Trajectory data-based traffic flow studies: A revisit
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Rui Jiang | Zhengbing He | Xuesong Zhou | Xiqun Chen | Li Li | Zhengbing He | X. Chen | Li Li | R. Jiang | Xuesong Zhou
[1] Nanning Zheng,et al. Cognitive Cars: A New Frontier for ADAS Research , 2012, IEEE Transactions on Intelligent Transportation Systems.
[2] M. Cassidy,et al. Some traffic features at freeway bottlenecks , 1999 .
[3] Hesham Rakha,et al. Calibration Procedure for Gipps Car-Following Model , 2007 .
[4] X. Chen,et al. Measuring the Passenger Car Equivalent of Small Cars and SUVs on Rainy and Sunny Days , 2018 .
[5] Milan Krbalek,et al. Vehicular headways on signalized intersections: theory, models, and reality , 2014, 1403.7454.
[6] N. Chiabaut,et al. Wave Velocity Estimation through Automatic Analysis of Cumulative Vehicle Count Curves , 2011 .
[7] Jie Sun,et al. A car-following model considering asymmetric driving behavior based on long short-term memory neural networks , 2018, Transportation Research Part C: Emerging Technologies.
[8] Boris S. Kerner,et al. Breakdown in Traffic Networks: Fundamentals of Transportation Science , 2017 .
[9] Soyoung Ahn,et al. Microscopic traffic hysteresis in traffic oscillations : a behavioral perspective , 2012 .
[10] Cristian Arteaga,et al. Calibration of traffic flow models using a memetic algorithm , 2015 .
[11] Majid Sarvi,et al. Modelling heavy vehicle car-following behaviour in congested traffic conditions , 2014 .
[12] Vincenzo Punzo,et al. On the assessment of vehicle trajectory data accuracy and application to the Next Generation SIMulation (NGSIM) program data , 2011 .
[13] Zhiheng Li,et al. A method for estimating carbon dioxide emissions based on low frequency GPS trajectories , 2017, 2017 Chinese Automation Congress (CAC).
[14] Yanfeng Ouyang,et al. Characterization of Traffic Oscillation Propagation Under Nonlinear Car-Following Laws , 2011 .
[15] Jianping Wu,et al. The validation of a microscopic simulation model: a methodological case study , 2003 .
[16] Nanning Zheng,et al. Parallel testing of vehicle intelligence via virtual-real interaction , 2019, Science Robotics.
[17] H. Mahmassani,et al. Travel time estimation based on piecewise truncated quadratic speed trajectory , 2008 .
[18] Chang Liu,et al. How Much Data Are Enough? A Statistical Approach With Case Study on Longitudinal Driving Behavior , 2017, IEEE Transactions on Intelligent Vehicles.
[19] Hesham Rakha,et al. Procedure for Calibrating Gipps Car-Following Model , 2009 .
[20] Xiqun Chen,et al. A Traffic Breakdown Model Based on Queueing Theory , 2014 .
[21] Serge Hoogendoorn,et al. Calibration of microscopic traffic-flow models using multiple data sources , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[22] Li Li,et al. Long memory is important: A test study on deep-learning based car-following model , 2019, Physica A: Statistical Mechanics and its Applications.
[23] Lei Zhang,et al. Freeway Travel-Time Estimation Based on Temporal–Spatial Queueing Model , 2013, IEEE Transactions on Intelligent Transportation Systems.
[24] Majid Sarvi. Heavy commercial vehicles‐following behavior and interactions with different vehicle classes , 2011 .
[25] Serge P. Hoogendoorn,et al. Car-Following Behavior Analysis from Microscopic Trajectory Data , 2005 .
[26] Xiaogang Jin,et al. Departure headways at signalized intersections: A log-normal distribution model approach , 2009 .
[27] P. G. Michalopoulos,et al. Vehicle detection video through image processing: the Autoscope system , 1991 .
[28] Gordon F. Newell,et al. A simplified car-following theory: a lower order model , 2002 .
[29] Agachai Sumalee,et al. A cross-entropy method and probabilistic sensitivity analysis framework for calibrating microscopic traffic models , 2016 .
[30] Benjamin Coifman,et al. Extended bottlenecks, the fundamental relationship, and capacity drop on freeways , 2011 .
