Spatiotemporal traffic forecasting: review and proposed directions

ABSTRACT This paper systematically reviews studies that forecast short-term traffic conditions using spatial dependence between links. We extract and synthesise 130 research papers, considering two perspectives: (1) methodological framework and (2) methods for capturing spatial information. Spatial information boosts the accuracy of prediction, particularly in congested traffic regimes and for longer horizons. Machine learning methods, which have attracted more attention in recent years, outperform the naïve statistical methods such as historical average and exponential smoothing. However, there is no guarantee of superiority when machine learning methods are compared with advanced statistical methods such as spatiotemporal autoregressive integrated moving average. As for the spatial dependency detection, a large gulf exists between the realistic spatial dependence of traffic links on a real network and the studied networks as follows: (1) studies capture spatial dependency of either adjacent or distant upstream and downstream links with the study link, (2) the spatially relevant links are selected either by prejudgment or by correlation-coefficient analysis, and (3) studies develop forecasting methods in a corridor test sample, where all links are connected sequentially together, assume a similarity between the behaviour of both parallel and adjacent links, and overlook the competitive nature of traffic links.

[1]  Wanli Min,et al.  Real-time road traffic prediction with spatio-temporal correlations , 2011 .

[2]  Zilu Liang,et al.  Real-time urban traffic amount prediction models for dynamic route guidance systems , 2014, EURASIP Journal on Wireless Communications and Networking.

[3]  Baher Abdulhai,et al.  Short-Term Traffic Flow Prediction Using Neuro-Genetic Algorithms , 2002, J. Intell. Transp. Syst..

[4]  V. Fabrizi,et al.  A pattern matching approach to speed forecasting of traffic networks , 2014, European Transport Research Review.

[5]  J. Haworth.  Spatio-temporal forecasting of network data , 2014 .

[6]  Alessandro De Gloria,et al.  Time-Aware Multivariate Nearest Neighbor Regression Methods for Traffic Flow Prediction , 2015, IEEE Transactions on Intelligent Transportation Systems.

[7]  Eleni I. Vlahogianni,et al.  Short‐term traffic forecasting: Overview of objectives and methods , 2004 .

[8]  Limin Jia,et al.  Urban expressway traffic state forecasting based on multimode maximum entropy model , 2010 .

[9]  François Bavaud,et al.  MODELS FOR SPATIAL WEIGHTS: A SYSTEMATIC LOOK , 2010 .

[10]  Anton Agafonov,et al.  Traffic Flow Forecasting Algorithm Based on Combination of Adaptive Elementary Predictors , 2015, AIST.

[11]  Biswajit Basu,et al.  Multivariate Short-Term Traffic Flow Forecasting Using Time-Series Analysis , 2009, IEEE Transactions on Intelligent Transportation Systems.

[12]  Billy M. Williams.  Multivariate Vehicular Traffic Flow Prediction: Evaluation of ARIMAX Modeling , 2001 .

[13]  Ying Zhu,et al.  DeepSense: A novel learning mechanism for traffic prediction with taxi GPS traces , 2014, 2014 IEEE Global Communications Conference.

[14]  Jin Xin Cao,et al.  Traffic volume forecasting based on radial basis function neural network with the consideration of traffic flows at the adjacent intersections , 2014 .

[15]  Haitham Al-Deek,et al.  Cross-Correlation Analysis and Multivariate Prediction of Spatial Time Series of Freeway Traffic Speeds , 2008 .

[16]  Nedal T. Ratrout,et al.  Short-term Traffic Flow Prediction Using Group Method Data Handling (GMDH)-based Abductive Networks , 2013, Arabian Journal for Science and Engineering.

[17]  Li Li,et al.  Efficient missing data imputing for traffic flow by considering temporal and spatial dependence , 2013 .

[18]  Bo Peng,et al.  Short‐term traffic flow prediction with linear conditional Gaussian Bayesian network , 2016 .

[19]  Hsing-Kuo Kenneth Pao,et al.  Efficient traffic speed forecasting based on massive heterogenous historical data , 2014, 2014 IEEE International Conference on Big Data (Big Data).

[20]  Yuanchang Xie,et al.  A Wavelet Network Model for Short-Term Traffic Volume Forecasting , 2006, J. Intell. Transp. Syst..

[21]  Shiliang Sun,et al.  Traffic Flow Forecasting Using a Spatio-temporal Bayesian Network Predictor , 2005, ICANN.

