.B.[Guan-Bin], Zhan, G.[Geng], He, Z.C.[Zhao-Cheng], Du, B.[Bowen], Lin, L.[Liang],
Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction,
ITS(22), No. 11, November 2021, pp. 7169-7183.
IEEE DOI 2112
Predictive models, Urban areas, Neural networks, Task analysis, Feature extraction, attentional recurrent neural network BibRef

Liu, Y.[Yang], Wang, K.[Keze], Liu, L.B.[Ling-Bo], Lan, H.Y.[Hao-Yuan], Lin, L.[Liang],
TCGL: Temporal Contrastive Graph for Self-Supervised Video Representation Learning,
IP(31), 2022, pp. 1978-1993.
IEEE DOI 2202
Code, Action Recognition.
WWW Link. Task analysis, Representation learning, Discrete cosine transforms, Legged locomotion, spatial-temporal data analysis BibRef

Luo, X.Y.[Xiao-Yi], Peng, J.H.[Jia-Heng], Liang, J.[Jun],
Directed hypergraph attention network for traffic forecasting,
IET-ITS(16), No. 1, 2022, pp. 85-98.
DOI Link 2112
BibRef

Liu, D.[Di], Baldi, S.[Simone], Yu, W.W.[Wen-Wu], Cao, J.[Jinde], Huang, W.[Wei],
On Training Traffic Predictors via Broad Learning Structures: A Benchmark Study,
SMCS(52), No. 2, February 2022, pp. 749-758.
IEEE DOI 2201
Training, Prediction algorithms, Zinc, Testing, Real-time systems, Learning systems, traffic flow prediction BibRef

Ren, Y.J.[Ya-Jie], Zhao, D.[Dong], Luo, D.[Dan], Ma, H.D.[Hua-Dong], Duan, P.R.[Peng-Rui],
Global-Local Temporal Convolutional Network for Traffic Flow Prediction,
ITS(23), No. 2, February 2022, pp. 1578-1584.
IEEE DOI 2202
Convolution, Feature extraction, Predictive models, Data models, Urban areas, Machine learning, neural network BibRef

Li, Z.S.[Zhi-Shuai], Xiong, G.[Gang], Tian, Y.L.[Yong-Lin], Lv, Y.S.[Yi-Sheng], Chen, Y.Y.[Yuan-Yuan], Hui, P.[Pan], Su, X.[Xiang],
A Multi-Stream Feature Fusion Approach for Traffic Prediction,
ITS(23), No. 2, February 2022, pp. 1456-1466.
IEEE DOI 2202
Feature extraction, Roads, Monitoring, Predictive models, Convolution, Neural networks, Computational modeling, data-driven adjacent matrix BibRef

Wu, S.F.[Shao-Fei],
Spatiotemporal Dynamic Forecasting and Analysis of Regional Traffic Flow in Urban Road Networks Using Deep Learning Convolutional Neural Network,
ITS(23), No. 2, February 2022, pp. 1607-1615.
IEEE DOI 2202
Convolution, Roads, Forecasting, Predictive models, Feature extraction, Convolutional neural networks, BiLSTM BibRef

Zhang, C.[Chi], Zhou, H.Y.[Hong-Yu], Qiu, Q.[Qiang], Jian, Z.C.[Zhi-Chun], Zhu, D.[Daoye], Cheng, C.Q.[Cheng-Qi], He, L.S.[Lie-Song], Liu, G.P.[Guo-Ping], Wen, X.[Xiang], Hu, R.[Runbo],
Augmented Multi-Component Recurrent Graph Convolutional Network for Traffic Flow Forecasting,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Li, X.L.[Xiao-Long], Xia, J.[Jing], Chen, X.Y.[Xiao-Yong], Tan, Y.B.[Yong-Bin], Chen, J.[Jing],
SIT: A Spatial Interaction-Aware Transformer-Based Model for Freeway Trajectory Prediction,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Wang, Y.[Yi], Jing, C.F.[Chang-Feng],
Spatiotemporal Graph Convolutional Network for Multi-Scale Traffic Forecasting,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Shin, Y.[Yuyol], Yoon, Y.[Yoonjin],
Incorporating Dynamicity of Transportation Network With Multi-Weight Traffic Graph Convolutional Network for Traffic Forecasting,
ITS(23), No. 3, March 2022, pp. 2082-2092.
IEEE DOI 2203
Forecasting, Predictive models, Convolution, Roads, Data models, Deep learning, Deep learning, graph convolutional network, transportation network BibRef

Huo, G.Y.[Guang-Yu], Zhang, Y.[Yong], Wang, B.Y.[Bo-Yue], Hu, Y.L.[Yong-Li], Yin, B.C.[Bao-Cai],
Text-to-Traffic Generative Adversarial Network for Traffic Situation Generation,
ITS(23), No. 3, March 2022, pp. 2623-2636.
IEEE DOI 2203
Social networking (online), Generative adversarial networks, Data models, Semantics, Generators, Blogs, Predictive models, condition generative adversarial network BibRef

Chen, Y.Y.[Yuan-Yuan], Chen, H.Y.[Hong-Yu], Ye, P.J.[Pei-Jun], Lv, Y.S.[Yi-Sheng], Wang, F.Y.[Fei-Yue],
Acting as a Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction,
ITS(23), No. 4, April 2022, pp. 3190-3200.
IEEE DOI 2204
Predictive models, Feature extraction, Training, Data models, Spatiotemporal phenomena, Stacking, Convolution, deep learning BibRef

Lai, Y.X.[Yong-Xuan], Xu, Y.F.[Yi-Fan], Mai, D.[Duojian], Fan, Y.[Yi], Yang, F.[Fan],
Optimized Large-Scale Road Sensing Through Crowdsourced Vehicles,
ITS(23), No. 4, April 2022, pp. 3878-3889.
IEEE DOI 2204
Sensors, Task analysis, Crowdsensing, Roads, Costs, Urban areas, Fans, Vehicular crowdsensing, maximal weighted sensing paths, least-interrupted urban sensing BibRef

Avedisov, S.S.[Sergei S.], Bansal, G.[Gaurav], Orosz, G.[Gábor],
Impacts of Connected Automated Vehicles on Freeway Traffic Patterns at Different Penetration Levels,
ITS(23), No. 5, May 2022, pp. 4305-4318.
IEEE DOI 2205
Vehicle-to-everything, Connected vehicles, Vehicle dynamics, Automobiles, Numerical models, Aerodynamics, traffic flow BibRef

Su, J.[Jie], Jin, Z.F.[Zhong-Fu], Ren, J.[Jie], Yang, J.[Jiandang], Liu, Y.[Yong],
GDFormer: A Graph Diffusing Attention based approach for Traffic Flow Prediction,
PRL(156), 2022, pp. 126-132.
Elsevier DOI 2205
Graph neural network, Diffusion process, Attention mechanism, Traffic flow prediction BibRef

Paliwal, C.[Charul], Bhatt, U.[Uttkarsha], Biyani, P.[Pravesh], Rajawat, K.[Ketan],
Traffic Estimation and Prediction via Online Variational Bayesian Subspace Filtering,
ITS(23), No. 5, May 2022, pp. 4674-4684.
IEEE DOI 2205
Bayes methods, Estimation, Prediction algorithms, Tensors, Roads, Probability density function, Predictive models, robust matrix completion BibRef

Yin, X.Y.[Xue-Yan], Wu, G.[Genze], Wei, J.Z.[Jin-Ze], Shen, Y.M.[Yan-Ming], Qi, H.[Heng], Yin, B.C.[Bao-Cai],
Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions,
ITS(23), No. 6, June 2022, pp. 4927-4943.
IEEE DOI 2206
Deep learning, Correlation, Predictive models, Data models, Convolution, Roads, Learning systems, Traffic prediction, spatial-temporal dependency modeling BibRef

Manibardo, E.L.[Eric L.], Laña, I.[Ibai], del Ser, J.[Javier],
Deep Learning for Road Traffic Forecasting: Does it Make a Difference?,
ITS(23), No. 7, July 2022, pp. 6164-6188.
IEEE DOI 2207
Forecasting, Deep learning, Predictive models, Roads, Data models, Time series analysis, Task analysis, Machine learning, spatio-temporal data mining BibRef

Li, D.[Duo], Lasenby, J.[Joan],
Spatiotemporal Attention-Based Graph Convolution Network for Segment-Level Traffic Prediction,
ITS(23), No. 7, July 2022, pp. 8337-8345.
IEEE DOI 2207
Roads, Feature extraction, Spatiotemporal phenomena, Deep learning, Predictive models, Meteorology, Detectors, Traffic prediction, attention mechanism BibRef

Zhang, S.[Shaokun], Guo, Y.[Yao], Zhao, P.[Peize], Zheng, C.P.[Chuan-Pan], Chen, X.Q.[Xiang-Qun],
A Graph-Based Temporal Attention Framework for Multi-Sensor Traffic Flow Forecasting,
ITS(23), No. 7, July 2022, pp. 7743-7758.
IEEE DOI 2207
Roads, Predictive models, Forecasting, Data models, Correlation, Topology, Network topology, Traffic flow prediction, road network distance BibRef

Yu, J.J.Q.[James J. Q.], Markos, C.[Christos], Zhang, S.Y.[Shi-Yao],
Long-Term Urban Traffic Speed Prediction With Deep Learning on Graphs,
ITS(23), No. 7, July 2022, pp. 7359-7370.
IEEE DOI 2207
Correlation, Deep learning, Transportation, Forecasting, Data mining, Predictive models, Training, Traffic speed prediction, data mining BibRef

Abdelraouf, A.[Amr], Abdel-Aty, M.[Mohamed], Yuan, J.H.[Jing-Hui],
Utilizing Attention-Based Multi-Encoder-Decoder Neural Networks for Freeway Traffic Speed Prediction,
ITS(23), No. 8, August 2022, pp. 11960-11969.
IEEE DOI 2208
Predictive models, Feature extraction, Roads, Decoding, Computational modeling, Traffic control, Data mining, explainable neural networks BibRef

Shi, R.Y.[Rong-Ye], Mo, Z.B.[Zhao-Bin], Huang, K.[Kuang], Di, X.[Xuan], Du, Q.[Qiang],
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation,
ITS(23), No. 8, August 2022, pp. 11688-11698.
IEEE DOI 2208
Mathematical model, Data models, Maximum likelihood estimation, Physics, Deep learning, Urban areas, Predictive models, physics-informed deep learning BibRef