[31] H. M. Zhang,et al. A stochastic wave propagation model , 2008 .
[32] Paolo Santi,et al. The Car as an Ambient Sensing Platform , 2017, Proc. IEEE.
[33] Constantinos Antoniou,et al. Online calibration for microscopic traffic simulation and dynamic multi-step prediction of traffic speed , 2016 .
[34] Bing-Hong Wang,et al. An asymmetric full velocity difference car-following model , 2008 .
[35] E. Montroll,et al. Traffic Dynamics: Studies in Car Following , 1958 .
[36] Alexandre Bernardino,et al. Detection and classification of highway lanes using vehicle motion trajectories , 2006, IEEE Transactions on Intelligent Transportation Systems.
[37] Dirk Helbing,et al. Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts , 2010, 1004.5545.
[38] Peter R. Stopher,et al. Review of GPS Travel Survey and GPS Data-Processing Methods , 2014 .
[39] Martin Treiber,et al. Calibrating Car-Following Models by Using Trajectory Data , 2008, 0803.4063.
[40] Christopher Monterola,et al. Asymmetric optimal-velocity car-following model , 2015 .
[41] H. M. Zhang. A mathematical theory of traffic hysteresis , 1999 .
[42] Ghim Ping Ong,et al. Spatial-temporal inference of urban traffic emissions based on taxi trajectories and multi-source urban data , 2018, Transportation Research Part C: Emerging Technologies.
[43] Joe Lee,et al. Characterizing and Modeling Observed Lane-Changing Behavior: Lane-Vehicle-Based Microscopic Simulation on Urban Street Network , 2000 .
[44] Zhengbing He,et al. Mapping to Cells: A Simple Method to Extract Traffic Dynamics from Probe Vehicle Data , 2017, Comput. Aided Civ. Infrastructure Eng..
[45] Yilmaz Hatipkarasulu,et al. Results of Car Following Analyses Using Global Positioning System , 2000 .
[46] Soyoung Ahn,et al. Comparisons of Speed-Spacing Relations under General Car following versus Lane Changing , 2008 .
[47] Yanfeng Ouyang,et al. Prediction and Field Validation of Traffic Oscillation Propagation Under Nonlinear Car-Following Laws , 2012 .
[48] Vincenzo Punzo,et al. “No Free Lunch” Theorems Applied to the Calibration of Traffic Simulation Models , 2014, IEEE Transactions on Intelligent Transportation Systems.
[49] Zhiyong Cui,et al. Real-Time Bidirectional Traffic Flow Parameter Estimation From Aerial Videos , 2017, IEEE Transactions on Intelligent Transportation Systems.
[50] Peter Wagner,et al. Calibration and Validation of Microscopic Models of Traffic Flow , 2005 .
[51] Afshin Shariat Mohaymany,et al. A copula-based estimation of distribution algorithm for calibration of microscopic traffic models , 2019, Transportation Research Part C: Emerging Technologies.
[52] Meead Saberi,et al. Hysteresis and Capacity Drop Phenomena in Freeway Networks , 2013 .
[53] Michalis E. Zervakis,et al. A survey of video processing techniques for traffic applications , 2003, Image Vis. Comput..
[54] Peter Wagner. Empirical Description of Car-Following , 2005 .
[55] Osama Masoud,et al. Tracking all traffic: computer vision algorithms for monitoring vehicles, individuals, and crowds , 2005, IEEE Robotics & Automation Magazine.
[56] Victor C. M. Leung,et al. Reliable Traffic Density Estimation in Vehicular Network , 2018, IEEE Transactions on Vehicular Technology.
[57] Li Li,et al. Vehicle headway modeling and its inferences in macroscopic/microscopic traffic flow theory: A survey , 2017 .
[58] Xiqun Chen,et al. Characterising scattering features in flow–density plots using a stochastic platoon model , 2014 .
[59] Vladimir Livshits,et al. Generating a Vehicle Trajectory Database from Time-Lapse Aerial Photography , 2016 .
[60] Mao-Bin Hu,et al. Traffic Experiment Reveals the Nature of Car-Following , 2014, PloS one.