[22]  Zuo Zhang,et al.  Urban traffic network modeling and short-term traffic flow forecasting based on GSTARIMA model , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[23]  Nicholas G. Polson,et al.  Deep Learning Predictors for Traffic Flows , 2016 .

[24]  Eleni I. Vlahogianni,et al.  Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach , 2005 .

[25]  Antony Stathopoulos,et al.  Fuzzy Modeling Approach for Combined Forecasting of Urban Traffic Flow , 2008, Comput. Aided Civ. Infrastructure Eng..

[26]  David M Levinson,et al.  Development and application of the network weight matrix to predict traffic flow for congested and uncongested conditions , 2019 .

[27]  Yi Zhang,et al.  Short-term traffic flow forecasting of urban network based on dynamic STARIMA model , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[28]  Slobodan Vucetic,et al.  Travel Speed Forecasting by Means of Continuous Conditional Random Fields , 2011 .

[29]  Matthew G. Karlaftis,et al.  A multivariate state space approach for urban traffic flow modeling and prediction , 2003 .

[30]  Jiaqiu Wang,et al.  A Dynamic Spatial Weight Matrix and Localized Space–Time Autoregressive Integrated Moving Average for Network Modeling , 2014 .

[31]  J. K. Ord,et al.  Space-time modelling with an application to regional forecasting , 1975 .

[32]  Fabien Moutarde,et al.  Analysis of network-level traffic states using locality preservative non-negative matrix factorization , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[33]  James Bailey,et al.  Traffic forecasting in complex urban networks: Leveraging big data and machine learning , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[34]  Sherif Ishak,et al.  Optimization of Dynamic Neural Network Performance for Short-Term Traffic Prediction , 2003 .

[35]  Haitham Al-Deek,et al.  Predictions of Freeway Traffic Speeds and Volumes Using Vector Autoregressive Models , 2009, J. Intell. Transp. Syst..

[36]  Salissou Moutari,et al.  A hybrid macroscopic-based model for traffic flow in road networks , 2010, Eur. J. Oper. Res..

[37]  Tao Cheng,et al.  Non-parametric regression for space-time forecasting under missing data , 2012, Comput. Environ. Urban Syst..

[38]  Stephen H Richards,et al.  Flow rate and time mean speed predictions for the urban freeway network using state space models , 2014 .

[39]  Dimitrios Tzovaras,et al.  Managing Spatial Graph Dependencies in Large Volumes of Traffic Data for Travel-Time Prediction , 2016, IEEE Transactions on Intelligent Transportation Systems.

[40]  A. Pascale,et al.  Adaptive Bayesian network for traffic flow prediction , 2011, 2011 IEEE Statistical Signal Processing Workshop (SSP).

[41]  Fangfang Zheng,et al.  Urban link travel time estimation based on sparse probe vehicle data , 2013 .

[42]  Eleni I. Vlahogianni,et al.  Spatio‐Temporal Short‐Term Urban Traffic Volume Forecasting Using Genetically Optimized Modular Networks , 2007, Comput. Aided Civ. Infrastructure Eng..

[43]  Bin Yu,et al.  k-Nearest Neighbor Model for Multiple-Time-Step Prediction of Short-Term Traffic Condition , 2016 .

[44]  H. J. Van Zuylen,et al.  Bayesian Training and Committees of State-Space Neural Networks for Online Travel Time Prediction , 2009 .

[45]  Dongjoo Park,et al.  Forecasting Freeway Link Travel Times with a Multilayer Feedforward Neural Network , 1999 .

[46]  G. Antes,et al.  Five Steps to Conducting a Systematic Review , 2003, Journal of the Royal Society of Medicine.

[47]  J. W. C. van Lint,et al.  Online Learning Solutions for Freeway Travel Time Prediction , 2008, IEEE Transactions on Intelligent Transportation Systems.

[48]  Weiqi Wang,et al.  Traffic Prediction Based on Correlation of Road Sections , 2013 .

[49]  Agachai Sumalee,et al.  Short-Term Traffic State Prediction Based on Temporal–Spatial Correlation , 2013, IEEE Transactions on Intelligent Transportation Systems.

[50]  Sul.I. Bajwa,et al.  Performance evaluation of an adaptive travel time prediction model , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[51]  Ming-Tsung Lee.  Short-term Freeway Traffic Flow Forecasting with ARIMAX Modeling , 2010 .

[52]  Jinyoung Ahn,et al.  3D Markov Process for Traffic Flow Prediction in Real-Time , 2016, Sensors.

