Bibliography
Andersen HK, Grush R (2009) A brief history of time-consciousness: historical precursors to James and Husserl. J Hist Philos 47(2):277–307
Andrews K (2015) The animal mind: an introduction to the philosophy of animal cognition. Routledge, Taylor & Francis Group, London
Anonymous (E Robert Kelly) (1882) The alternative: a study in psychology. Macmillan and Co., London
Asai Y, Tasaka Y, Nomura K, Nomura T, Casadio M, Morasso P (2009) A model of postural control in quiet standing: robust compensation of delay-induced instability using intermittent activation of feedback control. PLoS One 4(7):e6169 (1–14)
Asai Y, Tateyama S, Nomura T (2013) Learning an intermittent control strategy for postural balancing using an EMG-based human-computer interface. PLoS One 8(5):e62, 956 (19 pages)
Balasubramaniam R (2013) On the control of unstable objects: the dynamics of human stick balancing. In: Richardson M, Riley M, Shockley K (eds) Progress in motor control: neural, computational and dynamic approaches. Springer Science + Business Media, New York, pp 149–168
Bando M, Hasebe K, Nakayama A, Shibata A, Sugiyama Y (1995) Dynamical model of traffic congestion and numerical simulation. Phys Rev E 51:10351042
Bando M, Hasebe K, Nakanishi K, Nakayama A (1998) Analysis of optimal velocity model with explicit delay. Phys Rev E 58:5429–5435
Bernstein NA (1935) The problem of interrelation between coordination and localization. Arch Biol Sci 38:1–35, (in Russian)
Bifulco GN, Pariota L, Brackstione M, Mcdonald M (2013) Driving behaviour models enabling the simulation of advanced driving assistance systems: revisiting the action point paradigm. Transp Res C Emerg Technol 36:352–366. https://doi.org/10.1016/j.trc.2013.09.009
Bottaro A, Yasutake Y, Nomura T, Casadio M, Morasso P (2008) Bounded stability of the quiet standing posture: an intermittent control model. Hum Mov Sci 27(3):473–495
Bourne C (2006) A future for presentism. Oxford University Press, Oxford, UK
Brackstone M, McDonald M (1999) Car-following: a historical review. Transport Res F Traffic Psychol Behav 2(4):181–196
Carter P, Christiansen PL, Gaididei YB, Gorria C, Sand-stede B, Sǿrensen MP, Starke J (2014) Multijam solutions in traffic models with velocity-dependent driver strategies. SIAM J Appl Math 74(6):1895–1918
Castellano C, Fortunato S, Loreto V (2009) Statistical physics of social dynamics. Rev Mod Phys 81(2):591–646
Chowdhury D, Santen L, Schadschneider A (2000) Statistical physics of vehicular traffic and some related systems. Phys Rep 329(4–6):199–329
Clark A (2013) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav Brain Sci 36(03):181–204. https://doi.org/10.1017/S0140525X12000477
Edie LC (1961) Car-following and steady-state theory for noncongested traffic. Oper Res 9(1):66–76. https://doi.org/10.1287/opre.9.1.66
Elliott MA, Giersch A (2016) What happens in a moment. Front Psychol 6:Article 1905 (7 pages). https://doi.org/10.3389/fpsyg.2015.01905
Fancher P, Haugen J, Buonarosa ML, Bareket Z, Bogard SE, Hagan MR, Sayer JR, Ervin RD (1998) Intelligent cruise control field operational test. Final report. Volume I: Technical report. Report number: UMTRI-98-17, Report number: DOT/HS 808 849. University of Michigan, Transportation Research Institute, Ann Arbor
Friston K, Rigoli F, Ognibene D, Mathys C, Fitzgerald T, Pezzulo G (2015) Active inference and epistemic value. Cogn Neurosci 6(4):187–214. https://doi.org/10.1080/17588928.2015.1020053