[61] Ziyou Gao,et al. Empirical analysis and simulation of the concave growth pattern of traffic oscillations , 2016 .
[62] Bin Jia,et al. Microscopic driving theory with oscillatory congested states: Model and empirical verification , 2014, 1412.0445.
[63] Peter Wagner,et al. Calibration and Validation of Microscopic Traffic Flow Models , 2004, SimVis.
[64] Shuangshuang Han,et al. From Software-Defined Vehicles to Self-Driving Vehicles: A Report on CPSS-Based Parallel Driving , 2019, IEEE Intelligent Transportation Systems Magazine.
[65] R. E. Wilson,et al. Mechanisms for spatio-temporal pattern formation in highway traffic models , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[66] Jorge A. Laval,et al. A parsimonious model for the formation of oscillations in car-following models , 2014 .
[67] Li Li,et al. Risky Driver Recognition Based on Vehicle Speed Time Series , 2018, IEEE Transactions on Human-Machine Systems.
[68] Dongpu Cao,et al. A situation-aware collision avoidance strategy for car-following , 2018, IEEE/CAA Journal of Automatica Sinica.
[69] Mohammed A. Quddus,et al. Examining lane change gap acceptance, duration and impact using naturalistic driving data , 2019, Transportation Research Part C: Emerging Technologies.
[70] Dirk Helbing,et al. Memory effects in microscopic traffic models and wide scattering in flow-density data. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[71] Bin Ran,et al. A Novel Car-Following Control Model Combining Machine Learning and Kinematics Models for Automated Vehicles , 2019, IEEE Transactions on Intelligent Transportation Systems.
[72] Mark R. McCord,et al. Roadway traffic monitoring from an unmanned aerial vehicle , 2006 .
[73] Wanjing Ma,et al. Trajectory analysis for on-demand services: A survey focusing on spatial-temporal demand and supply patterns , 2019, Transportation Research Part C: Emerging Technologies.
[74] H. J. Van Zuylen,et al. Bayesian Calibration of Car-Following Models , 2010, CTS 2009.
[75] Soyoung Ahn,et al. Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform , 2011 .
[76] Ashish Bhaskar,et al. A pattern recognition algorithm for assessing trajectory completeness , 2018, Transportation Research Part C: Emerging Technologies.
[77] Serge P. Hoogendoorn,et al. Generic Calibration Framework for Joint Estimation of Car-Following Models by Using Microscopic Data , 2010 .
[78] Femke Kessels,et al. Traffic Flow Modelling , 2018, EURO Advanced Tutorials on Operational Research.
[79] Marcello Montanino,et al. Making NGSIM Data Usable for Studies on Traffic Flow Theory , 2013 .
[80] Hongchao Liu,et al. Analysis of asymmetric driving behavior using a self-learning approach , 2013 .
[81] Ning Zhu,et al. A Jam-Absorption Driving Strategy for Mitigating Traffic Oscillations , 2017, IEEE Transactions on Intelligent Transportation Systems.
[82] Dongpu Cao,et al. Parallel driving in CPSS: a unified approach for transport automation and vehicle intelligence , 2017, IEEE/CAA Journal of Automatica Sinica.
[83] Jiang Rui,et al. On the Intrinsic Concordance between the Wide Scattering Feature of Synchronized Flow and the Empirical Spacing Distributions , 2010 .
[84] Emmanouil N. Barmpounakis,et al. On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment , 2020 .
[85] Xiang Zhang,et al. A Survey on Platoon-Based Vehicular Cyber-Physical Systems , 2016, IEEE Communications Surveys & Tutorials.
[86] Christine Buisson,et al. Estimating Individual Speed-Spacing Relationship and Assessing Ability of Newell's Car-Following Model to Reproduce Trajectories , 2008 .
[87] Yanfeng Ouyang,et al. Calibration of nonlinear car-following laws for traffic oscillation prediction , 2015 .
[88] Wei Guo,et al. Compare linear interpolation and adaptive smoothing methods on traffic flow information reconstruction , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.
[89] Jorge A. Laval,et al. Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model , 2008 .
[90] Soyoung Ahn,et al. Verification of a simplified car-following theory , 2004 .
[91] William R. McShane,et al. A review of pedestrian safety models for urban areas in Low and Middle Income Countries , 2016 .
