June  2019, 14(2): 265-288. doi: 10.3934/nhm.2019011

Derivation of second order traffic flow models with time delays

1. 

Fraunhofer Institute ITWM, 67663 Kaiserslautern, Germany

2. 

University of Mannheim, Department of Mathematics, 68131 Mannheim, Germany

 

Received  December 2017 Revised  December 2018 Published  April 2019

Fund Project: S. Göttlich acknowledges funding by the German Research Foundation under grant GO 1920/4-1.

Starting from microscopic follow-the-leader models, we develop hyperbolic delay partial differential equations to govern the density and velocity of vehicular traffic. The proposed models can be seen as an extension of the classical Aw-Rascle-Zhang model, where the reaction time of drivers appears as an additional term in the velocity equation. We propose numerical methods based on first principles and present a numerical study, where we focus on the impact of time delays in comparison to undelayed models.

Citation: Michael Burger, Simone Göttlich, Thomas Jung. Derivation of second order traffic flow models with time delays. Networks & Heterogeneous Media, 2019, 14 (2) : 265-288. doi: 10.3934/nhm.2019011
References:
[1]

A. Ashyralyev and D. Agirseven, Well-posedness of delay parabolic difference equations, Adv. Difference Equ., 2014 (2014), 20pp. doi: 10.1186/1687-1847-2014-18.  Google Scholar

[2]

A. Ashyralyev and D. Agirseven, Bounded Solutions of nonlinear hyperbolic equations with time delay, Electron. J. Differential Equations, 2018 (2018), Paper No. 21, 15 pp.  Google Scholar

[3]

A. Aw and M. Rascle, Resurrection of "second order" models of traffic flow, SIAM J. Appl. Math., 60 (2000), 916-938.  doi: 10.1137/S0036139997332099.  Google Scholar

[4]

A. AwA. KlarT. Materne and M. Rascle, Derivation of continuum traffic flow models from microscopic follow-the-leader models, SIAM J. Appl. Math., 63 (2002), 259-278.  doi: 10.1137/S0036139900380955.  Google Scholar

[5] A. Bellen and M. Zennaro, Numerical Methods for Delay Differential Equations, Oxford University Press, Oxford, 2013.   Google Scholar
[6]

M. Brackstone and M. Mcdonald, Car-following: A historical review, Transportation Research Part F: Traffic Psychology and Behaviour, 2 (1999), 181-196.  doi: 10.1016/S1369-8478(00)00005-X.  Google Scholar

[7]

R. E. ChandlerR. Herman and E. W. Montroll, Traffic dynamics: Studies in car following, Operations Res., 6 (1958), 165-184.  doi: 10.1287/opre.6.2.165.  Google Scholar

[8]

R. M. CorlessG. H. GonnetD. E. G. HareD. J. Jeffrey and D. E. Knuth, On the Lambert W Function, Adv. Comput. Math, 5 (1996), 329-356.  doi: 10.1007/BF02124750.  Google Scholar

[9]

C. D'Apice and B. Piccoli, Vertex flow models for vehicular traffic on networks, Math. Models Methods Appl. Sci., 18 (2008), 1299-1315.  doi: 10.1142/S0218202508003042.  Google Scholar

[10]

C.F. Daganzo, Requiem for second-order fluid approximations of traffic flow, Transportation Research Part B: Methodological, 29 (1995), 277-286.  doi: 10.1016/0191-2615(95)00007-Z.  Google Scholar

[11]

N. DavoodiA. R. Soheili and S. M. Hashemi, A macro-model for traffic flow with consideration of driver's reaction time and distance, Nonlinear Dynam., 83 (2016), 1621-1628.  doi: 10.1007/s11071-015-2435-0.  Google Scholar

[12]

G. Emch, Coarse-graining in Liouville space and master equation, Helv. Phys. Acta, 37 (1964), 532-544.   Google Scholar

[13]

S. Fan and B. Seibold, Effect of the choice of stagnation density in data-fitted first- and second-order traffic models, preprint, arXiv: 1308.0393. Google Scholar

[14]

S. FanM. Herty and B. Seibold, Comparative model accuracy of a data-fitted generalized Aw-Rascle-Zhang model, Netw. Heterog. Media, 9 (2014), 239-268.  doi: 10.3934/nhm.2014.9.239.  Google Scholar

[15]

M. Garavello and B. Piccoli, Traffic Flow on Networks, American Institute of Mathematical Sciences (AIMS), Springfield, MO, 2006.  Google Scholar

[16]

S. Gottlieb and C.-W. Shu, Total variation diminishing Runge-Kutta schemes, Math. Comp., 67 (1998), 73-85.  doi: 10.1090/S0025-5718-98-00913-2.  Google Scholar