[53]  Xiaosi Zeng,et al.  Development of Recurrent Neural Network Considering Temporal‐Spatial Input Dynamics for Freeway Travel Time Modeling , 2013, Comput. Aided Civ. Infrastructure Eng..

[54]  Jon Shaw.  The Geography of Transport Systems, 4th edition, J.-P. Rodrigue, C. Comtois, B. Slack (Eds.), Routledge, Abingdon (2017), (440pp. £140 (hardback) £46.99 (paperback) £23.50 (ebook) ISBN 978-1138669574) , 2019 .

[55]  Jun Hu,et al.  Spatial econometrics models for congestion prediction with in-vehicle route guidance , 2009 .

[56]  Baher Abdulhai,et al.  Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction , 2015 .

[57]  Jingyan Song,et al.  A novel networked traffic parameter forecasting method based on Markov chain model , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[58]  Antony Stathopoulos,et al.  Adaptive hybrid fuzzy rule-based system approach for modeling and predicting urban traffic flow , 2008 .

[59]  Yajie Zou,et al.  A space–time diurnal method for short-term freeway travel time prediction , 2014 .

[60]  Chang-Tien Lu,et al.  Traffic Flow Prediction for Urban Network using Spatio-Temporal Random , 2011 .

[61]  B. Engr,et al.  A hybrid model-based and memory-based short-term traffic prediction system , 2003 .

[62]  Tong Zou,et al.  Short-Time Traffic Flow Forecasting Based on the K-Nearest Neighbor Model , 2015 .

[63]  Zili Zhang,et al.  A distributed spatial-temporal weighted model on MapReduce for short-term traffic flow forecasting , 2016, Neurocomputing.

[64]  Su Yang,et al.  Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection , 2015, PloS one.

[65]  Markos Papageorgiou,et al.  Unified Approach to Real-Time Freeway Network Traffic Surveillance , 2006 .

[66]  Chang-Tien Lu,et al.  Urban Traffic Flow Prediction Using a Spatio-Temporal Random Effects Model , 2016, J. Intell. Transp. Syst..

[67]  Bin Ran,et al.  Traffic Speed Data Imputation Method Based on Tensor Completion , 2015, Comput. Intell. Neurosci..

[68]  N. H. C. Yung,et al.  Modeling of traffic data characteristics by Dirichlet Process Mixtures , 2012, 2012 IEEE International Conference on Automation Science and Engineering (CASE).

[69]  Praveen Edara,et al.  Traffic Flow Forecasting for Urban Work Zones , 2015, IEEE Transactions on Intelligent Transportation Systems.

[70]  Alexandre M. Bayen,et al.  Estimating arterial traffic conditions using sparse probe data , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[71]  Satu Innamaa,et al.  Short-Term Prediction of Travel Time using Neural Networks on an Interurban Highway , 2005 .

[72]  Jackie MacDonald,et al.  Systematic Approaches to a Successful Literature Review , 2014 .

[73]  I Okutani,et al.  Dynamic prediction of traffic volume through Kalman Filtering , 1984 .

[74]  Yupo Chan,et al.  A microstate spatial-inference model for network-traffic estimation , 2013 .

[75]  Xia Li,et al.  Short-Term Traffic Flow Forecasting of Road Network Based on Spatial-Temporal Characteristics of Traffic Flow , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[76]  Muhammad Tayyab Asif,et al.  Wavelets on graphs with application to transportation networks , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[77]  Yang Yue,et al.  Prediction Time Horizon and Effectiveness of Real-time Data on Short-term Traffic Predictability , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[78]  Serge P. Hoogendoorn,et al.  Toward a Robust Framework for Freeway Travel time Prediction: Experiments with Simple Imputation and State-Space Neural Networks , 2003 .

[79]  Tao Yongqin,et al.  The Forecast and the Optimization Control of the Complex Traffic Flow Based on the Hybrid Immune Intelligent Algorithm , 2014 .

[80]  Srinivasa Ravi Chandra,et al.  Spatio-temporal Analyses For Prediction Of Traffic Flow, Speed And Occupancy On I-4 , 2009 .

[81]  Zheng-Wu Yuan,et al.  Research on K Nearest Neighbor Non-parametric Regression Algorithm Based on KD-Tree and Clustering Analysis , 2012, 2012 Fourth International Conference on Computational and Information Sciences.