[92] Carlos F. Daganzo,et al. Fundamentals of Transportation and Traffic Operations , 1997 .
[93] Osama Masoud,et al. A vision-based approach to collision prediction at traffic intersections , 2005, IEEE Transactions on Intelligent Transportation Systems.
[94] Ann Williamson,et al. The link between fatigue and safety. , 2011, Accident; analysis and prevention.
[95] Majid Sarvi,et al. Study of Mandatory Lane Change Execution Behavior Model for Heavy Vehicles and Passenger Cars , 2016 .
[96] Soyoung Ahn,et al. On the periodicity of traffic oscillations and capacity drop : the role of driver characteristics , 2014 .
[97] Zhe Sun,et al. Simultaneous estimation of states and parameters in Newell’s simplified kinematic wave model with Eulerian and Lagrangian traffic data , 2017 .
[98] Wanjing Ma,et al. Revisiting distribution model of departure headways at signalised intersections , 2017 .
[99] Motohiro Fujita,et al. Car-following behavior with instantaneous driver–vehicle reaction delay: A neural-network-based methodology , 2013 .
[100] Ludovic Leclercq,et al. From heterogeneous drivers to macroscopic patterns in congestion , 2010 .
[101] Marcello Montanino,et al. Do We Really Need to Calibrate All the Parameters? Variance-Based Sensitivity Analysis to Simplify Microscopic Traffic Flow Models , 2015, IEEE Transactions on Intelligent Transportation Systems.
[102] Serge P. Hoogendoorn,et al. Capacity Reduction at Incidents , 2008 .
[103] Martin Treiber,et al. Reconstructing the Traffic State by Fusion of Heterogeneous Data , 2009, Comput. Aided Civ. Infrastructure Eng..
[104] Feng Zhu,et al. An Optimal Estimation Approach for the Calibration of the Car-Following Behavior of Connected Vehicles in a Mixed Traffic Environment , 2017, IEEE Transactions on Intelligent Transportation Systems.
[105] Carlos F. Daganzo,et al. In Traffic Flow, Cellular Automata = Kinematic Waves , 2004 .
[106] Hussein Dia,et al. Neural Agent Car-Following Models , 2007, IEEE Transactions on Intelligent Transportation Systems.
[107] B.S. Kerner,et al. Traffic state detection with floating car data in road networks , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..
[108] Benjamin Coifman,et al. A critical evaluation of the Next Generation Simulation (NGSIM) vehicle trajectory dataset , 2017 .
[109] Mashrur Chowdhury,et al. Review of Microscopic Lane-Changing Models and Future Research Opportunities , 2013, IEEE Transactions on Intelligent Transportation Systems.
[110] Ioannis Kaparias,et al. A quantitative approach to the behavioural analysis of drivers in highways using particle filtering , 2015, Transportation Planning and Technology.
[111] Martin Treiber,et al. Microscopic Calibration and Validation of Car-Following Models – A Systematic Approach , 2013, 1403.4990.
[112] Baher Abdulhai,et al. Genetic Algorithm-Based Optimization Approach and Generic Tool for Calibrating Traffic Microscopic Simulation Parameters , 2002 .
[113] Bin Ran,et al. Large-Scale Freeway Network Traffic Monitoring: A Map-Matching Algorithm Based on Low-Logging Frequency GPS Probe Data , 2011, J. Intell. Transp. Syst..
[114] Keqiang Li,et al. A Vehicle Type Dependent Car-following Model Based on Naturalistic Driving Study , 2019 .
[115] Dirk Helbing,et al. Reconstructing the spatio-temporal traffic dynamics from stationary detector data , 2002 .
[116] S.P. Hoogendoorn,et al. A general framework for calibrating and comparing car-following models , 2015 .
[117] Kazuya Takeda,et al. Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification , 2007, Proceedings of the IEEE.
[118] Meng Li,et al. Connected vehicle-based red-light running prediction for adaptive signalized intersections , 2018, J. Intell. Transp. Syst..
[119] Y. Ouyang,et al. Measurement and estimation of traffic oscillation properties , 2010 .
[120] Hao Wang,et al. Experimental Features and Characteristics of Speed Dispersion in Urban Freeway Traffic , 2007 .
