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Traffic Networks, Breakdown in

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Glossary

Bottleneck :

Traffic breakdown leading to the onset of congestion in a traffic network occurs usually at a network bottleneck. Road bottlenecks are caused, for example, by on- and off-ramps, road gradients, roadworks, a decrease in the number of road lines (in the flow direction), traffic signal, etc.

Breakdown Minimization (BM) Principle :

The BM principle states that the optimum of a traffic or transportation network with N bottlenecks is reached when dynamic traffic assignment, optimization, and control are performed in the network in such a way that the probability P net for the occurrence of traffic breakdown in at least one of the network bottlenecks during a given time interval T ob for observing traffic flow reaches the minimum possible value. The BM principle is equivalent to the maximization of the probability that during the time interval T ob, traffic breakdown occurs at none of the network bottlenecks.

Congested Traffic :

Congested traffic is defined as a state of...

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Bibliography

Primary Literature

  • Allsop RE, Bell MGH, Heydecker BG (eds) (2007) Transportation and traffic theory 2007. Elsevier Science Ltd, Amsterdam

    Google Scholar 

  • Banks JH (1989) Freeway speed-flow-concentration relationships: more evidence and interpretations (with discussion and closure). Transp Res Rec 1225:53–60

    Google Scholar 

  • Banks JH (1990) Two-capacity phenomenon at freeway bottlenecks: a basis for ramp metering? Transp Res Rec 1287:20–28

    Google Scholar 

  • Barlović R, Santen L, Schadschneider A, Schreckenberg M (1998) Metastable states in cellular automata for traffic flow. Eur Phys J B 5:793–800

    Article  ADS  Google Scholar 

  • Bell MGH, Iida Y (1997) Transportation network analysis. John Wiley & Sons, Incorporated, Hoboken

    Book  Google Scholar 

  • Bellomo N, Coscia V, Delitala M (2002) On the mathematical theory of vehicular traffic flow I. Fluid dynamic and kinetic modelling. Math Mod Meth App Sc 12:1801–1843

    Article  MathSciNet  MATH  Google Scholar 

  • Bose A, Ioannou P (2003) Mixed manual/semi-automated traffic: a macroscopic analysis. Transp Res C 11:439–462

    Article  Google Scholar 

  • Brilon W, Zurlinden H (2004) Kapazität von Straßen als Zufallsgröße. Straßenverkehrstechnik 4:164

    Google Scholar 

  • Brilon W, Geistefeld J, Regler M (2005a) Reliability of freeway traffic flow: a stochastic concept of capacity. In: Mahmassani HS (ed) Transportation and traffic theory. Proceedings of the 16th international symposium on transportation and traffic theory. Elsevier, Amsterdam, pp 125–144

    Google Scholar 

  • Brilon W, Regler M, Geistefeld J (2005b) Zufallscharakter der Kapazität von Autobahnen und praktische Konsequenzen – Teil 1. Straßenverkehrstechnik 3:136

    Google Scholar 

  • Brockfeld E, Kühne RD, Skabardonis A, Wagner P (2003) Toward benchmarking of microscopic traffic flow models. Transp Res Rec 1852:124–129

    Article  Google Scholar 

  • Brockfeld E, Kühne RD, Wagner P (2005) Calibration and validation of simulation models. In: Proceeding of the transportation research board 84th annual meeting, TRB paper no. 05-2152. TRB, Washington, DC

    Google Scholar 

  • Cambridge Systematics, Inc (2001) Twin Cities ramp meter evaluation – final report. Cambridge Systematics, Inc., Oakland. Prepared for the Minnesota Department of Transportation

    Google Scholar 

  • Cassidy MJ, Skabardonis A (eds) (2011) Papers selected for the 19th international symposium on transportation and traffic theory. Procedia Soc Behav Sci 17:1–716

    Google Scholar 

  • Ceder A (ed) (1999) Transportation and traffic theory. In: Proceedings of the 14th international symposium on transportation and traffic theory. Elsevier Science Ltd, Oxford

    Google Scholar 

  • Chandler RE, Herman R, Montroll EW (1958) Traffic dynamics: studies in car following. Oper Res 6:165–184