Pavlyuk, D.[Dmitry],
Robust and Responsive Learning of Spatiotemporal Urban Traffic Flow Relationships,
ITS(23), No. 9, September 2022, pp. 14524-14541.
IEEE DOI 2209
Spatiotemporal phenomena, Forecasting, Predictive models, Roads, Feature extraction, Heuristic algorithms, Time series analysis, variable selection BibRef

Yu, J.J.Q.[James J. Q.],
Graph Construction for Traffic Prediction: A Data-Driven Approach,
ITS(23), No. 9, September 2022, pp. 15015-15027.
IEEE DOI 2209
Correlation, Training, Convolution, Laplace equations, Deep learning, Predictive models, Transportation, Traffic graph construction, data mining BibRef

Ge, L.F.[Liang-Fu], Dan, D.H.[Dan-Hui], Liu, Z.J.[Zi-Jia], Ruan, X.[Xin],
Intelligent Simulation Method of Bridge Traffic Flow Load Combining Machine Vision and Weigh-in-Motion Monitoring,
ITS(23), No. 9, September 2022, pp. 15313-15328.
IEEE DOI 2209
Bridges, Load modeling, Length measurement, Data models, Position measurement, Machine vision, Axles, Traffic flow load, Intelligent Driver Model BibRef

Wang, H.Q.[Han-Qiu], Zhang, R.Q.[Rong-Qing], Cheng, X.[Xiang], Yang, L.Q.[Liu-Qing],
Hierarchical Traffic Flow Prediction Based on Spatial-Temporal Graph Convolutional Network,
ITS(23), No. 9, September 2022, pp. 16137-16147.
IEEE DOI 2209
Predictive models, Data models, Protocols, Roads, Correlation, Urban areas, Support vector machines, traffic flow prediction BibRef

Hu, H.[Hexuan], Lin, Z.Z.[Zhen-Zhou], Hu, Q.[Qiang], Zhang, Y.[Ye],
Attention Mechanism With Spatial-Temporal Joint Model for Traffic Flow Speed Prediction,
ITS(23), No. 9, September 2022, pp. 16612-16621.
IEEE DOI 2209
Predictive models, Deep learning, Data models, Mathematical models, Roads, Task analysis, Urban areas, attention mechanism BibRef

Xing, L.[Lumin], Liu, W.J.[Wen-Jian],
A Data Fusion Powered Bi-Directional Long Short Term Memory Model for Predicting Multi-Lane Short Term Traffic Flow,
ITS(23), No. 9, September 2022, pp. 16810-16819.
IEEE DOI 2209
Predictive models, Roads, Spatiotemporal phenomena, Data models, Hidden Markov models, Correlation, Real-time systems, DFBD-LSTM BibRef

Wu, X.Y.[Xiang-Yang], Zhu, W.[Weite], Liu, Z.[Zhen], Zhang, Z.[Zhen],
A Novel Vehicle Destination Prediction Model With Expandable Features Using Attention Mechanism and Variational Autoencoder,
ITS(23), No. 9, September 2022, pp. 16548-16557.
IEEE DOI 2209
Predictive models, Data models, Vehicle driving, Trajectory, Feature extraction, Mathematical models, Load modeling, attentional mechanisms BibRef

Su, Y.C.[Yu-Chao], Du, J.[Jie], Li, Y.M.[Yuan-Man], Li, X.[Xia], Liang, R.Q.[Rong-Qin], Hua, Z.Y.[Zhong-Yun], Zhou, J.T.[Jian-Tao],
Trajectory Forecasting Based on Prior-Aware Directed Graph Convolutional Neural Network,
ITS(23), No. 9, September 2022, pp. 16773-16785.
IEEE DOI 2209
Trajectory, Predictive models, Directed graphs, Generative adversarial networks, Topology, Feature extraction, asymmetric interactions BibRef

Wang, Y.[Yang], Zheng, J.[Jin], Du, Y.Q.[Yu-Qi], Huang, C.[Cheng], Li, P.[Ping],
Traffic-GGNN: Predicting Traffic Flow via Attentional Spatial-Temporal Gated Graph Neural Networks,
ITS(23), No. 10, October 2022, pp. 18423-18432.
IEEE DOI 2210
Predictive models, Graph neural networks, Logic gates, Bidirectional control, Task analysis, Correlation, Message passing, traffic flow prediction BibRef

Dai, F.[Fei], Huang, P.G.[Peng-Gui], Mo, Q.[Qi], Xu, X.L.[Xiao-Long], Bilal, M.[Muhammad], Song, H.[Houbing],
ST-InNet: Deep Spatio-Temporal Inception Networks for Traffic Flow Prediction in Smart Cities,
ITS(23), No. 10, October 2022, pp. 19782-19794.
IEEE DOI 2210
Correlation, Mathematical models, Data models, Predictive models, Learning systems, Matrix converters, Support vector machines, inception networks BibRef

Duan, S.J.[Si-Jing], Lyu, F.[Feng], Ren, J.[Ju], Wang, Y.F.[Yi-Feng], Yang, P.[Peng], Zhang, D.S.[De-Sheng], Zhang, Y.X.[Yao-Xue],
Multitype Highway Mobility Analytics for Efficient Learning Model Design: A Case of Station Traffic Prediction,
ITS(23), No. 10, October 2022, pp. 19484-19496.
IEEE DOI 2210
Transportation, Predictive models, Analytical models, Roads, Urban areas, Logistics, Data analysis, Multitype highway mobility, traffic prediction model BibRef

Liu, F.Q.[Fu-Qiang], Wang, J.W.[Jia-Wei], Tian, J.B.[Jing-Bo], Zhuang, D.Y.[Ding-Yi], Miranda-Moreno, L.[Luis], Sun, L.J.[Li-Jun],
A Universal Framework of Spatiotemporal Bias Block for Long-Term Traffic Forecasting,
ITS(23), No. 10, October 2022, pp. 19064-19075.
IEEE DOI 2210
Predictive models, Convolution, Forecasting, Spatiotemporal phenomena, Computational modeling, Logic gates, residual connection BibRef

Wang, J.C.[Jing-Cheng], Zhang, Y.[Yong], Wang, L.[Lixun], Hu, Y.L.[Yong-Li], Piao, X.L.[Xing-Lin], Yin, B.C.[Bao-Cai],
Multitask Hypergraph Convolutional Networks: A Heterogeneous Traffic Prediction Framework,
ITS(23), No. 10, October 2022, pp. 18557-18567.
IEEE DOI 2210
Task analysis, Multitasking, Data models, Predictive models, Neural networks, Public transportation, Deep learning, multi-task learning BibRef

Huo, J.B.[Jin-Biao], Wu, X.H.[Xin-Hua], Lyu, C.[Cheng], Zhang, W.B.[Wen-Bo], Liu, Z.Y.[Zhi-Yuan],
Quantify the Road Link Performance and Capacity Using Deep Learning Models,
ITS(23), No. 10, October 2022, pp. 18581-18591.
IEEE DOI 2210
Business process re-engineering, Roads, Estimation, Neural networks, Transportation, Calibration, Deep learning, macroscopic and microscopic traffic modeling BibRef

Zang, D.[Di], Chen, X.[Xihao], Lei, J.T.[Jun-Tao], Wang, Z.Q.[Zeng-Qiang], Zhang, J.Q.[Jun-Qi], Cheng, J.[Jiujun], Tang, K.[Keshuang],
A multi-channel geometric algebra residual network for traffic data prediction,
IET-ITS(16), No. 11, 2022, pp. 1549-1560.
DOI Link 2210
BibRef

Badu-Marfo, G.[Godwin], Farooq, B.[Bilal], Patterson, Z.[Zachary],
Composite Travel Generative Adversarial Networks for Tabular and Sequential Population Synthesis,
ITS(23), No. 10, October 2022, pp. 17976-17985.
IEEE DOI 2210
Statistics, Sociology, Data models, Generative adversarial networks, Training, Linear programming, agent based modelling BibRef

Zeng, Z.[Zeng], Zhao, W.[Wei], Qian, P.S.[Pei-Sheng], Zhou, Y.J.[Ying-Jie], Zhao, Z.Y.[Zi-Yuan], Chen, C.[Cen], Guan, C.T.[Cun-Tai],
Robust Traffic Prediction From Spatial-Temporal Data Based on Conditional Distribution Learning,
Cyber(52), No. 12, December 2022, pp. 13458-13471.
IEEE DOI 2212
Training, Convolution, Graph neural networks, Probability distribution, Learning systems, Deep learning, traffic prediction BibRef

Zhao, Y.J.[Yi-Ji], Lin, Y.F.[You-Fang], Zhang, Y.K.[Yong-Kai], Wen, H.M.[Hao-Min], Liu, Y.X.[Yun-Xiao], Wu, H.[Hao], Wu, Z.H.[Zhi-Hao], Zhang, S.C.[Shuai-Chao], Wan, H.Y.[Huai-Yu],
Traffic Inflow and Outflow Forecasting by Modeling Intra- and Inter-Relationship Between Flows,
ITS(23), No. 11, November 2022, pp. 20202-20216.
IEEE DOI 2212
Feature extraction, Correlation, Predictive models, Forecasting, Data models, Convolutional neural networks, Training, graph convolutional networks BibRef

Huang, J.[Jing], Luo, K.[Kun], Cao, L.B.[Long-Bing], Wen, Y.Q.[Yuan-Qiao], Zhong, S.Y.[Shu-Yuan],
Learning Multiaspect Traffic Couplings by Multirelational Graph Attention Networks for Traffic Prediction,
ITS(23), No. 11, November 2022, pp. 20681-20695.
IEEE DOI 2212
Couplings, Predictive models, Roads, Data models, Hidden Markov models, Forecasting, Deep learning, traffic signal coupling BibRef

Li, Y.Q.[Yi-Qun], Chai, S.J.[Song-Jian], Wang, G.B.[Gui-Bin], Zhang, X.[Xian], Qiu, J.[Jing],
Quantifying the Uncertainty in Long-Term Traffic Prediction Based on PI-ConvLSTM Network,
ITS(23), No. 11, November 2022, pp. 20429-20441.
IEEE DOI 2212
Predictive models, Deep learning, Logic gates, Uncertainty, Reliability, Probabilistic logic, Feature extraction, traffic flow prediction BibRef