[121] Majid Sarvi,et al. Modeling the Lane-Changing Execution of Multiclass Vehicles under Heavy Traffic Conditions , 2010 .
[122] G. F. Newell. THEORIES OF INSTABILITY IN DENSE HIGHWAY TRAFFIC , 1962 .
[123] Majid Sarvi,et al. New Car-Following Model considering Impacts of Multiple Lead Vehicle Types , 2013 .
[124] Ali Ghaffari,et al. Improved adaptive neuro fuzzy inference system car-following behaviour model based on the driver–vehicle delay , 2014 .
[125] Ikki Kim,et al. Identifying driver heterogeneity in car-following based on a random coefficient model , 2013 .
[126] Mark D. Hickman,et al. Methods of analyzing traffic imagery collected from aerial platforms , 2003, IEEE Trans. Intell. Transp. Syst..
[127] Liang Zheng,et al. A simple nonparametric car-following model driven by field data , 2015 .
[128] Serge P. Hoogendoorn,et al. Heterogeneity In Car-Following Behavior: Theory And Empirics , 2011 .
[129] Soyoung Ahn,et al. A method to account for non-steady state conditions in measuring traffic hysteresis , 2013 .
[130] Pitu B. Mirchandani,et al. Airborne Traffic Flow Data and Traffic Management , 2008 .
[131] Li Li,et al. Adaptive Rolling Smoothing With Heterogeneous Data for Traffic State Estimation and Prediction , 2019, IEEE Transactions on Intelligent Transportation Systems.
[132] Ludovic Leclercq,et al. A mechanism to describe the formation and propagation of stop-and-go waves in congested freeway traffic , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[133] Dongpu Cao,et al. Retrieving Common Discretionary Lane Changing Characteristics From Trajectories , 2018, IEEE Transactions on Vehicular Technology.
[134] Laurence R. Rilett,et al. Analysis of Distribution and Calibration of Car-Following Sensitivity Parameters in Microscopic Traffic Simulation Models , 2004 .
[135] Yajie Zou,et al. Constructing a bivariate distribution for freeway speed and headway data , 2014 .
[136] Tieniu Tan,et al. Traffic accident prediction using 3-D model-based vehicle tracking , 2004, IEEE Transactions on Vehicular Technology.
[137] Soyoung Ahn,et al. A behavioural car-following model that captures traffic oscillations , 2012 .
[138] H. Christopher Frey,et al. Integrating a simplified emission estimation model and mesoscopic dynamic traffic simulator to efficiently evaluate emission impacts of traffic management strategies , 2015 .
[139] Ichiro Masaki,et al. Machine-Vision Systems for Intelligent Transportation Systems , 1998, IEEE Intell. Syst..
[140] Mashrur Chowdhury,et al. Improving the Efficacy of Car-Following Models With a New Stochastic Parameter Estimation and Calibration Method , 2015, IEEE Transactions on Intelligent Transportation Systems.
[141] L. Craig Davis,et al. Introduction to Modern Traffic Flow Theory and Control: The Long Road to Three-Phase Traffic Theory , 2009 .
[142] Xiao Qi,et al. Simultaneous modeling of car-following and lane-changing behaviors using deep learning , 2019, Transportation Research Part C: Emerging Technologies.
[143] H. Christopher Frey,et al. Measurement and Evaluation of Real-World Speed and Acceleration Activity Envelopes for Light-Duty Vehicles , 2015 .
[144] Xiaobo Qu,et al. A recurrent neural network based microscopic car following model to predict traffic oscillation , 2017 .
[145] Prashant Doshi,et al. Merging in Congested Freeway Traffic Using Multipolicy Decision Making and Passive Actor-Critic Learning , 2019, IEEE Transactions on Intelligent Vehicles.
[146] Xuesong Zhou,et al. Method for investigating intradriver heterogeneity using vehicle trajectory data: A Dynamic Time Warping approach , 2015 .
[147] Mallikarjuna Chunchu,et al. Trajectory reconstruction using locally weighted regression: a new methodology to identify the optimum window size and polynomial order , 2018 .
[148] Haris N. Koutsopoulos,et al. Estimation of Vehicle Trajectories with Locally Weighted Regression , 2007 .