Gaididei YB, Gorria C, Berkemer R, Kawamoto A, Shiga T, Christiansen PL, Sǿrensen MP, Starke J (2013) Controlling traffic jams by time modulating the safety distance. Phys Rev E 88(4):042,803
Gallagher S, Zahavi D (2012) The phenomenological mind: an introduction to philosophy of mind and cognitive science, 2nd edn. Routledge, Taylor & Francis Group, London
Gawthrop P, Loram I, Lakie M, Gollee H (2011) Intermittent control: a computational theory of human control. Biol Cybern 104(1–2):31–51
Gazis DC, Herman R, Potts RB (1959) Car-following theory of steady-state traffic flow. Oper Res 7(4):499–505. https://doi.org/10.1287/opre.7.4.499
Gazis DC, Herman R, Rothery RW (1961) Nonlinear follow-the-leader models of traffic flow. Oper Res 9(4):545–567
Gurusinghe GS, Nakatsuji T, Azuta Y, Ranjitkar P, Tanaboriboon Y (2002) Multiple car-following data with real-time kinematic global positioning system. Transp Res Rec J Transp Res Board 1802(1):166–180
Haken H (2009a) Synergetics: basic concepts. In: Meyers RA (ed) Encyclopedia of complexity and systems science. Springer Science+Buisiness Media, New York, pp 8926–8946
Haken H (2009b) Synergetics, introduction to. In: Meyers RA (ed) Encyclopedia of complexity and systems science. Springer Science+Buisiness Media, New York, pp 8946–8948
Hawley K (2015) Temporal parts In: Zalta EN (ed) The Stanford encyclopedia of philosophy, winter 2015 edn. Metaphysics Research Lab, Stanford University, Stanford, CA
Helbing D (1991) A mathematical model for the behavior of pedestrians. Behav Sci 36(4):298–310
Helbing D (1994) A mathematical model for the behavior of individuals in a social field. J Math Sociol 19(3):189–219
Helbing D (2001) Traffic and related self-driven many-particle systems. Rev Mod Phys 73:10671141
Helbing D, Molnár P (1995) Social force model for pedestrian dynamics. Phys Rev E 51(5):4282
Helbing D, Tilch B (1998) Generalized force model of traffic dynamics. Phys Rev E 58(1):133–138. https://doi.org/10.1103/PhysRevE.58.133
Hoogendoorn S, Hoogendoorn R, Daamen W (2011) Wiedemann revisited – new trajectory filtering technique and its implications for car-following modeling. Transp Res Rec J Transp Res Board 2260:152–162. https://doi.org/10.3141/2260–17
Huys R, Perdikis D, Jirsa VK (2014) Functional architectures and structured flows on manifolds: a dynamical framework for motor behavior. Psychol Rev 121(3):302–336
James W (1890) The principles of psychology, vol 1. Henry Holt and Company, New York
Jiang R, Wu Q, Zhu Z (2001) Full velocity difference model for a car-following theory. Phys Rev E 64(1):017,101 (4 pages). https://doi.org/10.1103/PhysRevE.64.017101
Jiang R, Hu MB, Zhang HM, Gao ZY, Jia B, Wu QS, Wang B, Yang M (2014) Traffic experiment reveals the nature of car-following. PLoS One 9(4):e94, 351 (9 pages). https://doi.org/10.1371/journal.pone.0094351
Jiang R, Hu MB, Zhang H, Gao ZY, Jia B, Wu QS (2015) On some experimental features of car-following behavior and how to model them. Transp Res B Methodol 80:338–354. https://doi.org/10.1016/j.trb.2015.08.003
Kendziorra A, Wagner P, Toledo T (2016) A stochastic car following model. Transp Res Procedia 15:198–207. https://doi.org/10.1016/j.trpro.2016.06.017, International Symposium on Enhancing Highway Performance (ISEHP), June 14–16, 2016, Berlin
Kerner BS (1998) Experimental features of self-organization in traffic flow. Phys Rev Lett 81(17):3797–3800. https://doi.org/10.1103/PhysRevLett.81.3797