    Article  MathSciNet  Google Scholar 

  • Cheng H (2011) Autonomous intelligent vehicles: theory, algorithms, and implementation. Springer, Berlin

    Book  Google Scholar 

  • Chien CC, Zhang Y, Ioannou PA (1997) Traffic density control for automated highway systems. Automatica 33:1273–1285

    Article  MathSciNet  MATH  Google Scholar 

  • Chowdhury D, Santen L, Schadschneider A (2000) Statistical physics of vehicular traffic and some related systems. Phys Rep 329:199

    Article  ADS  MathSciNet  Google Scholar 

  • Cremer M (1979) Der Verkehrsfluss auf Schnellstrassen. Springer, Berlin

    Book  Google Scholar 

  • Daganzo CF (1994) The cell-transmission model: a dynamic representation of highway traffic consistent with the hydrodynamic theory. Transp Res B 28:269–287

    Article  Google Scholar 

  • Daganzo CF (1995) The cell transmission model, part II: network traffic. Transp Res B 29:79–93

    Article  Google Scholar 

  • Daganzo CF (1997) Fundamentals of transportation and traffic operations. Elsevier Science Inc., New York

    Book  Google Scholar 

  • Davis LC (2004) Effect of adaptive cruise control systems on traffic flow. Phys Rev E 69:066110

    Article  ADS  Google Scholar 

  • Davis LC (2007) Effect of adaptive cruise control systems on mixed traffic flow near an on-ramp. Physica A 379:274–290

    Article  ADS  Google Scholar 

  • Davis LC (2014) Nonlinear dynamics of autonomous vehicles with limits on acceleration. Physica A 405:128–139

    Article  ADS  MathSciNet  Google Scholar 

  • Dion F, Rakha H, Kang YS (2004) Comparison of delay estimates at under-saturated and over-saturated pre-timed signalized intersections. Transp Res B 38:99–122

    Article  Google Scholar 

  • Elefteriadou L (2014) An introduction to traffic flow theory, Springer optimization and its applications, vol 84. Springer, Berlin

    MATH  Google Scholar 

  • Elefteriadou L, Roess RP, McShane WR (1995) Probabilistic nature of breakdown at freeway merge junctions. Transp Res Rec 1484:80–89

    Google Scholar 

  • Elefteriadou L, Kondyli A, Brilon W, Hall FL, Persaud B, Washburn S (2014) Enhancing ramp metering algorithms with the use of probability of breakdown models. J Transp Eng 140:04014003

    Article  Google Scholar 

  • Friesz TL, Bernstein D (2016) Foundations of network optimization and games, Complex networks and dynamic systems, vol 3. Springer, New York/Berlin

    MATH  Google Scholar 

  • Fukui M, Sugiyama Y, Schreckenberg M, Wolf DE (eds) (2003) Traffic and granular flow’ 01. Springer, Heidelberg

    MATH  Google Scholar 

  • Gartner NH (1983) OPAC: a demand-responsive strategy for traffic signal control. Transp Res Rec 906:75–81

    Google Scholar 

  • Gartner NH, Stamatiadis C (2002) Arterial-based control of traffic flow in urban grid networks. Math Comput Model Pergamon 35:657–671

    Article  MathSciNet  MATH  Google Scholar 

  • Gartner NH, Stamatiadis C (2009) Traffic networks, optimization and control of Urban. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin, pp 9470–9500

    Chapter  Google Scholar 

  • Gartner NH, Messer CJ, Rathi A (eds) (2001) Traffic flow theory: a state-of-the-art report. Transportation Research Board, Washington, DC

    Google Scholar 

  • Gazis DC (2002) Traffic theory. Springer, Berlin

    MATH  Google Scholar 

  • Gazis DC, Herman R, Potts RB (1959) Car-following theory of steady-state traffic flow. Oper Res 7:499–505

    Article  MathSciNet  Google Scholar 

  • Gazis DC, Herman R, Rothery RW (1961) Nonlinear follow-the-leader models of traffic flow. Oper Res 9:545–567

