Spatial Extension of Road Traffic Sensor Data with Artificial Neural Networks

This paper proposes a method for estimating traffic flows on some links of a road network knowing the data on other links that are monitored with sensors. In this way, it is possible to obtain more information on traffic conditions without increasing the number of monitored links. The proposed method is based on artificial neural networks (ANNs), wherein the input data are the traffic flows on some monitored road links and the output data are the traffic flows on some unmonitored links. We have implemented and tested several single-layer feed-forward ANNs that differ in the number of neurons and the method of generating datasets for training. The proposed ANNs were trained with a supervised learning approach where input and output example datasets were generated through traffic simulation techniques. The proposed method was tested on a real-scale network and gave very good results if the travel demand patterns were known and used for generating example datasets, and promising results if the demand patterns were not considered in the procedure. Numerical results have underlined that the ANNs with few neurons were more effective than the ones with many neurons in this specific problem.

[1]  Jürgen Schmidhuber,et al.  Multi-column deep neural network for traffic sign classification , 2012, Neural Networks.

[2]  Qi Qi,et al.  Wireless sensor networks in intelligent transportation systems , 2009, Wirel. Commun. Mob. Comput..

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

[4]  Lorenzo Mussone,et al.  A Neural Network Approach to Motorway OD Matrix Estimation from Loop Counts , 2010 .

[5]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Samson Mathew,et al.  OD Matrix Estimation from Link Counts Using Artificial Neural Network , 2013 .

[7]  Stelios Timotheou,et al.  The Random Neural Network: A Survey , 2010, Comput. J..

[8]  Enzo Baccarelli,et al.  Energy-saving adaptive computing and traffic engineering for real-time-service data centers , 2015, 2015 IEEE International Conference on Communication Workshop (ICCW).

[9]  Corinne Ledoux,et al.  An urban traffic flow model integrating neural networks , 1997 .

[10]  Darío Baptista,et al.  A survey of artificial neural network training tools , 2013, Neural Computing and Applications.

[11]  Shu Lin,et al.  Short-Term Traffic Flow Forecasting Using Macroscopic Urban Traffic Network Model , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[12]  Fulvio Simonelli,et al.  An artificial neural network approach for spatially extending road traffic monitoring measures , 2016, 2016 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS).

[13]  Jaime G. Carbonell,et al.  Nonparametric Neural Networks , 2017, ICLR.

[14]  S. Grossberg.  Neural Networks and Natural Intelligence , 1988 .

[15]  Rituparna Chaki,et al.  Applications of wireless sensor network in Intelligent Traffic System: A review , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[16]  YiZhang,et al.  Shortest path computation using pulse-coupled neural networks with restricted autowave , 2016 .

[17]  Charu C. Aggarwal,et al.  Neural Networks and Deep Learning , 2018, Springer International Publishing.

[18]  Alondra Chamorro,et al.  Data collection technologies for road management , 2006 .

[19]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[20]  Yurong Liu,et al.  A survey of deep neural network architectures and their applications , 2017, Neurocomputing.

[21]  Eduardo D. Sontag,et al.  Neural Networks for Control , 1993 .

[22]  Lorenzo Mussone,et al.  NEURAL-NETWORK MODELS FOR CLASSIFICATION AND FORECASTING OF FREEWAY TRAFFIC FLOW STABILITY , 1994 .

[23]  Hai Yang,et al.  A neural network approach to the identification of real time origin-destination flows from traffic counts , 1992 .

[24]  Manoranjan Parida,et al.  Short Term Traffic Flow Prediction for a Non Urban Highway Using Artificial Neural Network , 2013 .

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

[26]  Zhang Yi,et al.  Shortest path computation using pulse-coupled neural networks with restricted autowave , 2016, Knowl. Based Syst..

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

[28]  Thomas Jackson,et al.  Short-Term Traffic Prediction Using a Binary Neural Network. , 2011 .

[29]  S. Haykin.  Kalman Filtering and Neural Networks , 2001 .

[30]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[31]  Lu Zhen,et al.  Unmanned aerial vehicle scheduling problem for traffic monitoring , 2018, Comput. Ind. Eng..

[32]  O. L. Z..  Book Review: The Organization of Behaviour: A Neuropsychological Theory , 1950 .

[33]  Hwasoo Yeo,et al.  Short-term Travel-time Prediction on Highway: A Review of the Data-driven Approach , 2015 .

[34]  Xin Yao,et al.  A review of evolutionary artificial neural networks , 1993, Int. J. Intell. Syst..

[35]  Shiliang Sun,et al.  Multi-link traffic flow forecasting using neural networks , 2010, 2010 Sixth International Conference on Natural Computation.

[36]  Yang Lu,et al.  Origin-Destination Estimation Using Probe Vehicle Trajectory and Link Counts , 2017 .