Yan, H.Y.[Hao-Yang], Ma, X.L.[Xiao-Lei], Pu, Z.Y.[Zi-Yuan],
Learning Dynamic and Hierarchical Traffic Spatiotemporal Features With Transformer,
ITS(23), No. 11, November 2022, pp. 22386-22399.
IEEE DOI 2212
Forecasting, Roads, Predictive models, Feature extraction, Deep learning, Spatiotemporal phenomena, Heuristic algorithms, graph-based model BibRef

Liu, Z.Y.[Zhi-Yuan], Lyu, C.[Cheng], Huo, J.B.[Jin-Biao], Wang, S.A.[Shuai-An], Chen, J.[Jun],
Gaussian Process Regression for Transportation System Estimation and Prediction Problems: The Deformation and a Hat Kernel,
ITS(23), No. 11, November 2022, pp. 22331-22342.
IEEE DOI 2212
Kernel, Optimization, Transportation, Gaussian processes, Strain, Estimation, Bayes methods, Hat kernel, hyperparameter optimization, lower bound BibRef

Fang, Y.C.[Yu-Chen], Zhao, F.[Fang], Qin, Y.J.[Yan-Jun], Luo, H.Y.[Hai-Yong], Wang, C.X.[Chen-Xing],
Learning All Dynamics: Traffic Forecasting via Locality-Aware Spatio-Temporal Joint Transformer,
ITS(23), No. 12, December 2022, pp. 23433-23446.
IEEE DOI 2212
Forecasting, Correlation, Convolution, Roads, Transformers, Predictive models, Task analysis, Traffic forecasting, diffusion convolution network BibRef

Liang, M.[Maohan], Liu, R.W.[Ryan Wen], Zhan, Y.[Yang], Li, H.H.[Huan-Huan], Zhu, F.H.[Feng-Hua], Wang, F.Y.[Fei-Yue],
Fine-Grained Vessel Traffic Flow Prediction With a Spatio-Temporal Multigraph Convolutional Network,
ITS(23), No. 12, December 2022, pp. 23694-23707.
IEEE DOI 2212
Feature extraction, Correlation, Artificial intelligence, Trajectory, Data mining, Predictive models, Learning systems, automatic identification system (AIS) BibRef

Li, Z.L.[Zi-Long], Ren, Q.Q.[Qian-Qian], Chen, L.[Long], Li, J.B.[Jin-Bao], Li, X.K.[Xiao-Kun],
Multi-scale convolutional networks for traffic forecasting with spatial-temporal attention,
PRL(164), 2022, pp. 53-59.
Elsevier DOI 2212
Traffic forecasting, Spatial-temporal attention, Convolutional networks BibRef

Li, Z.L.[Zi-Long], Ren, Q.Q.[Qian-Qian], Chen, L.[Long], Sui, X.H.[Xiao-Hong], Li, J.B.[Jin-Bao],
Multi-Hierarchical Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting,
ICPR22(4913-4919)
IEEE DOI 2212
Correlation, Convolution, Transportation, Traffic control, Predictive models, Transformers, Feature extraction, traffic flow forecasting BibRef

Deng, X.D.[Xing-Dong], Zhang, J.[Ji], Liao, S.Y.[Shun-Yi], Zhong, C.J.[Chu-Jie], Gao, F.[Feng], Teng, L.[Li],
Interactive Impacts of Built Environment Factors on Metro Ridership Using GeoDetector: From the Perspective of TOD,
IJGI(11), No. 12, 2022, pp. xx-yy.
DOI Link 2301
BibRef

Nadarajan, J.[Jeba], Sivanraj, R.[Rathi],
Attention-Based Multiscale Spatiotemporal Network for Traffic Forecast with Fusion of External Factors,
IJGI(11), No. 12, 2022, pp. xx-yy.
DOI Link 2301
BibRef

Abdelraouf, A.[Amr], Abdel-Aty, M.[Mohamed], Mahmoud, N.[Nada],
Sequence-to-Sequence Recurrent Graph Convolutional Networks for Traffic Estimation and Prediction Using Connected Probe Vehicle Data,
ITS(24), No. 1, January 2023, pp. 1395-1405.
IEEE DOI 2301
Probes, Estimation, Data models, Sensors, Detectors, Predictive models, Roads, Traffic estimation, traffic prediction, recurrent neural networks BibRef

Diao, C.Y.[Chun-Yan], Zhang, D.[Dafang], Liang, W.[Wei], Li, K.C.[Kuan-Ching], Hong, Y.J.[Yu-Jie], Gaudiot, J.L.[Jean-Luc],
A Novel Spatial-Temporal Multi-Scale Alignment Graph Neural Network Security Model for Vehicles Prediction,
ITS(24), No. 1, January 2023, pp. 904-914.
IEEE DOI 2301
Convolution, Correlation, Vehicle dynamics, Forecasting, Roads, Predictive models, Time series analysis, vehicle prediction BibRef

Luo, D.[Dan], Zhao, D.[Dong], Cao, Z.J.[Zi-Jian], Wu, M.Y.[Ming-Yao], Liu, L.[Liang], Ma, H.D.[Hua-Dong],
M3AN: Multitask Multirange Multisubgraph Attention Network for Condition-Aware Traffic Prediction,
ITS(24), No. 1, January 2023, pp. 218-232.
IEEE DOI 2301
Roads, Data models, Correlation, Predictive models, Adaptation models, Deep learning, deep learning BibRef

Zhang, W.F.[Wei-Feng], Wu, Z.[Zhe], Zhang, X.F.[Xin-Feng], Song, G.[Guoli], Wang, Y.[Yaowei], Chen, J.[Jie],
Robust and Hierarchical Spatial Relation Analysis for Traffic Forecasting,
ITS(24), No. 1, January 2023, pp. 201-217.
IEEE DOI 2301
Feature extraction, Forecasting, Time series analysis, Transportation, Deep learning, temporal convolution network BibRef

Luo, G.Y.[Gui-Yang], Zhang, H.[Hui], Yuan, Q.[Quan], Li, J.L.[Jing-Lin], Wang, F.Y.[Fei-Yue],
ClusterST: Clustering Spatial-Temporal Network for Traffic Forecasting,
ITS(24), No. 1, January 2023, pp. 706-717.
IEEE DOI 2301
Feature extraction, Forecasting, Correlation, Laplace equations, Sensor phenomena and characterization, Predictive models, over-smoothing BibRef

Ji, J.Z.[Jun-Zhong], Yu, F.[Fan], Lei, M.L.[Ming-Long],
Self-Supervised Spatiotemporal Graph Neural Networks With Self-Distillation for Traffic Prediction,
ITS(24), No. 2, February 2023, pp. 1580-1593.
IEEE DOI 2302
Predictive models, Spatiotemporal phenomena, Task analysis, Data models, Feature extraction, Self-supervised learning, self-distillation BibRef

Li, M.X.[Ming-Xi], Tang, Y.H.[Yi-Hong], Ma, W.[Wei],
Few-Sample Traffic Prediction With Graph Networks Using Locale as Relational Inductive Biases,
ITS(24), No. 2, February 2023, pp. 1894-1908.
IEEE DOI 2302
Data models, Predictive models, Urban areas, Task analysis, Roads, Numerical models, Training, Traffic prediction, intelligent transportation systems BibRef

Li, N.[Na], Sheng, H.T.[Hao-Tian], Wang, P.Y.[Ping-Yao], Jia, Y.L.[Yu-Lin], Yang, Z.[Zaili], Jin, Z.H.[Zhi-Hong],
Modeling Categorized Truck Arrivals at Ports: Big Data for Traffic Prediction,
ITS(24), No. 3, March 2023, pp. 2772-2788.
IEEE DOI 2303
Containers, Predictive models, Data models, Seaports, Deep learning, Logic gates, Task analysis, Container terminal, truck arrival, big data BibRef

Jiang, W.W.[Wei-Wei], Luo, J.[Jiayun], He, M.[Miao], Gu, W.X.[Wei-Xi],
Graph Neural Network for Traffic Forecasting: The Research Progress,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Mahajan, V.[Vishal], Cantelmo, G.[Guido], Rothfeld, R.[Raoul], Antoniou, C.[Constantinos],
Predicting network flows from speeds using open data and transfer learning,
IET-ITS(17), No. 4, 2023, pp. 804-824.
DOI Link 2304
deep learning, open data, traffic forecasting, traffic prediction, traffic state estimation, transfer learning BibRef

Lai, Q.F.[Qi-Feng], Tian, J.Y.[Jin-Yu], Wang, W.[Wei], Hu, X.P.[Xi-Ping],
Spatial-Temporal Attention Graph Convolution Network on Edge Cloud for Traffic Flow Prediction,
ITS(24), No. 4, April 2023, pp. 4565-4576.
IEEE DOI 2304
Cloud computing, Data models, Predictive models, Servers, Convolution, Training, Feature extraction, Egde cloud, graph convolution network BibRef

Zeng, J.[Jie], Tang, J.J.[Jin-Jun],
Modeling Dynamic Traffic Flow as Visibility Graphs: A Network-Scale Prediction Framework for Lane-Level Traffic Flow Based on LPR Data,
ITS(24), No. 4, April 2023, pp. 4173-4188.
IEEE DOI 2304
Predictive models, Roads, Correlation, Spatiotemporal phenomena, Data models, Logic gates, Task analysis, license plate recognition data BibRef

Wang, Y.[Yi], Jing, C.F.[Chang-Feng], Huang, W.[Wei], Jin, S.Y.[Shi-Yuan], Lv, X.X.[Xin-Xin],
Adaptive Spatiotemporal InceptionNet for Traffic Flow Forecasting,
ITS(24), No. 4, April 2023, pp. 3882-3907.
IEEE DOI 2304
Spatiotemporal phenomena, Feature extraction, Forecasting, Roads, Predictive models, Data mining, Convolution, graph pooling BibRef

Ma, Q.W.[Qi-Wei], Sun, W.[Wei], Gao, J.[Junbo], Ma, P.W.[Peng-Wei], Shi, M.J.[Meng-Jie],
Spatio-temporal adaptive graph convolutional networks for traffic flow forecasting,
IET-ITS(17), No. 4, 2023, pp. 691-703.
DOI Link 2304
BibRef