[17]

A. Harten, High resolution schemes for hyperbolic conservation laws, J. Comput. Phys., 135 (1997), 259-278.  doi: 10.1006/jcph.1997.5725.  Google Scholar

[18]

D. Helbing, Verkehrsdynamik: Neue Physikalische Modellierungskonzepte, Springer Berlin Heidelberg, 1997. Google Scholar

[19]

S. P. Hoogendoorn and P. H. Bovy, State-of-the-art of vehicular traffic flow modelling, Proceedings of the Institution of Mechanical Engineers, Part Ⅰ: Journal of Systems and Control Engineering, 215 (2001), 283–303. doi: 10.1177/095965180121500402.  Google Scholar

[20]

W.-F. Jiang and Z. Wang, Developing an Aw-Rascle model of traffic flow, J. Engrg. Math., 97 (2016), 135-146.  doi: 10.1007/s10665-015-9801-2.  Google Scholar

[21]

E. Kometani and T. Sasaki, On the stability of traffic flow (Report-I), J. Op. Res. Japan, 2 (1958), 11-26.   Google Scholar

[22]

H. K. Lee, H.-W. Lee and D. Kim, Macroscopic traffic models from microscopic car-following models, Physical Review E, 64 (2001), 056126. doi: 10.1103/PhysRevE.64.056126.  Google Scholar

[23]

R. J. LeVeque, Finite Volume Methods for Hyperbolic Problems, 31st edition, Cambridge University Press, 2002. doi: 10.1017/CBO9780511791253.  Google Scholar

[24]

R. J. LeVeque, Numerical Methods for Conservation Laws, 2nd edition, Birkhäuser Verlag, Basel, 1992. doi: 10.1007/978-3-0348-8629-1.  Google Scholar

[25]

F. Maghami Asl and A. Ulsoy, Analysis of a system of linear delay differential equations, Journal of Dynamic Systems, Measurement, and Control, 125 (2003), 215-223.  doi: 10.1115/1.1568121.  Google Scholar

[26]

D. Ngoduy, Generalized macroscopic traffic model with time delay, Nonlinear Dynam., 77 (2014), 289-296.  doi: 10.1007/s11071-014-1293-5.  Google Scholar

[27]

H. J. Payne, Models of freeway traffic and control, Mathematical Models of Public Systems, Simulation Council Proceedings, (1971), 51–61. Google Scholar

[28]

RTMC Data Set, Available from: http://data.dot.state.mn.us/datatools/. Google Scholar

[29]

C.-W. Shu, TVB uniformly high-order schemes for conservation laws, Math. Comp., 49 (1987), 105-121.  doi: 10.1090/S0025-5718-1987-0890256-5.  Google Scholar

[30]

A. TordeuxG. CostesequeM. Herty and A. Seyfried, From traffic and pedestrian follow-the-leader models with reaction time to first order convection-diffusion flow models, SIAM J. Appl. Math., 78 (2018), 63-79.  doi: 10.1137/16M110695X.  Google Scholar

[31]

C. Travis and G. Webb, Existence and Stability for Partial Functional Differential Equations, Transactions of the American Mathematical Society, 200 (1974), 395-418.  doi: 10.1090/S0002-9947-1974-0382808-3.  Google Scholar

[32]

M. Treiber and A. Kesting, Traffic Flow Dynamics, Springer, Heidelberg, 2013. doi: 10.1007/978-3-642-32460-4.  Google Scholar

[33]

G. B. Whitham, Linear and Nonlinear Waves, John Wiley & Sons, Inc., New York, 1999. doi: 10.1002/9781118032954.  Google Scholar

show all references

References:
[1]

A. Ashyralyev and D. Agirseven, Well-posedness of delay parabolic difference equations, Adv. Difference Equ., 2014 (2014), 20pp. doi: 10.1186/1687-1847-2014-18.  Google Scholar

[2]

A. Ashyralyev and D. Agirseven, Bounded Solutions of nonlinear hyperbolic equations with time delay, Electron. J. Differential Equations, 2018 (2018), Paper No. 21, 15 pp.  Google Scholar

[3]

A. Aw and M. Rascle, Resurrection of "second order" models of traffic flow, SIAM J. Appl. Math., 60 (2000), 916-938.  doi: 10.1137/S0036139997332099.  Google Scholar

[4]

A. AwA. KlarT. Materne and M. Rascle, Derivation of continuum traffic flow models from microscopic follow-the-leader models, SIAM J. Appl. Math., 63 (2002), 259-278.  doi: 10.1137/S0036139900380955.  Google Scholar