[149] Robert L. Bertini,et al. Some observed queue discharge features at a freeway bottleneck , 2002 .
[150] Li Li,et al. Urban traffic signal control with connected and automated vehicles: A survey , 2019, Transportation Research Part C: Emerging Technologies.
[151] Benjamin Coifman,et al. Estimating travel times and vehicle trajectories on freeways using dual loop detectors , 2002 .
[152] Hani S. Mahmassani,et al. Life in the Fast Lane , 2009 .
[153] Kaan Ozbay,et al. New Calibration Methodology for Microscopic Traffic Simulation Using Enhanced Simultaneous Perturbation Stochastic Approximation Approach , 2009 .
[154] Rui Jiang,et al. Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow , 2016 .
[155] Danjue Chen,et al. Capacity-drop at extended bottlenecks: Merge, diverge, and weave , 2018 .
[156] Hjp Harry Timmermans,et al. Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data , 2016 .
[157] Meixin Zhu,et al. Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study , 2018, Transportation Research Part C: Emerging Technologies.
[158] Alejandra Medina Flintsch,et al. A rule-based neural network approach to model driver naturalistic behavior in traffic , 2013 .
[159] Xiqun Chen,et al. Phase Diagram Analysis Based on a Temporal-Spatial Queueing Model , 2012, IEEE Transactions on Intelligent Transportation Systems.
[160] Zhengbing He,et al. Constructing spatiotemporal speed contour diagrams: using rectangular or non-rectangular parallelogram cells? , 2019 .
[161] Jun Chen,et al. Using Trajectory Data to Analyze Intradriver Heterogeneity in Car-Following , 2010 .
[162] Soyoung Ahn,et al. The effects of lane-changing on the immediate follower : anticipation, relaxation, and change in driver characteristics , 2013 .
[163] G. F. Newell. A simplified theory of kinematic waves in highway traffic, part I: General theory , 1993 .
[164] Tom V. Mathew,et al. Vehicle-type dependent car-following model for heterogeneous traffic conditions , 2011 .
[165] Liang Zheng,et al. Empirical validation of vehicle type-dependent car-following heterogeneity from micro- and macro-viewpoints , 2019 .
[166] S. P. Hoogendoorn,et al. Piecewise Inverse Speed Correction by Using Individual Travel Times , 2008 .
[167] Ning Jia,et al. Estimating Carbon Dioxide Emissions of Freeway Traffic: A Spatiotemporal Cell-Based Model , 2020, IEEE Transactions on Intelligent Transportation Systems.
[168] X. Chen,et al. A global optimization algorithm for trajectory data based car-following model calibration , 2016 .
[169] Bin Jia,et al. Experimental and empirical investigations of traffic flow instability , 2018, Transportation Research Part C: Emerging Technologies.
[170] Zuduo Zheng,et al. Recent developments and research needs in modeling lane changing , 2014 .
[171] Jorge A. Laval,et al. Effects of Merging and Diverging on Freeway Traffic Oscillations , 2010 .
[172] Carlos F. Daganzo,et al. A Simple Traffic Analysis Procedure , 1997 .
[173] Xiaopeng Li,et al. Stop-and-go traffic analysis: Theoretical properties, environmental impacts and oscillation mitigation , 2014 .
[174] Soyoung Ahn,et al. Passing Rates to Measure Relaxation and Impact of Lane‐Changing in Congestion , 2011, Comput. Aided Civ. Infrastructure Eng..
[175] Alexander Skabardonis,et al. Microscopic fundamental relationships between vehicle speed and spacing in view of asymmetric traffic theory , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).
[176] Fei-Yue Wang,et al. Capturing Car-Following Behaviors by Deep Learning , 2018, IEEE Transactions on Intelligent Transportation Systems.
[177] Maria Laura Delle Monache,et al. Tracking vehicle trajectories and fuel rates in phantom traffic jams: Methodology and data , 2019, Transportation Research Part C: Emerging Technologies.
[178] Lutz Eckstein,et al. The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems , 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).
[179] Da Yang,et al. Modeling and Analysis of Lateral Driver Behavior in Lane-Changing Execution , 2015 .
[180] Yanfeng Ouyang,et al. Traffic state and emission estimation for urban expressways based on heterogeneous data , 2017 .
