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Modeling stochastic traffic behaviors at the microscopic level, such as car-following and lane-changing, is a crucial task to understand the interactions between individual vehicles in traffic streams.
Car-following behavior analysis from microscopic trajectory data
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Toledo, T., Koutsopoulos, H.N., Ben-Akiva, M.E., 2003 · 2003
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Car-following behavior with instantaneous driver–vehicle reaction delay: A neural-network-based methodology
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Toward an integrated car-following and lane-changing model based on neural-fuzzy approach, in: Helsinki summer workshop
Ma, X., 2004 · 2004
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Modelling vehicle interactions in microscopic simulation of merging and weaving
Hidas, P., 2005 · 2005
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Car following theory with lateral discomfort
Gunay, B., 2007 · 2007
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Zheng, J., Suzuki, K., Fujita, M., 2013 · 2013
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Artificial neural network models for car following: Experimental analysis and calibration issues
Colombaroni, C., Fusco, G., 2014 · 2014
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Calibration of an interrupted traffic flow system using ngsim trajectory data sets, in: Proceeding of the 11th World Congress on Intelligent Control and Automation, IEEE. pp. 4887–4892
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Microscopic calibration and validation of car-following models–a systematic approach
Treiber, M., Kesting, A., 2014 · 2014
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A state-of-the-art review of car-following models with particular considerations of heavy vehicles
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Towards data-driven car-following models
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Wilson, A.G., Hu, Z., Salakhutdinov, R., Xing, E.P., 2016 · 2016
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Microscopic car-following model for autonomous vehicles using reinforcement learning, in: Symposium on Innovations in Traffic Flow Theory and Characteristics and TFT Midyear Meeting, p. 3
Zhou, M., Qu, X., 2016 · 2016
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Hao, S., Yang, L., Shi, Y., 2017 · 2017
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A recurrent neural network based microscopic car following model to predict traffic oscillation
Zhou, M., Qu, X., Li, X., 2017 · 2017
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Parametric study of microscopic two-dimensional traffic flow models: A literature review
Mahapatra, G., Maurya, A.K., Chakroborty, P., 2018 · 2018
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Physics-informed machine learning for inorganic scintillator discovery
Pilania, G., McClellan, K.J., Stanek, C.R., Uberuaga, B.P., 2018 · 2018
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Multi-output gaussian processes for crowdsourced traffic data imputation
Rodrigues, F., Henrickson, K., Pereira, F.C., 2018 · 2018
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Heteroscedastic gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data
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Physics-informed machine learning approach for augmenting turbulence models: A comprehensive framework
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Human-like autonomous car-following model with deep reinforcement learning
Zhu, M., Wang, X., Wang, Y., 2018 · 2018
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Towards an integrated longitudinal and lateral movement data-driven model for mixed traffic
Papathanasopoulou, V., Antoniou, C., 2019 · 2019
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Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Raissi, M., Perdikaris, P., Karniadakis, G.E., 2019 · 2019
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Wang, J.X., Huang, J., Duan, L., Xiao, H., 2019 · 2019
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Memory, attention and prediction: a deep learning architecture for car-following
Wu, Y., Tan, H., Chen, X., Ran, B., 2019 · 2019
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Zhang, D., Lu, L., Guo, L., Karniadakis, G.E., 2019 · 2019
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A two-dimensional car-following model for two-dimensional traffic flow problems
Delpiano, R., Herrera, J.C., Laval, J., Coeymans, J.E., 2020 · 2020
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Simulation strategies for mixed traffic conditions: A review of car-following models and simulation frameworks
Matcha, B.N., Namasivayam, S.N., Hosseini Fouladi, M., Ng, K., Sivanesan, S., Noum, E., Yong, S., 2020 · 2020
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Posterior regularization for structured latent variable models
Ganchev, K., Gillenwater, J., Taskar, B., et al., 2010 · 2049
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Calibrating car-following models by using trajectory data: Methodological study
Kesting, A., Treiber, M., 2008 · 2088
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