Liao, Z.H.[Zhu-Hua], Huang, H.K.[Hao-Kai], Zhao, Y.J.[Yi-Jiang], Liu, Y.Z.[Yi-Zhi], Zhang, G.Q.[Guo-Qiang],
Analysis and Forecast of Traffic Flow between Urban Functional Areas Based on Ride-Hailing Trajectories,
IJGI(12), No. 4, 2023, pp. 144.
DOI Link 2305
BibRef

Liu, M.Z.[Ming-Zhe], Zhu, T.Y.[Tong-Yu], Ye, J.[Junchen], Meng, Q.X.[Qing-Xin], Sun, L.L.[Lei-Lei], Du, B.[Bowen],
Spatio-Temporal AutoEncoder for Traffic Flow Prediction,
ITS(24), No. 5, May 2023, pp. 5516-5526.
IEEE DOI 2305
Convolution, Time series analysis, Feature extraction, Decoding, Data mining, Correlation, History, Traffic flow prediction, hidden state extraction BibRef

Chondrodima, E.[Eva], Pelekis, N.[Nikos], Pikrakis, A.[Aggelos], Theodoridis, Y.[Yannis],
An Efficient LSTM Neural Network-Based Framework for Vessel Location Forecasting,
ITS(24), No. 5, May 2023, pp. 4872-4888.
IEEE DOI 2305
Trajectory, Forecasting, Artificial neural networks, Predictive models, Hidden Markov models, trajectory data augmentation BibRef

Weng, W.C.[Wen-Chao], Fan, J.[Jin], Wu, H.[Huifeng], Hu, Y.J.[Yu-Jie], Tian, H.[Hao], Zhu, F.[Fu], Wu, J.[Jia],
A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting,
PR(142), 2023, pp. 109670.
Elsevier DOI 2307
Traffic forecasting, Dynamic graph generation, Residual decomposition, Segmented learning, Graph convolution network BibRef

Li, H.R.[Hao-Ran], Yuan, Z.Z.[Zhen-Zhou], Chen, S.Y.[Si-Yuan], Zhu, C.[Chuang],
Exploring the effects of measures of performance and calibration strategies on calibrating traffic microsimulation model: A quantitative analysis approach,
IET-ITS(17), No. 6, 2023, pp. 1200-1219.
DOI Link 2307
calibration, performance evaluation, traffic engineering computing, transport modelling and microsimulation BibRef

Sun, H.R.[Hao-Ran], Wei, Y.L.[Yan-Ling], Huang, X.L.[Xue-Liang], Gao, S.[Shan], Song, Y.H.[Yu-Hang],
Global spatio-temporal dynamic capturing network-based traffic flow prediction,
IET-ITS(17), No. 6, 2023, pp. 1220-1228.
DOI Link 2307
complex networks, decision making, management and control, traffic modelling BibRef

Li, Z.X.[Zhen-Xin], Han, Y.[Yong], Xu, Z.Y.[Zhen-Yu], Zhang, Z.H.[Zhi-Hao], Sun, Z.X.[Zhi-Xian], Chen, G.[Ge],
PMGCN: Progressive Multi-Graph Convolutional Network for Traffic Forecasting,
IJGI(12), No. 6, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Fan, A.[Aihua], Chen, X.[Xumei], Yu, L.[Lei], Li, M.[Ming],
Investigating heterogeneity in travel behaviour change when implementing soft transport interventions: A latent class choice model,
IET-ITS(17), No. 6, 2023, pp. 1072-1086.
DOI Link 2307
latent class choice model, soft transport intervention, travel behaviour change, traveller heterogeneity BibRef

Wang, B.[Binwu], Zhang, Y.D.[Yu-Dong], Shi, J.H.[Jia-Hao], Wang, P.K.[Peng-Kun], Wang, X.[Xu], Bai, L.[Lei], Wang, Y.[Yang],
Knowledge Expansion and Consolidation for Continual Traffic Prediction With Expanding Graphs,
ITS(24), No. 7, July 2023, pp. 7190-7201.
IEEE DOI 2307
Spatiotemporal phenomena, Data models, Predictive models, Roads, Knowledge engineering, Task analysis, Correlation, continuous learning BibRef

Huang, R.[Ru], Chen, Z.J.[Zi-Jian], Zhai, G.T.[Guang-Tao], He, J.H.[Jian-Hua], Chu, X.L.[Xiao-Li],
Spatial-temporal correlation graph convolutional networks for traffic forecasting,
IET-ITS(17), No. 7, 2023, pp. 1380-1394.
DOI Link 2307
management and control, neural net architecture, network topology, traffic modeling BibRef

Qi, X.Y.[Xiao-Yu], Mei, G.[Gang], Tu, J.Z.[Jing-Zhi], Xi, N.[Ning], Piccialli, F.[Francesco],
A Deep Learning Approach for Long-Term Traffic Flow Prediction With Multifactor Fusion Using Spatiotemporal Graph Convolutional Network,
ITS(24), No. 8, August 2023, pp. 8687-8700.
IEEE DOI 2308
Spatiotemporal phenomena, Predictive models, Deep learning, Convolution, Data models, Forecasting, Logic gates, deep learning BibRef

Yuan, X.M.[Xiao-Ming], Chen, J.[Jiahui], Yang, J.[Jiayu], Zhang, N.[Ning], Yang, T.T.[Ting-Ting], Han, T.[Tao], Taherkordi, A.[Amir],
FedSTN: Graph Representation Driven Federated Learning for Edge Computing Enabled Urban Traffic Flow Prediction,
ITS(24), No. 8, August 2023, pp. 8738-8748.
IEEE DOI 2308
Computational modeling, Servers, Predictive models, Data models, Collaborative work, Deep learning, Training, smart city BibRef

Chen, Y.[Yan], Shu, T.[Tian], Zhou, X.K.[Xiao-Kang], Zheng, X.[Xuzhe], Kawai, A.[Akira], Fueda, K.[Kaoru], Yan, Z.[Zheng], Liang, W.[Wei], Wang, K.I.K.[Kevin I-Kai],
Graph Attention Network With Spatial-Temporal Clustering for Traffic Flow Forecasting in Intelligent Transportation System,
ITS(24), No. 8, August 2023, pp. 8727-8737.
IEEE DOI 2308
Forecasting, Feature extraction, Convolution, Predictive models, Task analysis, Internet of Things, Data models, intelligent transportation system BibRef

Guo, C.Y.[Can-Yang], Chen, C.H.[Chi-Hua], Hwang, F.J.[Feng-Jang], Chang, C.C.[Ching-Chun], Chang, C.C.[Chin-Chen],
Fast Spatiotemporal Learning Framework for Traffic Flow Forecasting,
ITS(24), No. 8, August 2023, pp. 8606-8616.
IEEE DOI 2308
Spatiotemporal phenomena, Correlation, Convolution, Roads, Intelligent transportation systems, Kernel, Logic gates, traffic flow forecasting BibRef

Guo, C.Y.[Can-Yang], Hwang, F.J.[Feng-Jang], Chen, C.H.[Chi-Hua], Chang, C.C.[Ching-Chun], Chang, C.C.[Chin-Chen],
Dynamic Spatiotemporal Straight-Flow Network for Efficient Learning and Accurate Forecasting in Traffic,
ITS(25), No. 11, November 2024, pp. 18899-18912.
IEEE DOI 2411
Spatiotemporal phenomena, Accuracy, Forecasting, Vehicle dynamics, Correlation, Aerodynamics, Data mining, Training, Predictive models, heterogeneous dependencies BibRef

Huang, Y.J.[Yun-Jie], Song, X.Z.[Xiao-Zhuang], Zhu, Y.S.[Yuan-Shao], Zhang, S.[Shiyao], Yu, J.J.Q.[James J. Q.],
Traffic Prediction With Transfer Learning: A Mutual Information-Based Approach,
ITS(24), No. 8, August 2023, pp. 8236-8252.
IEEE DOI 2308
Urban areas, Transfer learning, Roads, Task analysis, Data models, Forecasting, Predictive models, Traffic prediction, mutual information BibRef

Jin, G.Y.[Guang-Yin], Li, F.[Fuxian], Zhang, J.L.[Jin-Lei], Wang, M.[Mudan], Huang, J.C.[Jin-Cai],
Automated Dilated Spatio-Temporal Synchronous Graph Modeling for Traffic Prediction,
ITS(24), No. 8, August 2023, pp. 8820-8830.
IEEE DOI 2308
Computational modeling, Correlation, Convolution, Predictive models, Adaptation models, Time series analysis, automated machine learning BibRef

Yao, Z.X.[Zhi-Xiu], Xia, S.C.[Shi-Chao], Li, Y.[Yun], Wu, G.F.[Guang-Fu], Zuo, L.L.[Lin-Li],
Transfer Learning with Spatial-Temporal Graph Convolutional Network for Traffic Prediction,
ITS(24), No. 8, August 2023, pp. 8592-8605.
IEEE DOI 2308
Roads, Transfer learning, Convolutional neural networks, Feature extraction, Task analysis, Data models, Convolution, adversarial domain adaptation BibRef

Wang, Q.[Qiang], Jiang, H.[Hao], Qiu, M.[Meikang], Liu, Y.F.[Yi-Feng], Ye, D.S.[Dong-Sheng],
TGAE: Temporal Graph Autoencoder for Travel Forecasting,
ITS(24), No. 8, August 2023, pp. 8529-8541.
IEEE DOI 2308
Forecasting, Task analysis, Transportation, Vehicle dynamics, Predictive models, Peer-to-peer computing, Heuristic algorithms, temporal networks BibRef

Manibardo, E.L.[Eric L.], Laña, I.[Ibai], Villar-Rodriguez, E.[Esther], Ser, J.D.[Javier Del],
A Graph-Based Methodology for the Sensorless Estimation of Road Traffic Profiles,
ITS(24), No. 8, August 2023, pp. 8701-8715.
IEEE DOI 2308
Roads, Data models, Estimation, Behavioral sciences, Predictive models, Urban areas, Feature extraction, traffic data generation BibRef

Li, W.[Wei], Zhan, X.[Xi], Liu, X.[Xin], Zhang, L.[Lei], Pan, Y.[Yu], Pan, Z.S.[Zhi-Song],
SASTGCN: A Self-Adaptive Spatio-Temporal Graph Convolutional Network for Traffic Prediction,
IJGI(12), No. 8, 2023, pp. 346.
DOI Link 2309
BibRef

