Traffic Management for Smart Cities

Smart cities, participatory sensing as well as location data available in communication systems and social networks generates a vast amount of heterogeneous mobility data that can be used for traffic management . This chapter gives an overview of the different data sources and their characteristics and describes a framework for utilizing the various sources efficiently in the context of traffic management. Furthermore, different types of traffic models and algorithms are related to both the different data sources as well as some key functionalities of active traffic management, for example, short-term prediction and control.

[1]  Markos Papageorgiou,et al.  Coordinated ramp metering for freeway networks – A model-predictive hierarchical control approach , 2010 .

[2]  Haris N. Koutsopoulos,et al.  Path inference from sparse floating car data for urban networks , 2013 .

[3]  Ernesto Cipriani,et al.  Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design, demonstration and validation , 2016 .

[4]  A. Bayen,et al.  A traffic model for velocity data assimilation , 2010 .

[5]  David M Levinson,et al.  Optimal Freeway Ramp Control without Origin-Destination Information , 2004 .

[6]  Aude Hofleitner,et al.  Leveraging geolocalization technologies to model and estimate urban traffic , 2012 .

[7]  Alexandre M. Bayen,et al.  Travel Time and Point Speed Fusion Based on a Macroscopic Traffic Model and Non-linear Filtering , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[8]  Peter Nijkamp,et al.  Mobile phone data from GSM networks for traffic parameter and urban spatial pattern assessment: a review of applications and opportunities , 2011, GeoJournal.

[9]  Alexandre M. Bayen,et al.  Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment , 2009 .

[10]  Nikolaos Geroliminis,et al.  Properties of a well-defined Macroscopic Fundamental Diagram for urban traffic , 2011 .

[11]  Xiaoliang Ma,et al.  Analysis of a cooperative variable speed limit system using microscopic traffic simulation , 2015 .

[12]  Nikolas Geroliminis,et al.  Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control , 2015 .

[13]  Markos Papageorgiou,et al.  ALINEA: A LOCAL FEEDBACK CONTROL LAW FOR ON-RAMP METERING , 1990 .

[14]  H. B. Mitchell,et al.  Multi-Sensor Data Fusion: An Introduction , 2007 .

[15]  Alexandre M. Bayen,et al.  Understanding Road Usage Patterns in Urban Areas , 2012, Scientific Reports.

[16]  Johan Wideberg,et al.  Deriving origin destination data from a mobile phone network , 2007 .

[17]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[18]  Markos Papageorgiou,et al.  Local Feedback-Based Mainstream Traffic Flow Control on Motorways Using Variable Speed Limits , 2011, IEEE Transactions on Intelligent Transportation Systems.

[19]  Nikolaos Geroliminis,et al.  Perimeter and boundary flow control in multi-reservoir heterogeneous networks , 2013 .

[20]  Bart De Schutter,et al.  Optimal coordination of variable speed limits to suppress shock waves , 2005, IEEE Transactions on Intelligent Transportation Systems.

[21]  Alexandre M. Bayen,et al.  Trade-offs Between Inductive Loops and GPS Probe Vehicles for Travel Time Estimation: Mobile Century Case Study , 2012 .

[22]  Nikolaos Geroliminis,et al.  On the stability of traffic perimeter control in two-region urban cities , 2012 .

[23]  Roberto Horowitz,et al.  Optimal freeway ramp metering using the asymmetric cell transmission model , 2006 .

[24]  M J Lighthill,et al.  On kinematic waves II. A theory of traffic flow on long crowded roads , 1955, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[25]  Markos Papageorgiou,et al.  Modelling and real-time control of traffic flow on the southern part of Boulevard Peripherique in Paris: Part I: Modelling , 1990 .

[26]  Klaus Bogenberger,et al.  Advanced Coordinated Traffic Responsive Ramp Metering Strategies , 1999 .

[27]  Kitae Kim,et al.  Evaluation of Technologies for Freeway Travel Time Estimation: Case Study of I-287 in New Jersey , 2011 .

[28]  Cynthia Taylor,et al.  Fuzzy Ramp Metering: Design Overview and Simulation Results , 1998 .

[29]  Vikash V. Gayah,et al.  Accuracy of Networkwide Traffic States Estimated from Mobile Probe Data , 2014 .

[30]  Bell Atlantic Nynex Mobile Final evaluation report for the CAPITAL-ITS operational test and demonstration program , 1997 .

[31]  J. Barceló Fundamentals of traffic simulation , 2010 .