[5] A. Bellen and M. Zennaro, Numerical Methods for Delay Differential Equations, Oxford University Press, Oxford, 2013.   Google Scholar
[6]

M. Brackstone and M. Mcdonald, Car-following: A historical review, Transportation Research Part F: Traffic Psychology and Behaviour, 2 (1999), 181-196.  doi: 10.1016/S1369-8478(00)00005-X.  Google Scholar

[7]

R. E. ChandlerR. Herman and E. W. Montroll, Traffic dynamics: Studies in car following, Operations Res., 6 (1958), 165-184.  doi: 10.1287/opre.6.2.165.  Google Scholar

[8]

R. M. CorlessG. H. GonnetD. E. G. HareD. J. Jeffrey and D. E. Knuth, On the Lambert W Function, Adv. Comput. Math, 5 (1996), 329-356.  doi: 10.1007/BF02124750.  Google Scholar

[9]

C. D'Apice and B. Piccoli, Vertex flow models for vehicular traffic on networks, Math. Models Methods Appl. Sci., 18 (2008), 1299-1315.  doi: 10.1142/S0218202508003042.  Google Scholar

[10]

C.F. Daganzo, Requiem for second-order fluid approximations of traffic flow, Transportation Research Part B: Methodological, 29 (1995), 277-286.  doi: 10.1016/0191-2615(95)00007-Z.  Google Scholar

[11]

N. DavoodiA. R. Soheili and S. M. Hashemi, A macro-model for traffic flow with consideration of driver's reaction time and distance, Nonlinear Dynam., 83 (2016), 1621-1628.  doi: 10.1007/s11071-015-2435-0.  Google Scholar

[12]

G. Emch, Coarse-graining in Liouville space and master equation, Helv. Phys. Acta, 37 (1964), 532-544.   Google Scholar

[13]

S. Fan and B. Seibold, Effect of the choice of stagnation density in data-fitted first- and second-order traffic models, preprint, arXiv: 1308.0393. Google Scholar

[14]

S. FanM. Herty and B. Seibold, Comparative model accuracy of a data-fitted generalized Aw-Rascle-Zhang model, Netw. Heterog. Media, 9 (2014), 239-268.  doi: 10.3934/nhm.2014.9.239.  Google Scholar

[15]

M. Garavello and B. Piccoli, Traffic Flow on Networks, American Institute of Mathematical Sciences (AIMS), Springfield, MO, 2006.  Google Scholar

[16]

S. Gottlieb and C.-W. Shu, Total variation diminishing Runge-Kutta schemes, Math. Comp., 67 (1998), 73-85.  doi: 10.1090/S0025-5718-98-00913-2.  Google Scholar

[17]

A. Harten, High resolution schemes for hyperbolic conservation laws, J. Comput. Phys., 135 (1997), 259-278.  doi: 10.1006/jcph.1997.5725.  Google Scholar

[18]

D. Helbing, Verkehrsdynamik: Neue Physikalische Modellierungskonzepte, Springer Berlin Heidelberg, 1997. Google Scholar

[19]

S. P. Hoogendoorn and P. H. Bovy, State-of-the-art of vehicular traffic flow modelling, Proceedings of the Institution of Mechanical Engineers, Part Ⅰ: Journal of Systems and Control Engineering, 215 (2001), 283–303. doi: 10.1177/095965180121500402.  Google Scholar

[20]

W.-F. Jiang and Z. Wang, Developing an Aw-Rascle model of traffic flow, J. Engrg. Math., 97 (2016), 135-146.  doi: 10.1007/s10665-015-9801-2.  Google Scholar

[21]

E. Kometani and T. Sasaki, On the stability of traffic flow (Report-I), J. Op. Res. Japan, 2 (1958), 11-26.   Google Scholar

[22]

H. K. Lee, H.-W. Lee and D. Kim, Macroscopic traffic models from microscopic car-following models, Physical Review E, 64 (2001), 056126. doi: 10.1103/PhysRevE.64.056126.  Google Scholar

[23]

R. J. LeVeque, Finite Volume Methods for Hyperbolic Problems, 31st edition, Cambridge University Press, 2002. doi: 10.1017/CBO9780511791253.  Google Scholar

[24]

R. J. LeVeque, Numerical Methods for Conservation Laws, 2nd edition, Birkhäuser Verlag, Basel, 1992. doi: 10.1007/978-3-0348-8629-1.  Google Scholar

[25]

F. Maghami Asl and A. Ulsoy, Analysis of a system of linear delay differential equations, Journal of Dynamic Systems, Measurement, and Control, 125 (2003), 215-223.  doi: 10.1115/1.1568121.  Google Scholar