Chen, J.[Jing], Xu, M.Q.[Meng-Qi], Xu, W.Q.[Wen-Qiang], Li, D.P.[Da-Ping], Peng, W.M.[Wei-Min], Xu, H.T.[Hai-Tao],
A Flow Feedback Traffic Prediction Based on Visual Quantified Features,
ITS(24), No. 9, September 2023, pp. 10067-10075.
IEEE DOI 2310
BibRef

Liu, T.[Tao], Jiang, A.[Aimin], Zhou, J.[Jia], Li, M.[Min], Kwan, H.K.[Hon Keung],
GraphSAGE-Based Dynamic Spatial-Temporal Graph Convolutional Network for Traffic Prediction,
ITS(24), No. 10, October 2023, pp. 11210-11224.
IEEE DOI 2310
BibRef

Gou, Z.[Zhumei], Shen, Y.G.[Yong-Gang], Chen, S.[Shuifu],
Lanczos method for spatio-temporal graph convolutional networks to forecast expressway flow,
IET-ITS(17), No. 10, 2023, pp. 1979-1991.
DOI Link 2310
big data, convolutional neural nets, intelligent transportation systems, management and control, traffic modelling BibRef

Zhang, Q.Y.[Qing-Yong], Zhou, L.F.[Ling-Feng], Su, Y.X.[Yi-Xin], Xia, H.[Huiwen], Xu, B.[Bingrong],
Gated Recurrent Unit Embedded with Dual Spatial Convolution for Long-Term Traffic Flow Prediction,
IJGI(12), No. 9, 2023, pp. 366.
DOI Link 2310
BibRef

Xue, R.[Rui], Zhao, S.J.[Sheng-Jie], Han, F.X.[Feng-Xia],
An Embedding-Driven Multi-Hop Spatio-Temporal Attention Network for Traffic Prediction,
ITS(24), No. 11, November 2023, pp. 13192-13207.
IEEE DOI 2311
BibRef

Wang, L.H.[Li-Hua], Zhang, F.Q.[Feng-Qi], Cui, Y.H.[Ya-Hui], Coskun, S.[Serdar], Tang, X.L.[Xiao-Lin], Yang, Y.[Yalian], Hu, X.S.[Xiao-Song],
Stochastic Velocity Prediction for Connected Vehicles Considering V2V Communication Interruption,
ITS(24), No. 11, November 2023, pp. 11654-11667.
IEEE DOI 2311
BibRef

Djenouri, Y.[Youcef], Belhadi, A.[Asma], Djenouri, D.[Djamel], Srivastava, G.[Gautam], Lin, J.C.W.[Jerry Chun-Wei],
A Secure Intelligent System for Internet of Vehicles: Case Study on Traffic Forecasting,
ITS(24), No. 11, November 2023, pp. 13218-13227.
IEEE DOI 2311
BibRef

Chang, S.Y.[Shih Yu], Wu, H.C.[Hsiao-Chun], Kao, Y.C.[Yi-Chih],
Tensor Extended Kalman Filter and its Application to Traffic Prediction,
ITS(24), No. 12, December 2023, pp. 13813-13829.
IEEE DOI 2312
BibRef

Wang, C.[Chen], Zuo, K.[Kaizhong], Zhang, S.[Shaokun], Lei, H.[Hanwen], Hu, P.[Peng], Shen, Z.Y.[Zhang-Yi], Wang, R.[Rui], Zhao, P.[Peize],
PFNet: Large-Scale Traffic Forecasting With Progressive Spatio-Temporal Fusion,
ITS(24), No. 12, December 2023, pp. 14580-14597.
IEEE DOI 2312
BibRef

Zhao, J.[Jie], Chen, C.[Chao], Liao, C.W.[Cheng-Wu], Huang, H.Y.[Hong-Yu], Ma, J.[Jie], Pu, H.Y.[Hua-Yan], Luo, J.[Jun], Zhu, T.[Tao], Wang, S.L.[Shi-Long],
2F-TP: Learning Flexible Spatiotemporal Dependency for Flexible Traffic Prediction,
ITS(24), No. 12, December 2023, pp. 15379-15391.
IEEE DOI 2312
BibRef

Qi, Y.X.[Yu-Xin], Wu, J.[Jun], Bashir, A.K.[Ali Kashif], Lin, X.[Xi], Yang, W.[Wu], Alshehri, M.D.[Mohammad Dahman],
Privacy-Preserving Cross-Area Traffic Forecasting in ITS: A Transferable Spatial-Temporal Graph Neural Network Approach,
ITS(24), No. 12, December 2023, pp. 15499-15512.
IEEE DOI 2312
BibRef

Ali, F.[Faryal], Khan, Z.H.[Zawar Hussain], Khattak, K.S.[Khurram Shehzad], Gulliver, T.A.[Thomas Aaron],
The effect of visibility on road traffic during foggy weather conditions,
IET-ITS(18), No. 1, 2024, pp. 47-57.
DOI Link 2401
intelligent transportation systems, management and control, road safety, road traffic, simulation, traffic modelling BibRef

Ye, W.[Wei], Kuang, H.X.[Hao-Xuan], Li, J.[Jun], Lai, X.J.[Xin-Jun], Qu, H.[Haohao],
A parking occupancy prediction method incorporating time series decomposition and temporal pattern attention mechanism,
IET-ITS(18), No. 1, 2024, pp. 58-71.
DOI Link 2401
intelligent transportation systems, learning (artificial intelligence), time series BibRef

Wang, Q.[Qing], Liu, W.P.[Wei-Ping], Wang, X.M.[Xiu-Mei], Chen, X.H.[Xing-Hong], Chen, G.N.[Guan-Nan], Wu, Q.X.[Qing-Xiang],
GMHANN: A Novel Traffic Flow Prediction Method for Transportation Management Based on Spatial-Temporal Graph Modeling,
ITS(25), No. 1, January 2024, pp. 386-401.
IEEE DOI 2402
Predictive models, Roads, Data models, Transportation, Feature extraction, Complexity theory, Correlation, AGRU BibRef

Hu, H.X.[He-Xuan], Hu, Q.[Qiang], Tan, G.P.[Guo-Ping], Zhang, Y.[Ye], Lin, Z.Z.[Zhen-Zhou],
A Multi-Layer Model Based on Transformer and Deep Learning for Traffic Flow Prediction,
ITS(25), No. 1, January 2024, pp. 443-451.
IEEE DOI 2402
Predictive models, Data models, Computational modeling, Feature extraction, Transformers, Mathematical models, multi-layer model BibRef

Du, W.B.[Wen-Bo], Chen, S.W.[Shen-Wen], Li, Z.S.[Zhi-Shuai], Cao, X.B.[Xian-Bin], Lv, Y.S.[Yi-Sheng],
A Spatial-Temporal Approach for Multi-Airport Traffic Flow Prediction Through Causality Graphs,
ITS(25), No. 1, January 2024, pp. 532-544.
IEEE DOI 2402
Airports, Atmospheric modeling, Feature extraction, Predictive models, Adaptation models, Data mining, spatiotemporal analysis BibRef

Nie, L.[Laisen], Wang, X.J.[Xiao-Jie], Zhao, Q.L.[Qing-Lin], Shang, Z.G.[Zhi-Gang], Feng, L.[Li], Li, G.J.[Guo-Jun],
Digital Twin for Transportation Big Data: A Reinforcement Learning-Based Network Traffic Prediction Approach,
ITS(25), No. 1, January 2024, pp. 896-906.
IEEE DOI 2402
COVID-19, Predictive models, Neural networks, Feature extraction, Transportation, Generative adversarial networks, Digital twins, generative adversarial networks BibRef

Pu, B.[Bin], Liu, J.S.[Jian-Song], Kang, Y.[Yan], Chen, J.G.[Jian-Guo], Yu, P.S.[Philip S.],
MVSTT: A Multiview Spatial-Temporal Transformer Network for Traffic-Flow Forecasting,
Cyber(54), No. 3, March 2024, pp. 1582-1595.
IEEE DOI Code:
WWW Link. 2402
Forecasting, Correlation, Convolution, Transformers, Roads, Predictive models, Vehicle dynamics, Deep neural network, traffic-flow forecasting BibRef

Yao, S.L.[Shui-Lin], Zhang, H.Z.[Hui-Zhen], Wang, C.X.[Chen-Xi], Zeng, D.[Dan], Ye, M.[Ming],
GSTGAT: Gated spatiotemporal graph attention network for traffic demand forecasting,
IET-ITS(18), No. 2, 2024, pp. 258-268.
DOI Link 2402
demand forecasting, traffic, traffic and demand managing BibRef

Li, X.Y.[Xiao-Yu], Gong, Y.S.[Yong-Shun], Liu, W.[Wei], Yin, Y.L.[Yi-Long], Zheng, Y.[Yu], Nie, L.Q.[Li-Qiang],
Dual-track spatio-temporal learning for urban flow prediction with adaptive normalization,
AI(328), 2024, pp. 104065.
Elsevier DOI 2403
Urban flow prediction, Spatio-temporal learning, Spatio-temporal normalization, Contrastive learning, Regional and global correlations BibRef

Qi, X.D.[Xu-Dong], Yao, J.F.[Jun-Feng], Wang, P.[Ping], Shi, T.T.[Tong-Tong], Zhang, Y.J.[Ya-Jie], Zhao, X.M.[Xiang-Mo],
Combining Weather Factors to Predict Traffic Flow: A Spatial-Temporal Fusion Graph Convolutional Network-Based Deep Learning Approach,
IET-ITS(18), No. 3, 2024, pp. 528-539.
DOI Link 2403
management and control, traffic and demand managing, traffic information systems, traffic modelling BibRef

Lu, S.[Shuai], Chen, H.B.[Hai-Bo], Teng, Y.L.[Yi-Long],
Multi-Scale Non-Local Spatio-Temporal Information Fusion Networks for Multi-Step Traffic Flow Forecasting,
IJGI(13), No. 3, 2024, pp. 71.
DOI Link 2404
BibRef

Liu, L.J.[Li-Juan], Wang, F.Z.[Feng-Zhi], Liu, H.[Hang], Zhu, S.Z.[Shun-Zhi], Wang, Y.[Yan],
HD-Net: A hybrid dynamic spatio-temporal network for traffic flow prediction,
IET-ITS(18), No. 4, 2024, pp. 672-690.
DOI Link 2404
management and control, traffic modelling, transport modelling and microsimulation BibRef