    Article  MathSciNet  MATH  Google Scholar 

  • Gipps PG (1981) Behavioral car-following model for computer simulation. Transp Res B 15:105–111

    Article  Google Scholar 

  • Gipps PG (1986) A model for the structure of lane-changing decisions. Transp Res B 20:403–414

    Article  Google Scholar 

  • Grafton RB, Newell GF (1967) Optimal policies for the control of an undersaturated intersection. In: Edie LC, Herman R, Rothery R (eds) Vehicular traffic science. American Elsevier Publishing Company, New York, pp 239–257

    Google Scholar 

  • Greenshields BD (1935) A study of traffic capacity. In: Highway research board proceedings, vol 14, pp 448–477

    Google Scholar 

  • Haight FA (1963) Mathematical theories of traffic flow. Academic, New York

    MATH  Google Scholar 

  • Hall FL (1987) An interpretation of speed-flow-concentration relationships using catastrophe theory. Trans Res A 21:191–201

    Article  Google Scholar 

  • Hall FL (2001) Traffic stream characteristics. In: Gartner NH, Messer CJ, Rathi A (eds) Traffic flow theory: a state-of-the-art report. Transportation Research Board, Washington DC, pp 2-1–2-36

    Google Scholar 

  • Hall FL, Agyemang-Duah K (1991) Freeway capacity drop and the definition of capacity. Transp Res Rec 1320:91–98

    Google Scholar 

  • Hall FL, Hurdle VF, Banks JH (1992) Synthesis of recent work on the nature of speed-flow and flow-occupancy (or density) relationships on freeways. Transp Res Rec 1365:12–18

    Google Scholar 

  • Hegyi A, Bellemans T, De Schutter B (2017) Freeway traffic management and control. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin

    Google Scholar 

  • Helbing D (2001) Traffic and related self-driven many-particle systems. Rev Mod Phys 73:1067–1141

    Article  ADS  Google Scholar 

  • Helbing D, Herrmann HJ, Schreckenberg M, Wolf DE (eds) (2000) Traffic and granular flow’ 99. Springer, Heidelberg

    MATH  Google Scholar 

  • Herman R, Montroll EW, Potts RB, Rothery RW (1959) Traffic dynamics: analysis of stability in car following. Oper Res 7:86–106

    Article  MathSciNet  Google Scholar 

  • Highway Capacity Manual (2000) National Research Council, Transportation Research Boad, Washington, DC

    Google Scholar 

  • Highway Capacity Manual (2010) National Research Council, Transportation Research Boad, Washington, DC

    Google Scholar 

  • Hoogendoorn SP, Luding S, Bovy PHL, Schreckenberg M, Wolf DE (eds) (2005) Traffic and granular flow’ 03. Springer, Heidelberg

    Google Scholar 

  • Hoogendoorn SP, Knoop VL, van Lint H (eds) (2013) 20th international symposium on transportation and traffic theory (ISTTT 2013). Procedia Soc Behav Sci 80:1–996

    Google Scholar 

  • Hunt PB, Robertson DI, Bretherton RD, Winton RI (1981) SCOOT a traffic responsive method of coordinating signals. TRRL report no. LR 1014. Transportation and Road Research Laboratory, Crowthorne

    Google Scholar 

  • Ioannou PA, Chien CC (1993) Autonomous intelligent cruise control. IEEE Trans Veh Technol 42:657–672

    Article  Google Scholar 

  • ISO 15622 (2010) Intelligent transport systems – adaptive cruise control systems – performance requirements and test procedures

    Google Scholar 

  • Kerner BS (1998a) Theory of congested traffic flow. In: Rysgaard R (ed) Proceedings of the 3rd symposium on highway capacity and level of service, vol 2. Road Directorate, Ministry of Transport, Denmark, pp 621–642

    Google Scholar 

  • Kerner BS (1998b) Empirical features of self-organization in traffic flow. Phys Rev Lett 81:3797–3400

    Article  ADS  MATH  Google Scholar 

  • Kerner BS (1999a) Congested traffic flow: observations and theory. Transp Res Rec 1678:160–167