[26]

D. Ngoduy, Generalized macroscopic traffic model with time delay, Nonlinear Dynam., 77 (2014), 289-296.  doi: 10.1007/s11071-014-1293-5.  Google Scholar

[27]

H. J. Payne, Models of freeway traffic and control, Mathematical Models of Public Systems, Simulation Council Proceedings, (1971), 51–61. Google Scholar

[28]

RTMC Data Set, Available from: http://data.dot.state.mn.us/datatools/. Google Scholar

[29]

C.-W. Shu, TVB uniformly high-order schemes for conservation laws, Math. Comp., 49 (1987), 105-121.  doi: 10.1090/S0025-5718-1987-0890256-5.  Google Scholar

[30]

A. TordeuxG. CostesequeM. Herty and A. Seyfried, From traffic and pedestrian follow-the-leader models with reaction time to first order convection-diffusion flow models, SIAM J. Appl. Math., 78 (2018), 63-79.  doi: 10.1137/16M110695X.  Google Scholar

[31]

C. Travis and G. Webb, Existence and Stability for Partial Functional Differential Equations, Transactions of the American Mathematical Society, 200 (1974), 395-418.  doi: 10.1090/S0002-9947-1974-0382808-3.  Google Scholar

[32]

M. Treiber and A. Kesting, Traffic Flow Dynamics, Springer, Heidelberg, 2013. doi: 10.1007/978-3-642-32460-4.  Google Scholar

[33]

G. B. Whitham, Linear and Nonlinear Waves, John Wiley & Sons, Inc., New York, 1999. doi: 10.1002/9781118032954.  Google Scholar

Figure 5.  Comparison for contact discontinuity: numerical RSD and ARZ solutions vs. analytical ARZ
Figure 6.  Comparison for shock solution: numerical RSD and ARZ solutions vs. analytical ARZ
Figure 7.  Comparison for rarefaction wave: numerical RSD and ARZ solutions vs. analytical ARZ
Figure 1.  Real parts $ \lambda_2 $ for $ \gamma = 0. $
Figure 2.  Time evolution of density and flux of the delayed microscopic and macroscopic models for $ T = 0.5 $
Figure 3.  Zoom: Time evolution of density and flux of the delayed microscopic and macroscopic models for $ T = 0.5 $
Figure 4.  Convergence of the microscopic to the macroscopic models at time $ t = 10 $ and fixed delay $ T = 0.5 $
Figure 8.  Comparison of macroscopic models for $ T = 0.5 $ with Zoom
Figure 9.  Comparison of macroscopic models for $ T = 5 $ with Zoom
Figure 10.  Comparison TE model and convection-diffusion flow model for $ T = 0.5 $
Figure 11.  Traffic light scenario
Figure 12.  Density for the delayed model
Figure 13.  Density for the undelayed model
Figure 14.  Speed over time at the end of the road in the Traffic Light Situation
Figure 15.  Fundamental relation between density and flux and fitted function
Figure 16.  Comparison of the data-fitted delayed and undelayed ARZ model to real data
Table 1.  Comparison of errors for different $ \Delta x $
$ \Delta x $ 5 1 0.5 0.1
RSD $ ||\cdot||_{2} $-Error 0.074 0.0759 0.0706 0.0335
RSD $ ||\cdot||_{\infty} $-Error 0.038 0.0337 0.027 0.0288
CG $ ||\cdot||_{2} $-Error 0.0727 0.0746 0.0692 0.0308
CG $ ||\cdot||_{\infty} $-Error 0.036 0.0305 0.0236 0.0288
TE $ ||\cdot||_{2} $-Error 0.0651 0.0683 0.0657 0.0486
TE $ ||\cdot||_{\infty} $-Error 0.0223 0.0181 0.0236 0.0288
$ \Delta x $ 5 1 0.5 0.1
RSD $ ||\cdot||_{2} $-Error 0.074 0.0759 0.0706 0.0335
RSD $ ||\cdot||_{\infty} $-Error 0.038 0.0337 0.027 0.0288
CG $ ||\cdot||_{2} $-Error 0.0727 0.0746 0.0692 0.0308
CG $ ||\cdot||_{\infty} $-Error 0.036 0.0305 0.0236 0.0288
TE $ ||\cdot||_{2} $-Error 0.0651 0.0683 0.0657 0.0486
TE $ ||\cdot||_{\infty} $-Error 0.0223 0.0181 0.0236 0.0288
[1]

Lorenzo Zambotti. A brief and personal history of stochastic partial differential equations. Discrete & Continuous Dynamical Systems - A, 2021, 41 (1) : 471-487. doi: 10.3934/dcds.2020264