Shan, X.F.[Xiao-Feng], Yu, W.J.[Wei-Jie], Li, Z.B.[Zhi-Bin], Wang, C.[Chishe], Ren, Y.F.[Yi-Feng], Zhang, J.J.[Jia-Jie],
Vehicle Trajectory-Based Traffic Volume Prediction on Urban Roads With Fast-Communication License Plate Recognition Data,
ITS(25), No. 3, March 2024, pp. 2768-2778.
IEEE DOI 2405
Trajectory, Predictive models, Solid modeling, Roads, Data models, Recurrent neural networks, Real-time systems, Trajectory BibRef

Kong, J.L.[Jian-Lei], Fan, X.M.[Xiao-Meng], Jin, X.[Xuebo], Lin, S.[Sen], Zuo, M.[Min],
A Variational Bayesian Inference-Based En-Decoder Framework for Traffic Flow Prediction,
ITS(25), No. 3, March 2024, pp. 2966-2975.
IEEE DOI 2405
Bayes methods, Neural networks, Predictive models, Uncertainty, Deep learning, Computational modeling, Time series analysis, encoder-decoder BibRef

Liu, H.Z.[Hua-Zhong], Zhang, Y.F.[Yun-Fan], Ding, J.H.[Ji-Hong], Zhang, H.[Hanning], Yang, L.T.[Laurence T.], Zhou, X.K.[Xiao-Kang],
Tensor-Train-Based Incremental High Order Dominant Z-Eigen Decomposition for Multi-Modal Intelligent Transportation Prediction,
ITS(25), No. 3, March 2024, pp. 2534-2544.
IEEE DOI 2405
Tensors, Transportation, Markov processes, Mathematical models, Computational modeling, Predictive models, Data models, multi-modal ITS prediction BibRef

Zhao, J.H.[Jun-Hui], Xiong, X.C.[Xin-Cheng], Zhang, Q.[Qingmiao], Wang, D.M.[Dong-Ming],
Extended Multi-Component Gated Recurrent Graph Convolutional Network for Traffic Flow Prediction,
ITS(25), No. 5, May 2024, pp. 4634-4644.
IEEE DOI 2405
Roads, Convolutional neural networks, Sensors, Predictive models, Feature extraction, Correlation, Data models, graph convolutional network BibRef

Song, X.X.[Xiao-Xiang], Guo, Y.[Yan], Li, N.[Ning], Wang, H.[Hai], Yu, W.[Weibo],
Online Matrix Factorization-Based Traffic Flow Prediction Empowered by Edge Computing for the CAVs,
ITS(25), No. 5, May 2024, pp. 4049-4065.
IEEE DOI 2405
Predictive models, Edge computing, Real-time systems, Computational modeling, Servers, Autonomous vehicles, online prediction BibRef

Wu, Y.[Ying], Ye, Y.C.[Yong-Chao], Zeb, A.[Adnan], Yu, J.J.Q.[James Jian-Qiao], Wang, Z.[Zheng],
Adaptive Modeling of Uncertainties for Traffic Forecasting,
ITS(25), No. 5, May 2024, pp. 4427-4442.
IEEE DOI 2405
Predictive models, Uncertainty, Forecasting, Planning, Adaptation models, Data models, Computational modeling, quantile model BibRef

Yang, H.Y.[Han-Yi], Yu, W.[Wanxin], Zhang, G.H.[Guo-Hui], Du, L.[Lili],
Network-Wide Traffic Flow Dynamics Prediction Leveraging Macroscopic Traffic Flow Model and Deep Neural Networks,
ITS(25), No. 5, May 2024, pp. 4443-4457.
IEEE DOI 2405
Predictive models, Roads, Hidden Markov models, Data models, Boundary conditions, Traffic control, Deep learning, graph theory BibRef

Lv, Z.Q.[Zhi-Qiang], Cheng, Z.[Zesheng], Li, J.B.[Jian-Bo], Xu, Z.H.[Zhi-Hao], Yang, Z.[Zheng],
TreeCN: Time Series Prediction With the Tree Convolutional Network for Traffic Prediction,
ITS(25), No. 5, May 2024, pp. 3751-3766.
IEEE DOI 2405
Correlation, Transportation, Time series analysis, Roads, Convolutional neural networks, Task analysis, Predictive models, hierarchical feature BibRef

Ouyang, J.H.[Jin-Hui], Yu, M.X.[Ming-Xia], Yu, W.[Weiren], Qin, Z.[Zheng], Regan, A.C.[Amelia C.], Wu, D.[Di],
TPGraph: A Spatial-Temporal Graph Learning Framework for Accurate Traffic Prediction on Arterial Roads,
ITS(25), No. 5, May 2024, pp. 3911-3926.
IEEE DOI 2405
Roads, Feature extraction, Data mining, Convolutional neural networks, Convolution, Transformers, graph neural networks BibRef

Bilotta, S.[Stefano], Bonsignori, V.[Valerio], Nesi, P.[Paolo],
High Precision Traffic Flow Reconstruction via Hybrid Method,
ITS(25), No. 5, May 2024, pp. 4066-4076.
IEEE DOI 2405
Roads, Sensors, Data models, Computational modeling, Predictive models, Junctions, Pollution measurement, machine learning PDE solution BibRef

Feng, J.[Jian], Du, C.[Cailing], Mu, Q.[Qi],
Traffic Flow Prediction Based on Federated Learning and Spatio-Temporal Graph Neural Networks,
IJGI(13), No. 6, 2024, pp. 210.
DOI Link 2406
BibRef

He, Y.L.[Ying-Long], Mattas, K.[Konstantinos], Makridis, M.A.[Michail A.], Komnos, D.[Dimitrios], Marin, A.L.[Andres L.], Fontaras, G.[Georgios], Ciuffo, B.[Biagio],
Introducing Hybrid Vehicle Dynamics in Microscopic Traffic Simulation,
ITS(25), No. 7, July 2024, pp. 7977-7986.
IEEE DOI 2407
Vehicle dynamics, Microscopy, Mathematical models, Ice, Computational modeling, Hybrid electric vehicles, Vehicles, charge sustaining (CS) BibRef

Chang, M.M.[Meng-Meng], Ding, Z.M.[Zhi-Ming], Zhao, Z.[Zilin], Cai, Z.[Zhi],
Heterogeneous Modular Traffic Prediction Based on Multilayer Graph Convolutional Network,
ITS(25), No. 7, July 2024, pp. 7805-7817.
IEEE DOI 2407
Spatiotemporal phenomena, Correlation, Nonhomogeneous media, Convolution, Traffic control, Feature extraction, heterogeneous links BibRef

Liu, A.[Aoyu], Zhang, Y.[Yaying],
Spatial-Temporal Dynamic Graph Convolutional Network With Interactive Learning for Traffic Forecasting,
ITS(25), No. 7, July 2024, pp. 7645-7660.
IEEE DOI Code:
WWW Link. 2407
Correlation, Forecasting, Roads, Convolutional neural networks, Traffic control, Adaptation models, traffic forecasting BibRef

Shin, Y.[Yuyol], Yoon, Y.[Yoonjin],
PGCN: Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting,
ITS(25), No. 7, July 2024, pp. 7633-7644.
IEEE DOI 2407
Forecasting, Convolution, Adaptation models, Feature extraction, Correlation, Transportation, Predictive models, multivariate time-series BibRef

Sun, J.[Jie], Kim, J.[Jiwon],
Toward Data-Driven Simulation of Network-Wide Traffic: A Multi-Agent Imitation Learning Approach Using Urban Vehicle Trajectory Data,
ITS(25), No. 7, July 2024, pp. 6645-6657.
IEEE DOI 2407
Trajectory, Predictive models, Traffic control, Load modeling, Data models, Roads, Loading, Traffic simulation, MAGAIL BibRef

Zou, G.J.[Guo-Jian], Lai, Z.L.[Zi-Liang], Wang, T.[Ting], Liu, Z.S.[Zong-Shi], Li, Y.[Ye],
MT-STNet: A Novel Multi-Task Spatiotemporal Network for Highway Traffic Flow Prediction,
ITS(25), No. 7, July 2024, pp. 8221-8236.
IEEE DOI 2407
Spatiotemporal phenomena, Correlation, Predictive models, Feature extraction, Hidden Markov models, Multitasking, generative inference system BibRef

Yu, Q.[Qian], Ma, L.[Liang], Lai, P.[Pei], Guo, J.[Jin],
Dynamic spatial-temporal network for traffic forecasting based on joint latent space representation,
IET-ITS(18), No. 8, 2024, pp. 1369-1384.
DOI Link 2408
intelligent transportation systems, traffic modeling, management and control, neural nets BibRef

Wei, S.Q.[Shu-Qing], Feng, S.Y.[Si-Yuan], Yang, H.[Hai],
Multi-View Spatial-Temporal Graph Convolutional Network for Traffic Prediction,
ITS(25), No. 8, August 2024, pp. 9572-9586.
IEEE DOI 2408
Roads, Correlation, Public transportation, Convolutional neural networks, Predictive models, Data models, traffic prediction BibRef

Cao, S.Q.[Shu-Qin], Wu, L.[Libing], Zhang, R.[Rui], Wu, D.[Dan], Cui, J.[Jianqun], Chang, Y.[Yanan],
A Spatiotemporal Multiscale Graph Convolutional Network for Traffic Flow Prediction,
ITS(25), No. 8, August 2024, pp. 8705-8718.
IEEE DOI 2408
Correlation, Roads, Spatiotemporal phenomena, Feature extraction, Convolutional neural networks, Predictive models, cross-scale fusion BibRef

Chauhan, N.S.[Nisha Singh], Kumar, N.[Neetesh], Eskandarian, A.[Azim],
A Novel Confined Attention Mechanism Driven Bi-GRU Model for Traffic Flow Prediction,
ITS(25), No. 8, August 2024, pp. 9181-9191.
IEEE DOI 2408
Predictive models, Long short term memory, Feature extraction, Data models, Roads, Forecasting, Data mining, external features BibRef

Mallick, T.[Tanwi], Macfarlane, J.[Jane], Balaprakash, P.[Prasanna],
Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks,
ITS(25), No. 8, August 2024, pp. 9141-9152.
IEEE DOI Code:
WWW Link. 2408
BibRef