    Article  Google Scholar 

  • Kerner BS (1999b) Theory of congested traffic flow: self-organization without bottlenecks. In: Ceder A (ed) Transportation and traffic theory. Elsevier Science, Amsterdam, pp 147–171

    Google Scholar 

  • Kerner BS (1999c) The Physics of Traffic. Phys World 12:25–30

    Article  Google Scholar 

  • Kerner BS (2004a) The physics of traffic. Springer, Berlin/New York

    Book  Google Scholar 

  • Kerner BS (2004b) Verfahren zur Ansteuerung eines in einem Fahrzeug befindlichen verkehrsadaptiven Assistenzsystems, German patent publication DE 10308256A1. https://google.com/patents/DE10308256A1; Patent WO 2004076223A1 (2004) https://google.com/patents/WO2004076223A1; EU Patent EP 1597106B1 (2006); German patent DE 502004001669D1 (2006)

  • Kerner BS (2005) Control of spatiotemporal congested traffic patterns at highway bottlenecks. Physica A 355:565–601

    Article  ADS  Google Scholar 

  • Kerner BS (2007a) Control of spatiotemporal congested patterns at highway bottlenecks. IEEE Trans ITS 8:308–320

    ADS  Google Scholar 

  • Kerner BS (2007b) On-ramp metering based on three-phase theory – part III. Traffic Eng Control 48:68–75

    Google Scholar 

  • Kerner BS (2007c) Three-phase traffic theory and its applications for freeway traffic control. In: Inweldi PO (ed) Transportation research trends. Nova Science Publishers, Inc., New York, pp 1–97

    Google Scholar 

  • Kerner BS (2007d) Method for actuating a traffic-adaptive assistance system which is located in a vehicle, USA patent US 20070150167A1. https://google.com/patents/US20070150167A1; USA patent US 7451039B2 (2008)

  • Kerner BS (2007e) Betriebsverfahren für ein fahrzeugseitiges verkehrsadaptives Assistenzsystem, German patent publication DE 102007008253A1. https://register.dpma.de/DPMAregister/pat/PatSchrifteneinsicht?docId=DE102007008253A1

  • Kerner BS (2007f) Betriebsverfahren für ein fahrzeugseitiges verkehrsadaptives Assistenzsystem, German patent publication DE 102007008257A1. https://register.dpma.de/DPMAregister/pat/PatSchrifteneinsicht?docId=DE102007008257A1

  • Kerner BS (2008) Betriebsverfahren für ein fahrzeugseitiges verkehrsadaptives Assisten-system, German patent publication DE 102007008254A1

    Google Scholar 

  • Kerner BS (2009) Introduction to modern traffic flow theory and control. Springer, Berlin/New York

    Book  MATH  Google Scholar 

  • Kerner BS (2011a) Optimum principle for a vehicular traffic network: minimum probability of congestion. J Phys A Math Theor 44:092001

    Article  ADS  MathSciNet  Google Scholar 

  • Kerner BS (2011b) Physics of traffic gridlock in a city. Phys Rev E 84:045102(R)

    Article  ADS  Google Scholar 

  • Kerner BS (2013a) Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: a brief review. Physica A 392:5261–5282

    Article  ADS  MathSciNet  Google Scholar 

  • Kerner BS (2013b) The physics of green-wave breakdown in a city. Europhys Lett 102:28010

    Article  ADS  Google Scholar 

  • Kerner BS (2014) Three-phase theory of city traffic: moving synchronized flow patterns in under-saturated city traffic at signals. Physica A 397:76–110

    Article  ADS  MathSciNet  Google Scholar 

  • Kerner BS (2015a) Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: growing wave of increase in speed in synchronized flow. Phys Rev E 92:062827

    Article  ADS  Google Scholar 

  • Kerner BS (2015b) Failure of classical traffic flow theories: a critical review. Elektrotechnik und Informationstechnik 132:417–433

    Article  Google Scholar 

  • Kerner BS (2016a) Failure of classical traffic flow theories: stochastic highway capacity and automatic driving. Physica A 450:700–747