[82]  Kaigui Bian,et al.  Traffic Flow Decomposition and Prediction Based on Robust Principal Component Analysis , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[83]  Fabien Moutarde,et al.  Statistical Traffic State Analysis in Large-scale Transportation Networks Using Locality-Preserving Non-negative Matrix Factorization , 2012, ArXiv.

[84]  Liang Chen,et al.  Paratactic Spatial-Temporal Two Dimension Data Fusion Based on Support Vector Machines for Traffic Flow Prediction of Abnormal State , 2012 .

[85]  Thomas Urbanik,et al.  Short-Term Freeway Traffic Volume Forecasting Using Radial Basis Function Neural Network , 1998 .

[86]  David M Levinson,et al.  An Introduction to the Network Weight Matrix , 2017 .

[87]  van Lint,et al.  Reliable Real-Time Framework for Short-Term Freeway Travel Time Prediction , 2006 .

[88]  Srinivas S. Pulugurtha,et al.  ARIMA Model for Forecasting Short-Term Travel Time due to Incidents in Spatio-Temporal Context , 2015 .

[89]  Hui Chen,et al.  Urban traffic flow prediction: a spatio‐temporal variable selection‐based approach , 2016 .

[90]  Wei Shen,et al.  Real-time road traffic forecasting using regime-switching space-time models and adaptive LASSO , 2012 .

[91]  Zhiheng Li,et al.  Improving the Traffic Data Imputation Accuracy Using Temporal and Spatial Information , 2014, 2014 7th International Conference on Intelligent Computation Technology and Automation.

[92]  Y. Kamarianakis,et al.  Forecasting Traffic Flow Conditions in an Urban Network: Comparison of Multivariate and Univariate Approaches , 2003 .

[93]  Yanru Zhang,et al.  Hybrid short-term freeway speed prediction methods based on periodic analysis , 2015 .

[94]  Cheng Hu,et al.  Hybrid Process Neural Network based on Spatio-Temporal Similarities for Short-Term Traffic Flow Prediction , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[95]  Billy M. Williams,et al.  Comparison of parametric and nonparametric models for traffic flow forecasting , 2002 .

[96]  Yinhai Wang,et al.  Short-Term Speed Prediction Using Remote Microwave Sensor Data: Machine Learning versus Statistical Model , 2016 .

[97]  Rajesh Krishnan,et al.  Short-Term Traffic Prediction Under Normal and Abnormal Traffic Conditions on Urban Roads , 2012 .

[98]  Zhihua Xiong,et al.  A spatial–temporal-based state space approach for freeway network traffic flow modelling and prediction , 2015 .

[99]  Yiannis Kamarianakis,et al.  Space-time modeling of traffic flow , 2002, Comput. Geosci..

[100]  Ruimin Deng,et al.  TRAFFIC STATE FORECAST OF ROAD NETWORK BASED ON SPATIAL-TEMPORAL DATA MINING , 2011 .

[101]  S. P. Hoogendoorn,et al.  Freeway Travel Time Prediction with State-Space Neural Networks: Modeling State-Space Dynamics with Recurrent Neural Networks , 2002 .

[102]  Yanru Zhang,et al.  A Comparative Study of Three Multivariate Short-Term Freeway Traffic Flow Forecasting Methods With Missing Data , 2016, J. Intell. Transp. Syst..

[103]  Sherif Ishak,et al.  Optimizing traffic prediction performance of neural networks under various topological, input, and traffic condition settings , 2004 .

[104]  Gaetano Valenti,et al.  Traffic Estimation And Prediction Based On Real Time Floating Car Data , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[105]  Snigdhansu Chatterjee,et al.  Using temporal detrending to observe the spatial correlation of traffic , 2017, PloS one.

[106]  Chih-Wei Yi,et al.  Negative Binomial Additive Models for Short-Term Traffic Flow Forecasting in Urban Areas , 2014, IEEE Transactions on Intelligent Transportation Systems.

[107]  Rajesh Krishnan,et al.  Short-term traffic prediction under normal and incident conditions using singular spectrum analysis and the k-nearest neighbour method , 2012 .

[108]  Shiliang Sun,et al.  The Selective Random Subspace Predictor for Traffic Flow Forecasting , 2007, IEEE Transactions on Intelligent Transportation Systems.

[109]  B. Slack,et al.  The Geography of Transport Systems , 2006 .

[110]  Yang Yue,et al.  Spatiotemporal Traffic-Flow Dependency and Short-Term Traffic Forecasting , 2008 .

[111]  Jianjiang Yang,et al.  SPATIO-TEMPORAL DYNAMICS OF SHORT-TERM TRAFFIC , 2015 .