[181] Jianfeng Zheng,et al. A probabilistic stationary speed–density relation based on Newell’s simplified car-following model , 2014 .
[182] Benjamin Coifman,et al. Resurrecting the Lost Vehicle Trajectories of Treiterer and Myers with New Insights into a Controversial Hysteresis , 2018, Transportation Research Record: Journal of the Transportation Research Board.
[183] M. Treiber,et al. Estimating Acceleration and Lane-Changing Dynamics from Next Generation Simulation Trajectory Data , 2008, 0804.0108.
[184] Xuesong Zhou,et al. Traffic state estimation and uncertainty quantification based on heterogeneous data sources: A three detector approach , 2013 .
[185] Soyoung Ahn,et al. Applications of wavelet transform for analysis of freeway traffic : bottlenecks, transient traffic, and traffic oscillations , 2011 .
[186] Martin Treiber,et al. Validation of traffic flow models with respect to the spatiotemporal evolution of congested traffic patterns , 2012 .
[187] Gaetano Fusco,et al. Artificial Neural Network Models for Car Following: Experimental Analysis and Calibration Issues , 2014, J. Intell. Transp. Syst..
[188] Tarek Sayed,et al. Large-Scale Automated Analysis of Vehicle Interactions and Collisions , 2010 .
[189] W. F. Adams. Road Traffic Considered as a Random Series , 1950 .
[190] Silviu-Iulian Niculescu,et al. Stability of car following with human memory effects and automatic headway compensation , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[191] Boris S. Kerner,et al. Aerial observations of moving synchronized flow patterns in over-saturated city traffic , 2018 .
[192] Xiaoliang Ma,et al. A model identification scheme for driver-following dynamics in road traffic , 2013 .
[193] Sahar Ghanipoor Machiani,et al. Safety surrogate histograms (SSH): A novel real-time safety assessment of dilemma zone related conflicts at signalized intersections. , 2016, Accident; analysis and prevention.
[194] Scott A. Brandt,et al. Visual tracking for intelligent vehicle-highway systems , 1996 .
[195] Xiqun Chen,et al. Asymmetric stochastic Tau Theory in car-following , 2013 .
[196] Bin Jia,et al. A data-driven lane-changing model based on deep learning , 2019, Transportation Research Part C: Emerging Technologies.
[197] Hwasoo Yeo,et al. An empirical study on the traffic state evolution and stop-and-go traffic development on freeways , 2016 .
[198] Hesham Rakha,et al. Application of Naturalistic Driving Data to Modeling of Driver Car-Following Behavior , 2013 .
[199] Ludovic Leclercq,et al. Relaxation Phenomenon after Lane Changing , 2007 .
[200] Praveen Edara,et al. Situation assessment and decision making for lane change assistance using ensemble learning methods , 2015, Expert Syst. Appl..
[201] Haixin Wang,et al. Empirical evidence and stability analysis of the linear car-following model with gamma-distributed memory effect , 2016 .
[202] David J. Lovell,et al. Hardware and software for collecting microscopic trajectory data on naturalistic driving behavior , 2017, J. Intell. Transp. Syst..
[203] Yunfeng Ai,et al. Driver Lane Change Intention Inference for Intelligent Vehicles: Framework, Survey, and Challenges , 2019, IEEE Transactions on Vehicular Technology.
[204] Jorge A. Laval. Hysteresis in traffic flow revisited: An improved measurement method , 2011 .
[205] Charisma F. Choudhury,et al. Transferability of Car-Following Models Between Driving Simulator and Field Traffic , 2017 .
[206] H. Michael Zhang,et al. Calibration of Microsimulation with Heuristic Optimization Methods , 2007 .
[207] J Treiterer,et al. THE HYSTERESIS PHENOMENON IN TRAFFIC FLOW , 1974 .
[208] Ludovic Leclercq,et al. Fundamental Diagram Estimation Through Passing Rate Measurements in Congestion , 2009, IEEE Transactions on Intelligent Transportation Systems.
[209] Bongsoo Son,et al. A method for measuring accurate traffic density by aerial photography , 2015 .
[210] Meixin Zhu,et al. Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning , 2018, Transportation Research Part C: Emerging Technologies.