Wang, Q.Y.[Qing-Yi], Wang, S.[Shenhao], Zhuang, D.[Dingyi], Koutsopoulos, H.[Haris], Zhao, J.H.[Jin-Hua],
Uncertainty Quantification of Spatiotemporal Travel Demand With Probabilistic Graph Neural Networks,
ITS(25), No. 8, August 2024, pp. 8770-8781.
IEEE DOI 2408
Uncertainty, Probabilistic logic, Deep learning, Spatiotemporal phenomena, Data models, Predictive models, travel demand prediction BibRef

Kumar, K.N.[K. Naveen], Roy, D.[Debaditya], Suman, T.A.[Thakur Ashutosh], Vishnu, C.[Chalavadi], Mohan, C.K.[C. Krishna],
TSANet: Forecasting traffic congestion patterns from aerial videos using graphs and transformers,
PR(155), 2024, pp. 110721.
Elsevier DOI 2408
Spatio-temporal graphs, Transformers, Sequence modelling, Sequence estimation BibRef

Meese, C.[Collin], Chen, H.[Hang], Li, W.[Wanxin], Lee, D.[Danielle], Guo, H.[Hao], Shen, C.C.[Chien-Chung], Nejad, M.[Mark],
Adaptive Traffic Prediction at the ITS Edge With Online Models and Blockchain-Based Federated Learning,
ITS(25), No. 9, September 2024, pp. 10725-10740.
IEEE DOI 2409
Predictive models, Data models, Blockchains, Training, Computational modeling, Streams, Sensors, Blockchain, deep learning, traffic prediction BibRef

Laña, I.[Ibai], Olabarrieta, I.[Ignacio], Ser, J.D.[Javier Del],
Measuring the Confidence of Single-Point Traffic Forecasting Models: Techniques, Experimental Comparison, and Guidelines Toward Their Actionability,
ITS(25), No. 9, September 2024, pp. 11180-11199.
IEEE DOI 2409
Uncertainty, Predictive models, Forecasting, Estimation, Measurement uncertainty, Data models, Machine learning, traffic forecasting BibRef

Schrader, M.[Maxwell], Bittle, J.[Joshua],
A Global Sensitivity Analysis of Traffic Microsimulation Input Parameters on Performance Metrics,
ITS(25), No. 9, September 2024, pp. 11739-11752.
IEEE DOI 2409
Uncertainty, Calibration, Traffic control, Vehicles, Sensitivity analysis, Optimization, Aggregates, Sobal sensitivity analysis BibRef

Liu, Q.X.[Qing-Xiang], Sun, S.[Sheng], Liu, M.[Min], Wang, Y.W.[Yu-Wei], Gao, B.[Bo],
Online Spatio-Temporal Correlation-Based Federated Learning for Traffic Flow Forecasting,
ITS(25), No. 10, October 2024, pp. 13027-13039.
IEEE DOI 2410
Predictive models, Forecasting, Servers, Correlation, Data models, Federated learning, Adaptation models, Federated learning, traffic flow forecasting BibRef

Liu, Q.X.[Qing-Xiang], Sun, S.[Sheng], Liang, Y.X.[Yu-Xuan], Xu, X.L.[Xiao-Long], Liu, M.[Min], Bilal, M.[Muhammad], Wang, Y.W.[Yu-Wei], Li, X.[Xujing], Zheng, Y.[Yu],
REFOL: Resource-Efficient Federated Online Learning for Traffic Flow Forecasting,
ITS(26), No. 2, February 2025, pp. 2777-2792.
IEEE DOI 2502
Predictive models, Concept drift, Correlation, Forecasting, Computational modeling, Data models, Optimization, graph convolution BibRef

Gan, R.[Rui], An, B.[Bocheng], Li, L.H.[Lin-Heng], Qu, X.[Xu], Ran, B.[Bin],
A Freeway Traffic Flow Prediction Model Based on a Generalized Dynamic Spatio-Temporal Graph Convolutional Network,
ITS(25), No. 10, October 2024, pp. 13682-13693.
IEEE DOI 2410
Predictive models, Data models, Roads, Feature extraction, Long short term memory, Convolution, Detectors, Traffic prediction, traffic big data BibRef

Zhang, X.J.[Xiao-Jian], Ke, Q.[Qian], Zhao, X.[Xilei],
Travel Demand Forecasting: A Fair AI Approach,
ITS(25), No. 10, October 2024, pp. 14611-14627.
IEEE DOI 2410
Predictive models, Demand forecasting, Transportation, Sociology, Correlation, Decision making, Deep learning, AI, fairness, forecasting, travel demand BibRef

Du, K.[Kejun], Wang, S.[Shuling], Lo, H.K.[Hong K.],
Traffic Parameters Estimation With Partial Vehicle Trajectories by the Iterative Partial Backpropagation Maximum Likelihood Estimation (IPB-MLE) Framework,
ITS(25), No. 10, October 2024, pp. 14855-14865.
IEEE DOI 2410
Trajectory, Maximum likelihood estimation, Convergence, Backpropagation, Robustness, Real-time systems, Probes, maximum likelihood estimation (MLE) BibRef

Zhang, Y.D.[Yu-Dong], Wang, P.[Pengkun], Wang, B.[Binwu], Wang, X.[Xu], Zhao, Z.[Zhe], Zhou, Z.Y.[Zheng-Yang], Bai, L.[Lei], Wang, Y.[Yang],
Adaptive and Interactive Multi-Level Spatio-Temporal Network for Traffic Forecasting,
ITS(25), No. 10, October 2024, pp. 14070-14086.
IEEE DOI 2410
Forecasting, Roads, Correlation, Urban areas, Traffic control, Layout, Data models, Spatio-temporal data mining, traffic forecasting, urban computing BibRef

Zhao, J.L.[Jian-Li], Zhuo, F.T.[Fu-Tong], Sun, Q.X.[Qiu-Xia], Li, Q.[Qing], Hua, Y.[Yiran], Zhao, J.[Jianye],
DSFormer-LRTC: Dynamic Spatial Transformer for Traffic Forecasting With Low-Rank Tensor Compression,
ITS(25), No. 11, November 2024, pp. 16323-16335.
IEEE DOI 2411
Tensors, Transformers, Predictive models, Computational modeling, Forecasting, Correlation, Matrix decomposition, tensor compression BibRef

Zheng, X.[Xiao], Bagloee, S.A.[Saeed Asadi], Sarvi, M.[Majid],
TRECK: Long-Term Traffic Forecasting With Contrastive Representation Learning,
ITS(25), No. 11, November 2024, pp. 16964-16977.
IEEE DOI 2411
Forecasting, Predictive models, Representation learning, Contrastive learning, Data models, Task analysis, Casting, prediction interval BibRef

Zhu, W.G.[Wei-Guo], Zhang, X.Y.[Xing-Yu], Liu, C.[Caiyuan], Sun, Y.Q.[Yong-Qi],
D³STN: Dynamic Delay Differential Equation Spatiotemporal Network for Traffic Flow Forecasting,
ITS(25), No. 11, November 2024, pp. 18093-18106.
IEEE DOI 2411
Delays, Forecasting, Mathematical models, Correlation, Spatiotemporal phenomena, Predictive models, Convolution, traffic forecasting BibRef

Zhang, C.[Chengyang], Zhang, Y.[Yong], Shao, Q.[Qitan], Feng, J.T.[Jiang-Tao], Li, B.[Bo], Lv, Y.S.[Yi-Sheng], Piao, X.[Xinglin], Yin, B.C.[Bao-Cai],
BjTT: A Large-Scale Multimodal Dataset for Traffic Prediction,
ITS(25), No. 11, November 2024, pp. 18992-19003.
IEEE DOI Code:
WWW Link. 2411
Roads, Social networking (online), Transportation, Data collection, Task analysis, Blogs, Meteorology, Traffic prediction, large-scale, new dataset BibRef

Li, J.Y.[Jun-Yi], Liao, C.L.[Chen-Lei], Hu, S.[Simon], Chen, X.[Xiqun], Lee, D.H.[Der-Horng],
Physics-Guided Multi-Source Transfer Learning for Network-Scale Traffic Flow Prediction,
ITS(25), No. 11, November 2024, pp. 17533-17546.
IEEE DOI 2411
Transfer learning, Adaptation models, Telecommunication traffic, Task analysis, Predictive models, Feature extraction, Data models, physics-guided machine learning BibRef

Wu, Y.L.[Yi-Ling], Zhao, Y.P.[Ying-Ping], Zhang, X.F.[Xin-Feng], Wang, Y.[Yaowei],
Spatial-Temporal Correlation Learning for Traffic Demand Prediction,
ITS(25), No. 11, November 2024, pp. 15745-15758.
IEEE DOI 2411
Correlation, Predictive models, Public transportation, Automobiles, Attention mechanisms, Accuracy, Transformers, spatial-temporal mining BibRef

Zhang, J.F.[Jun-Feng], Xie, C.[Cheng], Cai, H.M.[Hong-Ming], Shen, W.M.[Wei-Ming], Yang, R.[Rui],
Knowledge Distillation-Based Spatio-Temporal MLP Model for Real-Time Traffic Flow Prediction,
ITS(25), No. 11, November 2024, pp. 18122-18135.
IEEE DOI Code:
WWW Link. 2411
Computational modeling, Spatiotemporal phenomena, Predictive models, Accuracy, Real-time systems, Data models, real-time traffic flow prediction BibRef

Sattarzadeh, A.R.[Ali Reza], Pathirana, P.N.[Pubudu N.], Kutadinata, R.[Ronny], Huynh, V.T.[Van Thanh],
Extracting long-term spatiotemporal characteristics of traffic flow using attention-based convolutional transformer,
IET-ITS(18), No. 10, 2024, pp. 1797-1814.
DOI Link 2411
convolutional neural nets, data mining, feature extraction, intelligent transportation systems, time series BibRef

Wang, Y.Q.[Yu-Qing], Zhang, J.W.[Jun-Wei], Ma, Z.[Zhuo], Lu, N.[Ning], Li, T.[Teng], Ma, J.F.[Jian-Feng],
Location-Aware and Privacy-Preserving Data Cleaning for Intelligent Transportation,
ITS(25), No. 12, December 2024, pp. 20405-20418.
IEEE DOI 2412
Cleaning, Data privacy, Accuracy, Reflective binary codes, Privacy, Predictive models, Forecasting, Data cleaning, location-aware, traffic forecasting BibRef