[37]  G. Klunder,et al.  Improvement of Network Performance by In-Vehicle Routing Using Floating Car Data , 2017 .

[38]  Shinya Kikuchi,et al.  A METHOD TO ESTIMATE TRIP O-D PATTERNS USING A NEURAL NETWORK APPROACH. , 1993 .

[39]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[40]  Agathoniki Trigoni,et al.  Utilizing Correlations to Compress Time-Series in Traffic Monitoring Sensor Networks , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[41]  Ah Chung Tsoi,et al.  Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results , 1998, Neural Networks.

[42]  E. Cascetta.  Estimation of trip matrices from traffic counts and survey data: A generalized least squares estimator , 1984 .

[43]  Luca D'Acierno,et al.  Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System , 2009, Eur. J. Oper. Res..

[44]  Doreen Meier,et al.  Neural Network Design And The Complexity Of Learning , 2016 .

[45]  Guang-Bin Huang,et al.  Trends in extreme learning machines: A review , 2015, Neural Networks.

[46]  Rajesh Krishnan,et al.  Short-term prediction of traffic flow using a binary neural network , 2014, Neural Computing and Applications.

[47]  Fulvio Simonelli,et al.  Limits and perspectives of effective O-D matrix correction using traffic counts , 2009 .

[48]  Junwei Gao,et al.  Short-term traffic flow forecasting model based on wavelet neural network , 2013, 2013 25th Chinese Control and Decision Conference (CCDC).

[49]  Enzo Baccarelli,et al.  Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: review, challenges, and a case study , 2016, IEEE Network.

[50]  Mark Dougherty,et al.  THE USE OF NEURAL NETWORKS TO RECOGNISE AND PREDICT TRAFFIC CONGESTION , 1993 .

[51]  Chalermpol Saiprasert,et al.  Combining Unsupervised Anomaly Detection and Neural Networks for Driver Identification , 2017 .

[52]  Zhejun Gong.  Estimating the urban OD matrix: A neural network approach , 1998, Eur. J. Oper. Res..

[53]  Guillaume Leduc,et al.  Road Traffic Data: Collection Methods and Applications , 2008 .

[54]  Frank Rosenblatt,et al.  PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS , 1963 .

[55]  Wei Huang,et al.  A time-delay neural network for solving time-dependent shortest path problem , 2017, Neural Networks.

[56]  Marvin Minsky,et al.  An introduction to computational geometry , 1969 .

[57]  G. Bebis,et al.  On-road vehicle detection using optical sensors: a review , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[58]  Michael G.H. Bell,et al.  The Estimation of an Origin-Destination Matrix from Traffic Counts , 1983 .

[59]  Raúl Rojas,et al.  Neural Networks - A Systematic Introduction , 1996 .

[60]  Eleni I. Vlahogianni,et al.  Short-term traffic forecasting: Where we are and where we’re going , 2014 .

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

[62]  Mark Dougherty,et al.  SHOULD WE USE NEURAL NETWORKS OR STATISTICAL MODELS FOR SHORT TERM MOTORWAY TRAFFIC FORECASTING , 1997 .

[63]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.

[64]  Stephen G. Ritchie,et al.  Macroscopic Modeling of Freeway Traffic Using an Artificial Neural Network , 1997 .

[65]  Der-Horng Lee,et al.  Short-term freeway traffic flow prediction : Bayesian combined neural network approach , 2006 .

[66]  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 .

[67]  Ramin Yasdi.  Prediction of Road Traffic using a Neural Network Approach , 1999, Neural Computing & Applications.

[68]  Lawrence A. Klein,et al.  Traffic Detector Handbook: Third Edition - Volume I , 2006 .

[69]  Enzo Baccarelli,et al.  Reliable Adaptive Resource Management for Cognitive Cloud Vehicular Networks , 2015, IEEE Transactions on Vehicular Technology.

[70]  Mark Dougherty,et al.  A REVIEW OF NEURAL NETWORKS APPLIED TO TRANSPORT , 1995 .

[71]  Juan Antonio Álvarez,et al.  Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods , 2018, Neural Networks.

[72]  Mariano Gallo,et al.  Artificial neural networks for forecasting user flows in transportation networks: Literature review, limits, potentialities and open challenges , 2017, 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS).

[73]  István Varga,et al.  Traffic speed prediction method for urban networks — an ANN approach , 2015, 2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS).

[74]  Kar-Ann Toh,et al.  Reduced multivariate polynomial-based neural network for automated traffic incident detection , 2008, Neural Networks.

[75]  Jürgen Schmidhuber,et al.  Deep learning in neural networks: An overview , 2014, Neural Networks.

[76]  Giuseppe Salvo,et al.  Urban traffic analysis through an UAV , 2014 .

[77]  Carl Goves,et al.  Short Term Traffic Prediction of the UK Motorway Network Using Neural Networks , 2015 .