[2]

Yueyang Zheng, Jingtao Shi. A stackelberg game of backward stochastic differential equations with partial information. Mathematical Control & Related Fields, 2020  doi: 10.3934/mcrf.2020047

[3]

Marion Darbas, Jérémy Heleine, Stephanie Lohrengel. Numerical resolution by the quasi-reversibility method of a data completion problem for Maxwell's equations. Inverse Problems & Imaging, 2020, 14 (6) : 1107-1133. doi: 10.3934/ipi.2020056

[4]

Fathalla A. Rihan, Hebatallah J. Alsakaji. Stochastic delay differential equations of three-species prey-predator system with cooperation among prey species. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020468

[5]

Siyang Cai, Yongmei Cai, Xuerong Mao. A stochastic differential equation SIS epidemic model with regime switching. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2020317

[6]

Xin-Guang Yang, Lu Li, Xingjie Yan, Ling Ding. The structure and stability of pullback attractors for 3D Brinkman-Forchheimer equation with delay. Electronic Research Archive, 2020, 28 (4) : 1395-1418. doi: 10.3934/era.2020074

[7]

Leilei Wei, Yinnian He. A fully discrete local discontinuous Galerkin method with the generalized numerical flux to solve the tempered fractional reaction-diffusion equation. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2020319

[8]

Juan Pablo Pinasco, Mauro Rodriguez Cartabia, Nicolas Saintier. Evolutionary game theory in mixed strategies: From microscopic interactions to kinetic equations. Kinetic & Related Models, , () : -. doi: 10.3934/krm.2020051

[9]

Gunther Uhlmann, Jian Zhai. Inverse problems for nonlinear hyperbolic equations. Discrete & Continuous Dynamical Systems - A, 2021, 41 (1) : 455-469. doi: 10.3934/dcds.2020380

[10]

Andy Hammerlindl, Jana Rodriguez Hertz, Raúl Ures. Ergodicity and partial hyperbolicity on Seifert manifolds. Journal of Modern Dynamics, 2020, 16: 331-348. doi: 10.3934/jmd.2020012

[11]

Hua Qiu, Zheng-An Yao. The regularized Boussinesq equations with partial dissipations in dimension two. Electronic Research Archive, 2020, 28 (4) : 1375-1393. doi: 10.3934/era.2020073

[12]

Ilyasse Lamrani, Imad El Harraki, Ali Boutoulout, Fatima-Zahrae El Alaoui. Feedback stabilization of bilinear coupled hyperbolic systems. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020434

[13]

Anna Abbatiello, Eduard Feireisl, Antoní Novotný. Generalized solutions to models of compressible viscous fluids. Discrete & Continuous Dynamical Systems - A, 2021, 41 (1) : 1-28. doi: 10.3934/dcds.2020345

[14]

Fabio Camilli, Giulia Cavagnari, Raul De Maio, Benedetto Piccoli. Superposition principle and schemes for measure differential equations. Kinetic & Related Models, , () : -. doi: 10.3934/krm.2020050

[15]

Wei Feng, Michael Freeze, Xin Lu. On competition models under allee effect: Asymptotic behavior and traveling waves. Communications on Pure & Applied Analysis, 2020, 19 (12) : 5609-5626. doi: 10.3934/cpaa.2020256

[16]

Mark F. Demers. Uniqueness and exponential mixing for the measure of maximal entropy for piecewise hyperbolic maps. Discrete & Continuous Dynamical Systems - A, 2021, 41 (1) : 217-256. doi: 10.3934/dcds.2020217

[17]

Dan Zhu, Rosemary A. Renaut, Hongwei Li, Tianyou Liu. Fast non-convex low-rank matrix decomposition for separation of potential field data using minimal memory. Inverse Problems & Imaging, , () : -. doi: 10.3934/ipi.2020076

[18]

Giuseppina Guatteri, Federica Masiero. Stochastic maximum principle for problems with delay with dependence on the past through general measures. Mathematical Control & Related Fields, 2020  doi: 10.3934/mcrf.2020048

[19]

Zexuan Liu, Zhiyuan Sun, Jerry Zhijian Yang. A numerical study of superconvergence of the discontinuous Galerkin method by patch reconstruction. Electronic Research Archive, 2020, 28 (4) : 1487-1501. doi: 10.3934/era.2020078

[20]

Vieri Benci, Marco Cococcioni. The algorithmic numbers in non-archimedean numerical computing environments. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020449

2019 Impact Factor: 1.053

Metrics

  • PDF downloads (207)
  • HTML views (487)
  • Cited by (0)

Other articles
by authors

[Back to Top]