Kerner BS (1999) Theory of congested traffic flow: self-organization without bottlenecks. In: Ceder A (ed) Transportation and traffic theory: proceedings of the 14th international symposium on transportation and traffic theory Jerusalem, Israel, 20–23 July, 1999. Elsevier Science, Oxford, UK, pp 147–171
Kerner BS (2004) The physics of traffic: empirical freeway pattern features, engineering applications, and theory. Springer, Berlin
Kerner BS (2009a) Introduction to modern traffic flow theory and control: the long road to three-phase traffic theory. Springer, Berlin
Kerner BS (2009b) Traffic congestion, modeling approaches to. In: Meyers RA (ed) Encyclopedia of complexity and systems science. Springer- Science+Buisiness Media, New York, pp 9302–9355
Kerner BS (2013) Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: a brief review. Phys A Stat Mech Appl 392(21):5261–5282. https://doi.org/10.1016/j.physa.2013.06.004
Kerner BS (2016) Failure of classical traffic flow theories: stochastic highway capacity and automatic driving. Phys A Stat Mech Appl 450:700–747. https://doi.org/10.1016/j.physa.2016.01.034
Kerner BS (2017) Breakdown in traffic networks: fundamentals of transportation science. Springer, Berlin. https://doi.org/10.1007/978-3-662-54473-0
Kerner BS, Klenov SL (2002) A microscopic model for phase transitions in traffic flow. J Phys A Math Gen 35(3):L31–L43. https://doi.org/10.1088/0305–4470/35/3/102
Kerner BS, Klenov SL (2003) Microscopic theory of spatial-temporal congested traffic patterns at highway bottlenecks. Phys Rev E 68(3):036,130 (20 pages). https://doi.org/10.1103/PhysRevE.68.036130
Kerner BS, Klenov SL (2006) Deterministic microscopic three-phase traffic flow models. J Phys A Math Gen 39(8):1775–1809. https://doi.org/10.1088/0305-4470/39/23/C01
Kerner BS, Rehborn H (1997) Experimental properties of phase transitions in traffic flow. Phys Rev Lett 79(202A-3):4030–4033. https://doi.org/10.1103/PhysRevLett.79.4030
Kerner BS, Klenov SL, Wolf DE (2002) Cellular automata approach to three-phase traffic theory. J Phys A Math Gen 35(47):9971–10,013. https://doi.org/10.1088/0305–4470/35/47/303
Kerner BS, Klenov SL, Hiller A (2006) Criterion for traffic phases in single vehicle data and empirical test of a microscopic three-phase traffic theory. J Phys A Math Gen 39(9):2001–2020. https://doi.org/10.1088/0305–4470/39/9/002
Knospe W, Santen L, Schadschneider A, Schreckenberg M (2002) Single-vehicle data of highway traffic: microscopic description of traffic phases. Phys Rev E 65(5):056–133 (16 pages)
Krauss S, Wagner P, Gawron C (1996) Continuous limit of the Nagel-Schreckenberg model. Phys Rev E 54(4):3707–3712. https://doi.org/10.1103/PhysRevE.54.3707
Latash ML (2008) Synergy. Oxford University Press, Oxford
Latash ML (2012a) Fundamentals of motor control. Elsevier, London
Latash ML (2012b) The bliss (not the problem) of motor abundance (not redundancy). Exp Brain Res 217(1):1–5. https://doi.org/10.1007/s00221–012–3000–4
Latash ML (2015) Bernstein’s “desired future” and physics of human movement. In: Nadin M (ed) Anticipation: learning from the past the Russian/soviet contributions to the science of anticipation. Springer, Cham, pp 287–300
Latash ML, Scholz JP, Schöner G (2007) Toward a new theory of motor synergies. Mot Control 11(3):276–308
Lewin K (1951) In: Cartwright D-w (ed) Field theory in social science: selected theoretical papers. Harpers, Oxford, UK