[211] Constantinos Antoniou,et al. Towards data-driven car-following models , 2015 .
[212] Sanhita Das,et al. Multivariate analysis of microscopic traffic variables using copulas in staggered car-following conditions , 2018 .
[213] Keith Redmill,et al. Collecting ambient vehicle trajectories from an instrumented probe vehicle: High quality data for microscopic traffic flow studies , 2016 .
[214] Sergio A. Velastin,et al. A Review of Computer Vision Techniques for the Analysis of Urban Traffic , 2011, IEEE Transactions on Intelligent Transportation Systems.
[215] Meng Li,et al. Emission Mitigation via Longitudinal Control of Intelligent Vehicles in a Congested Platoon , 2015, Comput. Aided Civ. Infrastructure Eng..
[216] Peng Hao,et al. Trajectory-based vehicle energy/emissions estimation for signalized arterials using mobile sensing data , 2015 .
[217] Jinjun Tang,et al. Real-Time Traffic Flow Parameter Estimation From UAV Video Based on Ensemble Classifier and Optical Flow , 2019, IEEE Transactions on Intelligent Transportation Systems.
[218] Yajie Zou,et al. A copula-based approach to accommodate the dependence among microscopic traffic variables , 2016 .
[219] J. W. C. van Lint,et al. Empirical Evaluation of New Robust Travel Time Estimation Algorithms , 2010 .
[220] Yi Zhang,et al. A Markov Model for Headway/Spacing Distribution of Road Traffic , 2010, IEEE Transactions on Intelligent Transportation Systems.
[221] Tomer Toledo,et al. Modeling Duration of Lane Changes , 2007 .
[222] Ziyou Gao,et al. Experimental study and modeling of car-following behavior under high speed situation , 2018, Transportation Research Part C: Emerging Technologies.
[223] Daiheng Ni,et al. Trajectory Reconstruction for Travel Time Estimation , 2008, J. Intell. Transp. Syst..
[224] Majid Sarvi,et al. Lane-Changing Decision Model for Heavy Vehicle Drivers , 2012, J. Intell. Transp. Syst..
[225] Chao Wang,et al. The Effect of Lane-Change Maneuvers on a Simplified Car-Following Theory , 2008, IEEE Transactions on Intelligent Transportation Systems.
[226] Bin Ran,et al. Dangerous driving behavior detection using video-extracted vehicle trajectory histograms , 2017, J. Intell. Transp. Syst..
[227] Tarek Sayed,et al. A framework for automated road-users classification using movement trajectories , 2013 .
[228] Marcello Montanino,et al. Can Results of car-following Model Calibration Based on Trajectory Data be Trusted? , 2012 .
[229] Mao-Bin Hu,et al. Understanding the structure of hyper-congested traffic from empirical and experimental evidences , 2015 .
[230] Xiqun Chen,et al. Bayesian network for red-light-running prediction at signalized intersections , 2018, J. Intell. Transp. Syst..
[231] Xuesong Zhou,et al. Estimating risk effects of driving distraction: a dynamic errorable car-following model , 2015 .
[232] Weihua Zhuang,et al. Stochastic Analysis of a Single-Hop Communication Link in Vehicular Ad Hoc Networks , 2014, IEEE Transactions on Intelligent Transportation Systems.
[233] Ronghui Liu,et al. The principles of calibrating traffic microsimulation models , 2008 .
[234] Mahmoud Mesbah,et al. Impact of heavy vehicles on surrounding traffic characteristics , 2015 .
[235] Qi Wang,et al. Investigation of Discretionary Lane-Change Characteristics Using Next-Generation Simulation Data Sets , 2014, J. Intell. Transp. Syst..
[236] Liu Yang,et al. Exploring the Relationship between Electroencephalography (EEG) and Ordinary Driving Behavior: A Simulated Driving Study , 2018, Transportation Research Record: Journal of the Transportation Research Board.
[237] Wei Ni,et al. An extended generalized filter algorithm for urban expressway traffic time estimation based on heterogeneous data , 2016, J. Intell. Transp. Syst..
[238] Soyoung Ahn,et al. Car-Following and Lane-Changing Behavior Involving Heavy Vehicles: , 2016 .