September  2011, 6(3): 351-381. doi: 10.3934/nhm.2011.6.351

Two-way multi-lane traffic model for pedestrians in corridors

1. 

1-University Paris-Sud, Laboratory of Theoretical Physics, Batiment 210, F-91405 ORSAY Cedex, France

2. 

1-Université de Toulouse; UPS, INSA, UT1, UTM, Institut de Mathématiques de Toulouse, F-31062 Toulouse

3. 

5-Department of Mathematics, University of Maryland, College Park, MD 20742-4015, United States

Received  December 2010 Revised  April 2011 Published  August 2011

We extend the Aw-Rascle macroscopic model of car traffic into a two-way multi-lane model of pedestrian traffic. Within this model, we propose a technique for the handling of the congestion constraint, i.e. the fact that the pedestrian density cannot exceed a maximal density corresponding to contact between pedestrians. In a first step, we propose a singularly perturbed pressure relation which models the fact that the pedestrian velocity is considerably reduced, if not blocked, at congestion. In a second step, we carry over the singular limit into the model and show that abrupt transitions between compressible flow (in the uncongested regions) to incompressible flow (in congested regions) occur. We also investigate the hyperbolicity of the two-way models and show that they can lose their hyperbolicity in some cases. We study a diffusive correction of these models and discuss the characteristic time and length scales of the instability.
Citation: Cécile Appert-Rolland, Pierre Degond, Sébastien Motsch. Two-way multi-lane traffic model for pedestrians in corridors. Networks & Heterogeneous Media, 2011, 6 (3) : 351-381. doi: 10.3934/nhm.2011.6.351
References:
[1]

S. Al-nasur and P. Kachroo, "A Microscopic-to-Macroscopic Crowd Dynamic Model,", Proceedings of the IEEE ITSC 2006, (2006), 17.   Google Scholar

[2]

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

[3]

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

[4]

N. Bellomo and C. Dogbé, On the modelling crowd dynamics: From scaling to second order hyperbolic macroscopic models,, Math. Models Methods Appl. Sci., 18 (2008), 1317.  doi: 10.1142/S0218202508003054.  Google Scholar

[5]

S. Benzoni-Gavage and R. M. Colombo, An $n$-populations model for traffic flow,, European J. Appl. Math., 14 (2003), 587.  doi: 10.1017/S0956792503005266.  Google Scholar

[6]

F. Berthelin, P. Degond, M. Delitala and M. Rascle, A model for the formation and evolution of traffic jams,, Arch. Rat. Mech. Anal., 187 (2008), 185.  doi: 10.1007/s00205-007-0061-9.  Google Scholar

[7]

F. Berthelin, P. Degond, V. Le Blanc, S. Moutari, J. Royer and M. Rascle, A traffic-flow model with constraints for the modeling of traffic jams,, Math. Models Methods Appl. Sci., 18 (2008), 1269.  doi: 10.1142/S0218202508003030.  Google Scholar

[8]

F. Bouchut, Y. Brenier, J. Cortes and J. F. Ripoll, A hierachy of models for two-phase flows,, J. Nonlinear Sci., 10 (2000), 639.  doi: 10.1007/s003320010006.  Google Scholar

[9]

C. Burstedde, K. Klauck, A. Schadschneider and J. Zittarz, Simulation of pedestrian dynamics using a 2-dimensional cellular automaton,, Physica A, 295 (2001), 507.  doi: 10.1016/S0378-4371(01)00141-8.  Google Scholar

[10]

C. Chalons, Numerical approximation of a macroscopic model of pedestrian flows,, SIAM J. Sci. Comput., 29 (2007), 539.  doi: 10.1137/050641211.  Google Scholar

[11]

R. M. Colombo and M. D. Rosini, Pedestrian flows and nonclassical shocks,, Math. Methods Appl. Sci., 28 (2005), 1553.  doi: 10.1002/mma.624.  Google Scholar

[12]

C. Daganzo, Requiem for second order fluid approximations of traffic flow,, Transp. Res. B, 29 (1995), 277.  doi: 10.1016/0191-2615(95)00007-Z.  Google Scholar

[13]

P. Degond and M. Delitala, Modelling and simulation of vehicular traffic jam formation,, Kinet. Relat. Models, 1 (2008), 279.  doi: 10.3934/krm.2008.1.279.  Google Scholar

[14]

P. Degond, J. Hua and L. Navoret, Numerical simulations of the Euler system with congestion constraint,, preprint, ().   Google Scholar

[15]

P. Degond and M. Tang, All speed scheme for the low Mach number limit of the isentropic Euler equations,, Commun. Comput. Phys., 10 (2011), 1.   Google Scholar

[16]

R. Y. Guo and H. J. Huang, A mobile lattice gas model for simulating pedestrian evacuation,, Physica A, 387 (2008), 580.  doi: 10.1016/j.physa.2007.10.001.  Google Scholar

[17]

S. J. Guy, J. Chhugani, C. Kim, N. Satish, M. C. Lin, D. Manocha and P. Dubey, "Clearpath: Highly Parallel Collision Avoidance for Multi-Agent Simulation,", ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA), (2009), 177.   Google Scholar