Li QL, Wong S, Min J, Tian S, Wang BH (2016) A cellular automata traffic flow model considering the heterogeneity of acceleration and delay probability. Phys A Stat Mech Appl 456:128134. https://doi.org/10.1016/j.physa.2016.03.026
Loram I, Gollee H, Lakie M, Gawthrop P (2011) Human control of an inverted pendulum: is continuous control necessary? Is intermittent control effective? Is intermittent control physiological? J Physiol 589(2):307–324
Lubashevsky I (2012) Dynamical traps caused by fuzzy rationality as a new emergence mechanism. Adv Complex Syst 15(8):1250,045 (25 pages). https://doi.org/10.1142/S0219525912500452
Lubashevsky I (2016) Human fuzzy rationality as a novel mechanism of emergent phenomena. In: Skiadas CH, Skiadas C (eds) Handbook of applications of Chaos theory. CRC Press, Taylor & Francis Group, London, pp 827–878
Lubashevsky I (2017) Physics of the human mind. Springer International Publishing AG, Cham. https://doi.org/10.1007/978-3-319-51706-3
Lubashevsky I, Ando H (2016) Intermittent control properties of car following: theory and driving simulator experiments. arXiv preprint physics 160901812, pp 125
Lubashevsky IA, Gafiychuk VV, Demchuk AV (1998) Anomalous relaxation oscillations due to dynamical traps. Phys A Stat Mech Appl 255(3–4):406–414. https://doi.org/10.1016/S0378-4371(98)00094-6
Lubashevsky I, Kalenkov S, Mahnke R (2002a) Towards a variational principle for motivated vehicle motion. Phys Rev E 65:036,140, (5 pages). https://doi.org/10.1103/PhysRevE.65.036140
Lubashevsky I, Mahnke R, Wagner P, Kalenkov S (2002b) Long-lived states in synchronized traffic flow: empirical prompt and dynamical trap model. Phys Rev E 66:016,117, 13 pages
Lubashevsky I, Hajimahmoodzadeh M, Katsnelson A, Wagner P (2003a) Noise-induced phase transition in an oscillatory system with dynamical traps. Eur Phys J B Condens Matter Complex Syst 36(1):115–118. https://doi.org/10.1140/epjb/e2003-00323-0
Lubashevsky I, Wagner P, Mahnke R (2003b) Bounded rational driver models. Eur Phys J B Condens Matter Complex Syst 32(2):243–247. https://doi.org/10.1140/epjb/e2003-00094-6
Lubashevsky I, Wagner P, Mahnke R (2003c) Rational-driver approximation in car-following theory. Phys Rev E 68(5):056,109, (15 pages). https://doi.org/10.1103/PhysRevE.68.056109
Luttinen RT (1996) Statistical analysis of vehicle time headways. PhD thesis, Helsinki University of Technol-ogy, Lahti Cente, Neopoli, Lahti
Maerivoet S, Moor BD (2005) Cellular automata models of road traffic. Phys Rep 419(1):1–4. https://doi.org/10.1016/j.physrep.2005.08.005
Mahnke R, Kaupužs J, Lubashevsky I (2005) Probabilistic description of traffic flow. Phys Rep 408(1):1–130. https://doi.org/10.1016/j.physrep.2004.12.001
Marschler C, Sieber J, Berkemer R, Kawamoto A, Starke J (2014) Implicit methods for equation-free analysis: convergence results and analysis of emergent waves in microscopic traffic models. SIAM J Appl Dyn Syst 13(3):1202–1238
Marschler C, Sieber J, Hjorth PG, Starke J (2015) Equation-free analysis of macroscopic behavior in traffic and pedestrian flow. In: Chraibi M, Boltes M, Schadschneider A, Seyfried A (eds) Traffic and granular Flow’13. Springer International Publishing, Cham, pp 423–439
Martin V, Scholz JP, Schöner G (2009) Redundancy, self-motion, and motor control. Neural Comput 21(5):1371–1414
Milton JG (2013) Intermittent motor control: the “drift-and-act” hypothesis. In: Richardson MJ, Riley MA, Shockley K (eds) Progress in motor: control neural, computational and dynamic approaches. Springer Science+Business Media, New York, pp 169–193