Lim, J.[Junwoo], Lee, J.[Juyeob], An, C.[Chaehee], Park, E.[Eunil],
Enhancing real-time traffic volume prediction: A two-step approach of object detection and time series modelling,
IET-ITS(18), No. 12, 2024, pp. 2744-2758.
DOI Link 2501
artificial intelligence, object detection, real-time systems, road traffic, time series, traffic management and control BibRef

Dou, Z.[Zeping], Guo, D.[Danhuai],
DPSTCN: Dynamic Pattern-Aware Spatio-Temporal Convolutional Networks for Traffic Flow Forecasting,
IJGI(14), No. 1, 2025, pp. 10.
DOI Link 2501
BibRef

Zhang, D.K.[Ding-Kai], Wang, P.F.[Peng-Fei], Ding, L.[Lu], Wang, X.L.[Xiao-Ling], He, J.F.[Ji-Feng],
Spatio-Temporal Contrastive Learning-Based Adaptive Graph Augmentation for Traffic Flow Prediction,
ITS(26), No. 1, January 2025, pp. 1304-1318.
IEEE DOI 2501
Adaptation models, Data models, Correlation, Predictive models, Roads, Computational modeling, Accuracy, Traffic control, graph structure learning BibRef

Lin, M.W.[Ming-Wei], Liu, J.Q.[Jia-Qi], Chen, H.[Hong], Xu, X.[Xiuqin], Luo, X.[Xin], Xu, Z.[Zeshui],
A 3D Convolution-Incorporated Dimension Preserved Decomposition Model for Traffic Data Prediction,
ITS(26), No. 1, January 2025, pp. 673-690.
IEEE DOI 2501
Data models, Predictive models, Feature extraction, Roads, Solid modeling, Data mining, Accuracy, Complexity theory, Tensors, 3D convolution BibRef

Nie, T.[Tong], Qin, G.[Guoyang], Sun, L.J.[Li-Jun], Ma, W.[Wei], Mei, Y.[Yu], Sun, J.[Jian],
Contextualizing MLP-Mixers Spatiotemporally for Urban Traffic Data Forecast at Scale,
ITS(26), No. 1, January 2025, pp. 1241-1256.
IEEE DOI 2501
Spatiotemporal phenomena, Forecasting, Computational modeling, Sensors, Predictive models, Scalability, deployed traffic applications BibRef

Yingran, Z.[Zheng], Chao, L.[Luo], Rui, S.[Shao],
Enhancing Traffic Flow Forecasting With Delay Propagation: Adaptive Graph Convolution Networks for Spatio-Temporal Data,
ITS(26), No. 1, January 2025, pp. 650-660.
IEEE DOI 2501
Delays, Convolution, Roads, Forecasting, Feature extraction, Correlation, Adaptation models, Predictive models, Logic gates, traffic flow delay propagation BibRef

Monteil, J.[Julien], Dekusar, A.[Anton], Gambella, C.[Claudio], Lassoued, Y.[Yassine], Mevissen, M.[Martin],
On Model Selection for Scalable Time Series Forecasting in Transport Networks,
ITS(23), No. 7, July 2022, pp. 6699-6708.
IEEE DOI 2207
Predictive models, Time series analysis, Deep learning, Forecasting, Data models, Correlation, Roads, Time series, autoregressive models BibRef

Naing, H.[Htet], Cai, W.[Wentong], Yu, J.Q.[Jin-Qiang], Zhong, J.H.[Jing-Hui], Yu, L.[Liang],
Fine-Grained Trajectory Reconstruction by Microscopic Traffic Simulation With Dynamic Data-Driven Evolutionary Optimization,
ITS(26), No. 2, February 2025, pp. 1930-1950.
IEEE DOI 2502
Trajectory, Microscopy, Image reconstruction, Optimization, Accuracy, Vehicle dynamics, Traffic control, Data models, surrogate-assisted evolutionary optimization BibRef

Ouyang, N.[Nan], Ao, L.[Lei], Cai, Q.[Qing], Wan, W.K.[Wen-Kang], Ren, X.J.[Xiao-Jiang], He, X.[Xin], Sheng, K.[Kai],
Graph Transformer-Based Dynamic Edge Interaction Encoding for Traffic Prediction,
ITS(26), No. 3, March 2025, pp. 4066-4079.
IEEE DOI Code:
WWW Link. 2503
Transformers, Feature extraction, Encoding, Predictive models, Accuracy, Roads, Time series analysis, Data models, Data mining, spatio-temporal interactive encoding BibRef

Wu, X.[Xunjin], Zhan, J.M.[Jian-Ming], Ding, W.P.[Wei-Ping], Pedrycz, W.[Witold],
GRNN Model With Feedback Mechanism Incorporating k-Nearest Neighbor and Modified Gray Wolf Optimization Algorithm in Intelligent Transportation,
ITS(26), No. 3, March 2025, pp. 3855-3872.
IEEE DOI 2503
Nearest neighbor methods, Predictive models, Heuristic algorithms, Prediction algorithms, Optimization, generalized regression neural network with feedback mechanism BibRef

Yuan, Q.[Qing], Wang, J.[Junbo], Han, Y.[Yu], Liu, Z.[Zhi], Liu, W.Q.[Wan-Quan],
DAGCAN: Decoupled Adaptive Graph Convolution Attention Network for Traffic Forecasting,
ITS(26), No. 3, March 2025, pp. 3513-3526.
IEEE DOI 2503
Predictive models, Data models, Adaptation models, Correlation, Optimization, Forecasting, Feature extraction, Sensors, attention mechanism BibRef

Chen, L.Q.[Ling-Qiang], Zhao, Q.L.[Qing-Lin], Li, G.H.[Guang-Hui], Zhou, M.C.[Meng-Chu], Dai, C.L.[Cheng-Long], Feng, Y.M.[Yi-Ming], Liu, X.W.[Xiao-Wei], Li, J.J.[Jin-Jiang],
A Sparse Cross Attention-Based Graph Convolution Network With Auxiliary Information Awareness for Traffic Flow Prediction,
ITS(26), No. 3, March 2025, pp. 3210-3222.
IEEE DOI 2503
Computational modeling, Data models, Meteorology, Convolution, Computational complexity, Vehicle dynamics, Traffic control, graph convolutional network BibRef

Wang, T.[Ting], Zhao, S.J.[Sheng-Jie], Jia, W.Z.[Wen-Zhen], Shi, D.[Daqian],
A Task-Oriented Spatial Graph Structure Learning Method for Traffic Forecasting,
ITS(26), No. 4, April 2025, pp. 4770-4779.
IEEE DOI 2504
Forecasting, Roads, Correlation, Learning systems, Feature extraction, Data models, Periodic structures, graph representation BibRef

Englezou, Y.[Yiolanda], Timotheou, S.[Stelios], Panayiotou, C.G.[Christos G.],
Fault-Adaptive Traffic Demand Estimation Using Network Flow Dynamics,
ITS(26), No. 5, May 2025, pp. 6157-6170.
IEEE DOI 2505
Estimation, Sensors, Fault diagnosis, Data models, State estimation, Europe, Computational modeling, Bayes methods, Vehicle dynamics, demand estimation BibRef

Wu, K.[Kai], Hao, F.[Fei], Yao, R.X.[Ruo-Xia], Li, J.H.[Jin-Hai], Min, G.[Geyong], Kuznetsov, S.O.[Sergei O.],
Traffic Prediction Based on Formal Concept-Enhanced Federated Graph Learning,
ITS(26), No. 5, May 2025, pp. 6936-6948.
IEEE DOI 2505
Data models, Training, Predictive models, Accuracy, Data privacy, Federated learning, Roads, Time series analysis, traffic prediction BibRef

Hua, X.[Xin], Liu, W.[Wei],
Spatial-Temporal Network Data-Driven Multi-Layer Traffic Knowledge Graph Reconstruction for Dynamic Prediction,
ICRVC22(20-24)
IEEE DOI 2301
Knowledge engineering, Training, Correlation, Roads, Scalability, Weather forecasting, Transportation, spatial-temporal, ST-KG, reconstruction BibRef

Guo, K.[Ke], Liu, W.X.[Wen-Xi], Pan, J.[Jia],
End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Maps,
CVPR22(2232-2241)
IEEE DOI 2210
Reinforcement learning, Predictive models, Transformers, Trajectory, Task analysis, Behavior analysis, Robot vision BibRef

Sun, Y.W.[Yi-Wen], Wang, Y.[Yulu], Fu, K.[Kun], Wang, Z.[Zheng], Zhang, C.S.[Chang-Shui], Ye, J.P.[Jie-Ping],
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting,
ICPR21(3483-3490)
IEEE DOI 2105
Measurement, Deep learning, Recurrent neural networks, Correlation, Roads, Traffic control, User experience BibRef

Ai, W., Su, Y., Xing, T., Liu, D.,
Phase Plane Analysis of Traffic Flow Evolution Based on Sticky Payne Model,
CVIDL20(237-240)
IEEE DOI 2102
road traffic, phase plane analysis method, nonlinear phenomena, traffic congestion, system instability, phase plan, system stability BibRef

Jiber, M., Lamouik, I., Ali, Y., Sabri, M.A.,
Traffic flow prediction using neural network,
ISCV18(1-4)
IEEE DOI 1807
neural nets, road traffic, traffic engineering computing, transportation, Moroccan center, neural network model, neural network BibRef

Hou, J., Chen, J., Liao, S., Wen, J., Xiong, Q.,
Predicting Traffic Flow via Ensemble Deep Convolutional Neural Networks with Spatio-temporal Joint Relations,
ICPR18(1487-1492)
IEEE DOI 1812
Predictive models, Data models, Optimization, Task analysis, Kernel, Convolutional neural networks BibRef

Zhang, Q., Jin, Q., Chang, J., Xiang, S., Pan, C.,
Kernel-Weighted Graph Convolutional Network: A Deep Learning Approach for Traffic Forecasting,
ICPR18(1018-1023)
IEEE DOI 1812
Kernel, Forecasting, Roads, Task analysis, Convolution, Convolutional neural networks BibRef

Priambodo, B.[Bagus], Ahmad, A.[Azlina],
Predicting Traffic Flow Based on Average Speed of Neighbouring Road Using Multiple Regression,
IVIC17(309-318).
Springer DOI 1711
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Short-Term Traffic Flow Prediction, Forecast .