    Article  ADS  MathSciNet  Google Scholar 

  • Kerner BS (2016b) The maximization of the network throughput ensuring free flow conditions in traffic and transportation networks: breakdown minimization (BM) principle versus Wardrops equilibria. Eur Phys J B 89:199

    Article  ADS  Google Scholar 

  • Kerner BS (2017a) Breakdown minimization principle versus Wardrops equilibria for dynamic traffic assignment and control in traffic and transportation networks: a critical mini-review. Physica A 466:626–662

    Article  ADS  MathSciNet  Google Scholar 

  • Kerner BS (2017b) Breakdown in traffic networks: fundamentals of transportation science. Springer, Berlin/New York

    Book  Google Scholar 

  • Kerner BS (2017c) Traffic breakdown, modeling approaches to. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin

    Google Scholar 

  • Kerner BS (2017d) Physics of Autonomous Driving based on Three-Phase Traffic Theory. arXiv:1710.10852v3 (http://arxiv.org/abs/1710.10852)

  • Kerner BS, Klenov SL (2003) Microscopic theory of spatio-temporal congested traffic patterns at highway bottlenecks. Phys Rev E 68:036130

    Article  ADS  Google Scholar 

  • Kerner BS, Klenov SL (2009) Traffic breakdown, probabilistic theory of. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin, pp. 9282–9303

    Google Scholar 

  • Kerner BS, Konhäuser P (1994) Structure and parameters of clusters in traffic flow. Phys Rev E 50:54–83

    Article  ADS  Google Scholar 

  • Kerner BS, Rehborn H (1996a) Experimental features and characteristics of traffic jams. Phys Rev E 53:R1297–R1300

    Article  ADS  Google Scholar 

  • Kerner BS, Rehborn H (1996b) Experimental properties of complexity in traffic flow. Phys Rev E 53:R4275–R4278

    Article  ADS  Google Scholar 

  • Kerner BS, Rehborn H (1997) Experimental properties of phase transitions in traffic flow. Phys Rev Lett 79:4030–4033

    Article  ADS  Google Scholar 

  • Kerner BS, Klenov SL, Schreckenberg M (2014) Traffic breakdown at a signal: classical theory versus the three-phase theory of city traffic. J Stat Mech 2014:P03001

    Article  MathSciNet  Google Scholar 

  • Kometani E, Sasaki T (1958) On the stability of traffic flow (report-I). J Oper Res Soc Jpn 2:11

    MathSciNet  Google Scholar 

  • Kometani E, Sasaki T (1959) A safety index for traffic with linear spacing. Oper Res 7:704

    Article  Google Scholar 

  • Kometani E, Sasaki T (1961) Dynamic behavior of traffic with a nonlinear spacing. In: Herman R (ed) Theory of traffic flow. Elsevier, Amsterdam, pp 105–119

    Google Scholar 

  • Krauß S, Wagner P, Gawron C (1997) Metastable states in a microscopic model of traffic flow. Phys Rev E 55:5597–5602

    Article  ADS  Google Scholar 

  • Kuhn TS (2012) The structure of scientific revolutions, 4th edn. The University of Chicago Press, Chicago/London

    Book  Google Scholar 

  • Kukuchi S, Uno N, Tanaka M (2003) Impacts of shorter perception-reaction time of adapted cruise controlled vehicles on traffic flow and safety. J Transp Eng 129:146–154

    Article  Google Scholar 

  • Kuwahara M, Kita H, Asakura Y (eds) (2015) 21st international symposium on transportation and traffic theory. Transp Res Procedia 7:1–704

    Google Scholar 

  • Lam WHK, Wong SC, Lo HK (eds) (2009) Transportation and traffic theory 2009. Springer, Dordrecht/Heidelberg/London/New York

    Google Scholar 

  • Lesort J-B (ed) (1996) Transportation and traffic theory. In: Proceedings of the 13th international symposium on transportation and traffic theory. Elsevier Science Ltd, Oxford

    Google Scholar 

  • Leutzbach W (1988) Introduction to the theory of traffic flow. Springer, Berlin

    Book  Google Scholar 

  • Levine W, Athans M (1966) On the optimal error regulation of a string of moving vehicles. IEEE Trans Automat Contr 11:355–361