Nagatani T, Nakanishi K (1998) Delay effect on phase transitions in traffic dynamics. Phys Rev E 57(6):6415–6421. https://doi.org/10.1103/PhysRevE.57.6415
Nagel K, Schreckenberg M (1992) A cellular automaton model for freeway traffic. J Phys I 2(12):2221–2229. https://doi.org/10.1051/jp1:1992277
Newell GF (1961) Nonlinear effects in the dynamics of car following. Oper Res 9(2):209–229
Oullier O, Kelso J (2009) Social coordination, from the perspective of coordination dynamics. In: Meyers R (ed) Encyclopedia of complexity and systems science. Springer Science +Business Media, LLC, New York, pp 8198–8213
Pariota L, Bifulco GN (2015) Experimental evidence supporting simpler action point paradigms for car-following. Transport Res F Traffic Psychol Behav 35:1–15. https://doi.org/10.1016/j.trf.2015.08.002
Perlovsky LI (2006) Toward physics of the mind: concepts, emotions, consciousness, and symbols. Phys Life Rev 3(1):23–55. https://doi.org/10.1016/j.plrev.2005.11.003
Perlovsky LI (2016) Physics of the mind. Front Syst Neurosci 10:Article 84 (12 pages. https://doi.org/10.3389/fnsys.2016.00084
Pezzulo G, Rigoli F, Friston K (2015) Active inference, homeostatic regulation and adaptive behavioural control. Prog Neurobiol 134:17–35. https://doi.org/10.1016/j.pneurobio.2015.09.001
Pipes LA (1953) An operational analysis of traffic dynamics. J Appl Phys 24(3):274–281
Proctor RW, Vu KPL (2003) Action selection. In: Weiner IB, Healy AF, Proctor RW (eds) Handbook of psychology. Experimental psychology, vol 4. Wiley, Hoboken, pp 293–316
Reiter U (1994) Empirical studies as basis for traffic flow models. In: Alçelik R and Reilly W (eds) Proceedings of the second international symposium on highway capacity (Sydney, N.S.W., 1994), vol 2. : Australian Road Research Board, Vermont South, Victoria, Australia pp 493–502
Reuschel A (1950a) Vehicle movements in a platoon. Österr Ing Arch 4:193–215
Reuschel A (1950b) Vehicle movements in a platoon with uniform acceleration or deceleration of the lead vehicle. Z Österr Ing Arch Ver 95:50–62; 73–77
Schmidt RA (1975) A schema theory of discrete motor skill learning. Psychol Rev 82(4):225–260
Schmidt RA (2003) Motor schema theory after 27 years: reflections and implications for a new theory. Res Q Exerc Sport 74(4):366–375
Schmidt RA, Lee TD (2011) Motor control and learning: a behavioral emphasis, 5th edn. Human Kinetics, Champaign
Schoeller F, Perlovsky L, Arseniev D (2018) Physics of mind: experimental confirmations of theoretical predictions. Phys Life Rev. https://doi.org/10.1016/j.plrev.2017.11.021
Scholz PJ, Schöner G (1999) The uncontrolled manifold concept: identifying control variables for a functional task. Exp Brain Res 126(3):289–306. https://doi.org/10.1007/s002210050738
Smith DW (2013) Phenomenology In: Zalta EN (ed) The Stanford encyclopedia of philosophy, winter 2016 edn. Metaphysics Research Lab, Stanford University, Stanford, CA
Suzuki Y, Nomura T, Casadio M, Morasso P (2012) Intermittent control with ankle, hip, and mixed strategies during quiet standing: a theoretical proposal based on a double inverted pendulum model. J Theor Biol 310:55–79
Tian J, Jiang R, Jia B, Gao Z, Ma S (2016) Empirical analysis and simulation of the concave growth pattern of traffic oscillations. Transp Res B Methodol 93:338–354. https://doi.org/10.1016/j.trb.2016.08.001
Todosiev EP (1963) The action point model of the driver-vehicle system. Technical report 202A–3, PhD dissertation, Ohio State University