[32]  Serge P. Hoogendoorn,et al.  A Robust and Efficient Method for Fusing Heterogeneous Data from Traffic Sensors on Freeways , 2010, Comput. Aided Civ. Infrastructure Eng..

[33]  Andreas Hegyi,et al.  SPECIALIST: A dynamic speed limit control algorithm based on shock wave theory , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[34]  Pu Wang,et al.  Development of origin–destination matrices using mobile phone call data , 2014 .

[35]  Nikolas Geroliminis,et al.  Optimal Perimeter Control for Two Urban Regions With Macroscopic Fundamental Diagrams: A Model Predictive Approach , 2013, IEEE Transactions on Intelligent Transportation Systems.

[36]  J. W. C. van Lint,et al.  Empirical Evaluation of New Robust Travel Time Estimation Algorithms , 2010 .

[37]  Henry Leung,et al.  Data fusion in intelligent transportation systems: Progress and challenges - A survey , 2011, Inf. Fusion.

[38]  Ernesto Cipriani,et al.  A Gradient Approximation Approach for Adjusting Temporal Origin–Destination Matrices , 2011 .

[39]  Chris Bachmann,et al.  A comparative assessment of multi-sensor data fusion techniques for freeway traffic speed estimation using microsimulation modeling , 2013 .

[40]  Clas Rydergren,et al.  Optimal toll locations and toll levels in congestion pricing schemes: a case study of Stockholm , 2014 .

[41]  A. Hegyi,et al.  MPC-based optimal coordination of variable speed limits to suppress shock waves in freeway traffic , 2003, Proceedings of the 2003 American Control Conference, 2003..

[42]  Markos Papageorgiou,et al.  Integrated feedback ramp metering and mainstream traffic flow control on motorways using variable speed limits , 2014 .

[43]  Nikolaos Geroliminis,et al.  On the spatial partitioning of urban transportation networks , 2012 .

[44]  Andreas Hegyi,et al.  SPECIALIST-RM — Integrated variable speed limit control and ramp metering based on shock wave theory , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[45]  Carlos F. Daganzo,et al.  Urban Gridlock: Macroscopic Modeling and Mitigation Approaches , 2007 .

[46]  P J Wong,et al.  GUIDELINES FOR DESIGN AND OPERATION OF RAMP CONTROL SYSTEMS , 1975 .

[47]  C. Daganzo THE CELL TRANSMISSION MODEL.. , 1994 .

[48]  Vikash V. Gayah,et al.  Using Mobile Probe Data and the Macroscopic Fundamental Diagram to Estimate Network Densities , 2013 .

[49]  Chris Lee,et al.  Evaluation of Variable Speed Limits to Improve Traffic Safety , 2006 .

[50]  José Cuena,et al.  Knowledge-based models for adaptive traffic management systems , 1995 .

[51]  Alexandre M. Bayen,et al.  The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data , 2014, WAFR.

[52]  Markos Papageorgiou,et al.  Traffic-Responsive Linked Ramp-Metering Control , 2008, IEEE Transactions on Intelligent Transportation Systems.

[53]  Harry Lahrmann,et al.  Bluetooth detektorer som ny cost - effektiv sensor i vejtrafikken Forfattere: , 2010 .

[54]  Karine Zeitouni,et al.  Proactive Vehicular Traffic Rerouting for Lower Travel Time , 2013, IEEE Transactions on Vehicular Technology.

[55]  E. van den Hoogen,et al.  Control by variable speed signs: results of the Dutch experiment , 1994 .

[56]  Ludovic Leclercq,et al.  Macroscopic Fundamental Diagrams: A cross-comparison of estimation methods , 2014 .

[57]  Alexandre M. Bayen,et al.  An ensemble Kalman filtering approach to highway traffic estimation using GPS enabled mobile devices , 2008, 2008 47th IEEE Conference on Decision and Control.

[58]  Hillel Bar-Gera,et al.  Evaluation of a Cellular Phone-Based System for Measurements of Traffic Speeds and Travel Times: A Case Study from Israel , 2007 .

[59]  Jay H. Lee,et al.  Model predictive control: past, present and future , 1999 .

[60]  Haris N. Koutsopoulos,et al.  Kalman Filter Applications for Traffic Management , 2010 .

[61]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..

[62]  Bart De Schutter,et al.  Model predictive control for optimal coordination of ramp metering and variable speed limits , 2005 .

[63]  Anders Peterson,et al.  A heuristic for the bilevel origin-destination-matrix estimation problem , 2008 .

[64]  Lídia Montero Mercadé,et al.  A Kalman-filter approach for dynamic OD estimation in corridors based on bluetooth and Wi-Fi data collection , 2010 .