    Article  Google Scholar 

  • Levinson D, Zhang L (2006) Ramp meters on trial: evidence from the twin cities metering holiday. Transp Res A 40:810–828

    Google Scholar 

  • Liang C-Y, Peng H (1999) Optimal adaptive cruise control with guaranteed string stability. Veh Syst Dyn 32:313–330

    Article  Google Scholar 

  • Liang C-Y, Peng H (2000) String stability analysis of adaptive cruise controlled vehicles. JSME Jnt J Ser C 43:671–677

    Google Scholar 

  • Lighthill MJ, Whitham GB (1995) On kinematic waves. I flow movement in long rives. II a theory of traffic flow on long crowded roads. Proc Roy Soc A 229:281–345

    Article  ADS  Google Scholar 

  • Little JD, Kelson MD, Gartner NH (1982) MAXBAND: a program for setting signals on arteries and triangular networks. Transp Res Rec 795:40–46

    Google Scholar 

  • Lorenz M, Elefteriadou L (2000) A probabilistic approach to defining freeway capacity and breakdown. Trans Res Cir E-C018:84–95

    Google Scholar 

  • Maerivoet S, De Moor B (2005) Cellular automata models of road traffic. Phys Rep 419:1–64

    Article  ADS  MathSciNet  Google Scholar 

  • Mahmassani HS (2001) Dynamic network traffic assignment and simulation methodology for advanced system management applications. Netw Spat Econ 1:267–292

    Article  Google Scholar 

  • Mahmassani HS (ed) (2005) Transportation and traffic theory. In: Proceedings of the 16th international symposium on transportation and traffic theory. Elsevier, Amsterdam

    Google Scholar 

  • May AD (1990) Traffic flow fundamentals. Prentice-Hall, Inc., Englewood Cliffs

    Google Scholar 

  • McDonald M, Wu J (1997) The integrated impacts of autonomous intelligent cruise control on motorway traffic flow. In: Proceedings of the ISC 97 conference, Boston

    Google Scholar 

  • Morgan JT, Little JDC (1964) Synchronizing traffic signals for maximal bandwidth. Oper Res 12:896–912

    Article  Google Scholar 

  • Nagatani T (2002) The physics of traffic jams. Rep Prog Phys 65:1331–1386

    Article  ADS  Google Scholar 

  • Nagel K, Schreckenberg M (1992) A cellular automaton model for freeway traffic. J Phys (France) I 2:2221–2229

    Article  ADS  Google Scholar 

  • Nagel K, Wagner P, Woesler R (2003) Still flowing: approaches to traffic flow and traffic jam modeling. Oper Res 51:681–716

    Article  MathSciNet  MATH  Google Scholar 

  • Newell GF (1961) Nonlinear effects in the dynamics of car following. Oper Res 9:209–229

    Article  MATH  Google Scholar 

  • Newell GF (1963) Instability in dense highway traffic, a review. In: Proceedings of the second international symposium on traffic road traffic flow. OECD, London, pp 73–83

    Google Scholar 

  • Newell GF (1982) Applications of queuing theory. Chapman Hall, London

    Book  MATH  Google Scholar 

  • Newell GF (2002) A simplified car-following theory: a lower order model. Transp Res B 36:195–205

    Article  Google Scholar 

  • Papageorgiou M (1983) Application of automatic control concepts in traffic flow modeling and control. Springer, Berlin/New York

    Book  MATH  Google Scholar 

  • Papageorgiou M, Kotsialos A (2000) Freeway ramp metering: an overview. In: Proceedings of the 3rd annual IEEE conference on intelligent transportation systems (ITSC 2000), Dearborn, Oct 2000, pp 228–239

    Google Scholar 

  • Papageorgiou M, Kotsialos A (2002) Freeway ramp metering: an overview. IEEE Trans Intell Transp Syst 3(4):271–280

    Article  Google Scholar 

  • Papageorgiou M, Papamichail I (2008) Overview of traffic signal operation policies for ramp metering. Transp Res Rec 2047:28–36