Todosiev EP, Barbosa LC (1963/64) A proposed model for the driver-vehicle system. Traffic Eng 34:17–20
TORCS (2018). The official site of TORCS. http://torcs.sourceforge.net/index.php. Accessed on Feb 2018
Treiber M, Helbing D (1999) Macroscopic simulation of widely scattered synchronized traffic states. J Phys A Math Gen 32(1):L17–L23. https://doi.org/10.1088/0305-4470/32/1/003
Treiber M, Kesting A (2013) Traffic flow dynamics: data, models and simulation. Springer, Berlin
Treiber M, Hennecke A, Helbing D (2000) Congested traffic states in empirical observations and microscopic simulations. Phys Rev E 62:1805–1824
Wagner P (2006) How human drivers control their vehicle. Eur Phys J B Condens Matter Complex Syst 52(3):427–431. https://doi.org/10.1140/epjb/e2006-00300-1
Wagner P (2012) Analyzing fluctuations in car-following. Transp Res B Methodol 46(10):1384–1392
Wagner P, Lubashevsky I (2003) Empirical basis for car-following theory development. arXiv preprint condmat/0311192. http://adsabs.harvard.edu/abs/2003cond.mat.11192W
Yoshikawa N, Suzuki Y, Kiyono K, Nomura T (2016) Intermittent feedback-control strategy for stabilizing inverted pendulum on manually controlled cart as analogy to human stick balancing. Front Comput Neurosci 10:Article 34 , 19 pages. https://doi.org/10.3389/fncom.2016.00034
Yu S, Liu Q, Li X (2013) Full velocity difference and acceleration model for a car-following theory. Commun Nonlinear Sci Numer Simul 18(5):1229–1234. https://doi.org/10.1016/j.cnsns.2012.09.014
Zaslavsky GM (1995) From Hamiltonian chaos to Maxwell’s demon. Chaos 5(4):653–661
Zaslavsky GM (2002) Dynamical traps. Phys D Nonlinear Phenom 168–169:292–304. https://doi.org/10.1016/S0167-2789(02)00516-X {VII} Latin American Workshop on Nonlinear Phenomena
Zaslavsky GM (2005) Hamiltonian chaos and fractional dynamics. Oxford University Press, New York
Zgonnikov A, Lubashevsky I (2014) Extended phase space description of human-controlled systems dynamics. Prog Theor Exp Phys 2014(3):033J02
Zgonnikov A, Lubashevsky I (2015) Double-well dynamics of noise-driven control activation in human intermittent control: the case of stick balancing. Cogn Process 16(4):351–358. https://doi.org/10.1007/s10339-015-0653-5
Zgonnikov A, Lubashevsky I, Kanemoto S, Miyazawa T, Suzuki T (2014) To react or not to react? Intrinsic stochasticity of human control in virtual stick balancing. J R Soc Interface 11:20140,636
Zgonnikov A, Kanemoto S, Lubashevsky I, Suzuki T (2015) How the type of visual feedback affects actions of human operators: the case of virtual stick balancing. In: Systems, man, and cybernetics (SMC), 2015 I.E. international conference on. IEEE, Piscataway, NJ pp 1100–1103. https://doi.org/10.1109/SMC.2015.197
Zhao X, Gao Z (2005) A new car-following model: full velocity and acceleration difference model. Eur Phys J B Condens Matter Complex Syst 47(1):145–150. https://doi.org/10.1140/epjb/e2005-00304-3
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media LLC
About this entry
Cite this entry
Lubashevsky, I., Morimura, K. (2018). Physics of Mind and Car-Following Problem. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27737-5_714-1
Download citation
DOI: https://doi.org/10.1007/978-3-642-27737-5_714-1
Received:
Accepted:
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27737-5
Online ISBN: 978-3-642-27737-5
eBook Packages: Springer Reference Physics and AstronomyReference Module Physical and Materials ScienceReference Module Chemistry, Materials and Physics