[112]  Jinyoung Ahn,et al.  Predicting Spatiotemporal Traffic Flow Based on Support Vector Regression and Bayesian Classifier , 2015, 2015 IEEE Fifth International Conference on Big Data and Cloud Computing.

[113]  Bin Yu,et al.  Improved k-nn for Short-Term Traffic Forecasting Using Temporal and Spatial Information , 2014 .

[114]  R Van Grol,et al.  ON-LINE TRAFFIC CONDITION FORECASTING USING ON-LINE MEASUREMENTS AND A HISTORICAL DATABASE , 2000 .

[115]  Tianlu Pan.  The stochastic dynamic journey time reliability analysis by considering the spatial and temporal correlation , 2012 .

[116]  Michael A. West,et al.  Statistical Analyses of Freeway Traffic Flows , 2002 .

[117]  Shiliang Sun,et al.  Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks , 2012 .

[118]  Wang Shuo,et al.  Flight Tests of Autopilot Integrated with Fault-Tolerant Control of a Small Fixed-Wing UAV , 2016 .

[119]  Stephen D. Clark,et al.  THE USE OF NEURAL NETWORKS AND TIME SERIES MODELS FOR SHORT TERM TRAFFIC FORECASTING: A COMPARATIVE STUDY , 1993 .

[120]  Kenneth L Head,et al.  EVENT-BASED SHORT-TERM TRAFFIC FLOW PREDICTION MODEL , 1995 .

[121]  Lee D. Han,et al.  Short-Term Freeway Speed Profiling Based on Longitudinal Spatiotemporal Dynamics , 2014 .

[122]  Gaetano Fusco,et al.  Comparative Analysis of Implicit Models for Real-time Short-term Traffic Predictions , 2016 .

[123]  Shuai Ling,et al.  Key Factors of K-Nearest Neighbours Nonparametric Regression in Short-Time Traffic Flow Forecasting , 2015, IEEM 2015.

[124]  Saeid Nahavandi,et al.  Prediction Intervals to Account for Uncertainties in Travel Time Prediction , 2011, IEEE Transactions on Intelligent Transportation Systems.

[125]  Satu Innamaa.  Self-adapting traffic flow status forecasts using clustering , 2009 .

[126]  P. Abbeel,et al.  Short – Term Traffic Forecasting : Modeling and Learning Spatio – Temporal Relations in Transportation Networks Using Graph Neural Networks by Behrooz Shahsavari Research Project , 2015 .

[127]  Baher Abdulhai,et al.  Short Term Freeway Traffic Flow Prediction Using Genetically-Optimized Time-Delay-Based Neural Networks , 1999 .

[128]  Jiaqiu Wang,et al.  Spatio-temporal autocorrelation of road network data , 2012, J. Geogr. Syst..

[129]  Zuo Zhang,et al.  Short-Term Traffic Flow Forecasting Based on MARS , 2008, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery.

[130]  Shiliang Sun,et al.  High-Order Gaussian Process Dynamical Models for Traffic Flow Prediction , 2016, IEEE Transactions on Intelligent Transportation Systems.

[131]  Paolo Frasconi,et al.  Collective Traffic Forecasting , 2010, ECML/PKDD.

[132]  Fei-Yue Wang,et al.  Traffic Flow Prediction With Big Data: A Deep Learning Approach , 2015, IEEE Transactions on Intelligent Transportation Systems.

[133]  Alexandre M. Bayen,et al.  Learning the dependency structure of highway networks for traffic forecast , 2011, IEEE Conference on Decision and Control and European Control Conference.

[134]  Cheng Hu,et al.  A Multiple SVR Approach with Time Lags for Traffic Flow Prediction , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[135]  Dimitris Kotzinos,et al.  Bivariate Traffic Relations: a Space-Time Modeling Approach ∗ , 2004 .

[136]  Jiaqiu Wang,et al.  Modelling dynamic space-time autocorrelations of urban transport network , 2011 .

[137]  Rajesh Krishnan,et al.  Comparison of modelling approaches for short term traffic prediction under normal and abnormal conditions , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[138]  Gaetano Fusco,et al.  Short-term traffic predictions on large urban traffic networks: Applications of network-based machine learning models and dynamic traffic assignment models , 2015, 2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS).

[139]  Ruimin Li,et al.  Combined Neural Network Approach for Short-Term Urban Freeway Traffic Flow Prediction , 2009, ISNN.