    Article  Google Scholar 

  • Papageorgiou M, Blosseville J-M, Hadj-Salem H (1990a) Modelling and real-time control of traffic flow on the southern part of Boulevard Priphrique in Paris: part I: modelling. Transp Res Part A 24A(5):345–359

    Article  Google Scholar 

  • Papageorgiou M, Blosseville J-M, Hadj-Salem H (1990b) Modelling and real-time control of traffic flow on the southern part of Boulevard Priphrique in Paris: part II: coordinated on-ramp metering. Transp Res Part A 24A(5):361–370

    Article  Google Scholar 

  • Papageorgiou M, Hadj-Salem H, Blosseville J-M (1991) ALINEA: a local feedback control law for on-ramp metering. Transp Res Rec 1320:58–64

    Google Scholar 

  • Papageorgiou M, Hadj-Salem H, Middelham F (1997) ALINEA local ramp metering – summary of field results. Transp Res Rec 1603:90–98

    Article  Google Scholar 

  • Papageorgiou M, Diakaki C, Dinopoulou V, Kotsialos A, Wang Y (2003) Review of road traffic control strategies. In: Proceedings of the IEEE, vol 91, pp 2043–2067

    Google Scholar 

  • Papageorgiou M, Wang Y, Kosmatopoulos E, Papamichail I (2007) ALINEA maximizes motorway throughput – an answer to flawed criticism. Traffic Eng Control 48(6):271–276

    Google Scholar 

  • Payne HJ (1971) Models of freeway traffic and control. In: Bekey GA (ed) Mathematical models of public systems, vol 1. Simulation Council, La Jolla

    Google Scholar 

  • Payne HJ (1979) FREFLO: A macroscopic simulation model of freeway traffic. Transp Res Rec 772:68

    Google Scholar 

  • Peeta S, Ziliaskopoulos AK (2001) Foundations of dynamic traffic assignment: the past, the present and the future. Netw Spat Econ 1:233–265

    Article  Google Scholar 

  • Persaud BN, Yagar S, Brownlee R (1998) Exploration of the breakdown phenomenon in freeway traffic. Transp Res Rec 1634:64–69

    Article  Google Scholar 

  • Pipes LA (1953) An operational analysis of traffic dynamics. J Appl Phys 24:274–287

    Article  ADS  MathSciNet  Google Scholar 

  • Prigogine I (1961) A Boltzmann-like approach to the statistical theory of traffic flow. In: Herman R (ed) Theory of traffic flow. Elsevier, Amsterdam, pp 158–164

    Google Scholar 

  • Rajamani R (2012) Vehicle dynamics AML control, Mechanical engineering series. Springer, Boston

    Book  MATH  Google Scholar 

  • Rakha H, Tawfik A (2009) Traffic networks: dynamic traffic routing, assignment, and assessment. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin, pp. 9429–9470

    Google Scholar 

  • Ran B, Boyce D (1996) Modeling dynamic transportation networks. Springer, Berlin

    Book  MATH  Google Scholar 

  • Rehborn H, Klenov SL (2009) Traffic prediction of congested patterns. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin, pp. 9500–9536

    Google Scholar 

  • Rehborn H, Klenov SL, Koller M (2017) Traffic prediction of congested patterns. In: Meyers RA (ed) Encyclopedia of complexity and system science. Springer, Berlin

    Google Scholar 

  • Reuschel A (1950) Fahrzeugbewegungen in der Kolonne. Österreichisches Ingenieur-Archiv 4:193–215

    MATH  Google Scholar 

  • Richards PI (1956) Shockwaves on the highway. Oper Res 4:42–51

    Article  Google Scholar 

  • Saifuzzaman M, Zheng Z (2014) Incorporating human-factors in car-following models: a review of recent developments and research needs. Transp Res C 48:379–403

    Article  Google Scholar 

  • Sathiyan SP, Kumar SS, Selvakumar AI (2013) A comprehensive review on cruise control for intelligent vehicles. Int J Innov Technol Explor Eng (IJITEE) 2:89–96