[65]  Larry Rudolph,et al.  Bluetooth Essentials for Programmers , 2007 .

[66]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[67]  R. Kalman,et al.  New results in linear prediction and filtering theory Trans. AMSE , 1961 .

[68]  D. Levinson,et al.  Some Properties of Flows at Freeway Bottlenecks , 2004 .

[69]  Markos Papageorgiou,et al.  Freeway ramp metering: an overview , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[70]  N. B. Goldstein,et al.  A decentralized control strategy for freeway regulation , 1982 .

[71]  Yasuo Asakura,et al.  Estimation of flow and density using probe vehicles with spacing measurement equipment , 2015 .

[72]  Oriol Serch,et al.  Exploring Link Covering and Node Covering Formulations of Detection Layout Problem , 2012 .

[73]  April Armstrong,et al.  Traffic Analysis Toolbox Volume XIII: Integrated Corridor Management Analysis, Modeling, and Simulation Guide , 2012 .

[74]  Philip J Tarnoff,et al.  Data Collection of Freeway Travel Time Ground Truth with Bluetooth Sensors , 2010 .

[75]  Chao Wei,et al.  Efficient Traffic State Estimation for Large-Scale Urban Road Networks , 2013, IEEE Transactions on Intelligent Transportation Systems.

[76]  Jaume Barceló,et al.  A Kalman Filter Approach for Exploiting Bluetooth Traffic Data When Estimating Time-Dependent OD Matrices , 2013, J. Intell. Transp. Syst..

[77]  Kun Zhou,et al.  A Multimodal Trip Planning System With Real-Time Traffic and Transit Information , 2012, J. Intell. Transp. Syst..

[78]  Alexandre M. Bayen,et al.  Hybrid Approach for Short-Term Traffic State and Travel Time Prediction on Highways , 2016 .

[79]  N. Geroliminis,et al.  Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings - eScholarship , 2007 .

[80]  Nikolaos Geroliminis,et al.  Empirical observations of capacity drop in freeway merges with ramp control and integration in a first-order model , 2013 .

[81]  Carlo Ratti,et al.  Understanding individual mobility patterns from urban sensing data: A mobile phone trace example , 2013 .

[82]  Oriol Serch,et al.  Robustness and Computational Efficiency of Kalman Filter Estimator of Time-Dependent Origin–Destination Matrices , 2013 .

[83]  Mario E. Magaña,et al.  Wireless Data Collection System for Real-Time Arterial Travel Time Estimates , 2011 .

[84]  Michael J. Cassidy,et al.  Relation between traffic density and capacity drop at three freeway bottlenecks , 2007 .

[85]  J. Hellendoorn,et al.  Reduction of area-wide emissions using an efficient model-based traffic control strategy , 2011, 2011 IEEE Forum on Integrated and Sustainable Transportation Systems.

[86]  Johan M Karlsson,et al.  Handover location accuracy for travel time estimation in GSM and UMTS , 2007 .

[87]  Fabio Ricciato,et al.  Exploiting Cellular Networks for Road Traffic Estimation: A Survey and a Research Roadmap , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[88]  Bart De Schutter,et al.  A Predictive Traffic Controller for Sustainable Mobility Using Parameterized Control Policies , 2012, IEEE Transactions on Intelligent Transportation Systems.

[89]  Nils-Hassan Quttineh,et al.  Surrogate-based optimization of cordon toll levels in congested traffic networks , 2016 .

[90]  Lídia Montero Mercadé,et al.  A DUE based bilevel optimization approach for the estimation of time sliced OD matrices , 2014 .

[91]  D. Gundlegard,et al.  Generating Road Traffic Information from Cellular Networks - New Possibilities in UMTS , 2006, 2006 6th International Conference on ITS Telecommunications.

[92]  Dirk Helbing,et al.  Reconstructing the spatio-temporal traffic dynamics from stationary detector data , 2002 .

[93]  G. Evensen Data Assimilation: The Ensemble Kalman Filter , 2006 .

[94]  Baher Abdulhai,et al.  Traffic Data Fusion Using SCAAT Kalman Filters , 2010 .

[95]  Ernesto Cipriani,et al.  An Adaptive Bi-Level Gradient Procedure for the Estimation of Dynamic Traffic Demand , 2014, IEEE Transactions on Intelligent Transportation Systems.

[96]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[97]  Stephen G. Ritchie,et al.  FREEWAY RAMP METERING USING ARTIFICIAL NEURAL NETWORKS , 1997 .