    Google Scholar 

  • Schadschneider A, Pöschel T, Kühne R, Schreckenberg M, Wolf, DE (eds) (2007) Traffic and granular flow’ 05. In: Proceedings of the international workshop on traffic and granular flow. Springer, Berlin

    Google Scholar 

  • Schadschneider A, Chowdhury D, Nishinari K (2011) Stochastic transport in complex systems. Elsevier Science Inc., New York

    MATH  Google Scholar 

  • Schreckenberg M, Wolf DE (eds) (1998) Traffic and granular flow’ 97. In: Proceedings of the international workshop on traffic and granular flow. Springer, Singapore

    Google Scholar 

  • Sheffi Y (1984) Urban transportation networks: equilibrium analysis with mathematical programming methods. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  • Shladover SE (1995) Review of the state of development of advanced vehicle control systems (AVCS). Veh Syst Dyn 24:551–595

    Article  Google Scholar 

  • Shvetsov VI (2003) Mathematical modeling of traffic flows. Autom Remote Control 64:1651–1689

    Article  MathSciNet  MATH  Google Scholar 

  • Smaragdis E, Papageorgiou M (2003) Series of new local ramp metering strategies. Transp Res Rec 1856:74–86

    Article  Google Scholar 

  • Swaroop D, Hedrick JK (1996) String stability for a class of nonlinear systems. IEEE Trans Autom Control 41:349–357

    Article  MATH  Google Scholar 

  • Swaroop D, Hedrick JK, Choi SB (2001) Direct adaptive longitudinal control of vehicle platoons. IEEE Trans Veh Technol 50:150–161

    Article  Google Scholar 

  • Taylor MAP (ed) (2002) Transportation and traffic theory in the 21st century. In: Proceedings of the 15th international symposium on transportation and traffic theory. Elsevier Science Ltd, Amsterdam

    Google Scholar 

  • Treiber M, Helbing D (2001) Microsimulations of freeway traffic including control measures. Automatisierungstechnik 49:478–484

    Article  Google Scholar 

  • Treiber M, Kesting A (2013) Traffic Flow dynamics. Springer, Berlin

    Book  MATH  Google Scholar 

  • van Arem B, van Driel C, Visser R (2006) The impact of cooperative adaptive cruise control on traffic-flow characteristics. IEEE Trans Intell Transp Syst 7:429–436

    Article  Google Scholar 

  • Wardrop JG (1952) Some theoretical aspects of road traffic research. In: Proceedings of the institute of civil engineers part II, vol 1, pp 325–378

    Google Scholar 

  • Webster FV (1958) Traffic signal settings. HMSO, London

    Google Scholar 

  • Whitham GB (1974) Linear and nonlinear waves. Wiley, New York

    MATH  Google Scholar 

  • Wiedemann R (1974) Simulation des Verkehrsflusses. University of Karlsruhe, Karlsruhe

    Google Scholar 

  • Wolf DE (1999) Cellular automata for traffic simulations. Physica A 263:438–451

    Article  ADS  MathSciNet  Google Scholar 

  • Wolf DE, Schreckenberg M, Bachem A (eds) (1995) Traffic and granular flow. In: Proceedings of the international workshop on traffic and granular flow. World Scientific, Singapore

    Google Scholar 

  • Xiao L, Gao F (2010) A comprehensive review of the development of adaptive cruise control systems. Veh Syst Dyn 48:1167–1192

    Article  ADS  Google Scholar 

  • Zurlinden H (2003) Ganzjahresanalyse des Verkehrsflusses auf Straßen. Schriftenreihe des Lehrstuhls für Verkehrswesen der Ruhr-Universität Bochum, Heft 26, Bochum

    Google Scholar 

Download references

Acknowledgments

I would like to thank Sergey Klenov and Hubert Rehborn for the help and useful suggestions. I thank our partners for their support in the projects “UR:BAN – Urban Space: User oriented assistance systems and network management” and “MEC-View – Object detection for automated driving based on Mobile Edge Computing,” funded by the German Federal Ministry of Economic Affairs and Energy.

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Correspondence to Boris S. Kemer .

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Kemer, B.S. (2017). Traffic Networks, Breakdown in. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27737-5_701-1

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