[18]

D. Helbing, A mathematical model for the behavior of pedestrians,, Behavioral Science, 36 (1991), 298.  doi: 10.1002/bs.3830360405.  Google Scholar

[19]

D. Helbing, A fluid-dynamic model for the movement of pedestrians,, Complex Systems, 6 (1992), 391.   Google Scholar

[20]

D. Helbing and P. Molnàr, Social force model for pedestrian dynamics,, Physical Review E, 51 (1995), 4282.  doi: 10.1103/PhysRevE.51.4282.  Google Scholar

[21]

D. Helbing and P. Molnàr, Self-organization of complex structures. From individual to collective dynamics,, Proceedings of the International Conference held in Berlin, (1995), 24.   Google Scholar

[22]

L. F. Henderson, On the fluid mechanics of human crowd motion,, Transportation Research, 8 (1974), 509.  doi: 10.1016/0041-1647(74)90027-6.  Google Scholar

[23]

S. Hoogendoorn and P. H. L. Bovy, Simulation of pedestrian flows by optimal control and differential games,, Optimal Control Appl. Methods, 24 (2003), 153.  doi: 10.1002/oca.727.  Google Scholar

[24]

R. L. Hughes, A continuum theory for the flow of pedestrians,, Transportation Research B, 36 (2002), 507.  doi: 10.1016/S0191-2615(01)00015-7.  Google Scholar

[25]

R. L. Hughes, The flow of human crowds,, Ann. Rev. Fluid Mech., 35 (2003), 169.  doi: 10.1146/annurev.fluid.35.101101.161136.  Google Scholar

[26]

A. Kurganov and E. Tadmor, New high-resolution central schemes for nonlinear conservation laws and convection-diffusion equations,, J. Comput. Phys., 160 (2000), 240.   Google Scholar

[27]

R. J. LeVeque, "Finite Volume Methods for Hyperbolic Problems,", Cambridge Texts in Mathematics, (2002).  doi: 10.1017/CBO9780511791253.  Google Scholar

[28]

M. J. Lighthill and J. B. Whitham, On kinematic waves. I: Flow movement in long rivers. II: A theory of traffic flow on long crowded roads,, Proc. Roy. Soc., A229 (1955), 281.   Google Scholar

[29]

B. Maury, A. Roudneff-Chupin and F. Santambrogio, A macroscopic crowd motion model of gradient flow type,, Math. Models Methods Appl. Sci., 20 (2010), 1787.  doi: 10.1142/S0218202510004799.  Google Scholar

[30]

B. Maury and J. Venel, A mathematical framework for a crowd motion model,, C. R. Acad. Sci. Paris, 346 (2008), 1245.   Google Scholar

[31]

K. Nishinari, A. Kirchner, A. Namazi and A. Schadschneider, Extended floor field CA model for evacuation dynamics,, IEICE Transp. Inf. & Syst., E87-D (2004), 726.   Google Scholar

[32]

J. Ondřej, J. Pettré, A.-H. Olivier and S. Donikian, "A Synthetic-Vision Based Steering Approach for Crowd Simulation,", SIGGRAPH '10, (2010).   Google Scholar

[33]

S. Paris, J. Pettré and S. Donikian, Pedestrian reactive navigation for crowd simulation: A predictive approach,, Eurographics, 26 (2007), 665.   Google Scholar

[34]

Pedigree team, Pedestrian flow measurements and analysis in an annular setup,, in preparation., ().   Google Scholar

[35]

J. Pettré, J. Ondřej, A.-H. Olivier, A. Cretual and S. Donikian, "Experiment-Based Modeling, Simulation and Validation of Interactions Between Virtual Walkers,", SCA '09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, (2009), 189.   Google Scholar

[36]

B. Piccoli and A. Tosin, Pedestrian flows in bounded domains with obstacles,, Contin. Mech. Thermodyn., 21 (2009), 85.   Google Scholar

[37]

B. Piccoli and A. Tosin, Time-evolving measures and macroscopic modeling of pedestrian flow,, Arch. Ration. Mech. Anal., 199 (2011), 707.   Google Scholar

[38]

C. W. Reynolds, "Steering Behaviors for Autonomous Characters,", Proceedings of Game Developers Conference 1999, (1999), 763.   Google Scholar

[39]

V. Shvetsov and D. Helbing, Macroscopic dynamics of multi-lane traffic,, Phys. Rev. E, 59 (1999), 6328.  doi: 10.1103/PhysRevE.59.6328.  Google Scholar

[40]

J. van den Berg and H. Overmars, Planning time-minimal safe paths amidst unpredictably moving obstacles,, Int. Journal on Robotics Research, 27 (2008), 1274.  doi: 10.1177/0278364908097581.  Google Scholar

[41]

W. G. Weng, S. F. Shena, H. Y. Yuana and W. C. Fana, A behavior-based model for pedestrian counter flow,, Physica A, 375 (2007), 668.  doi: 10.1016/j.physa.2006.09.028.  Google Scholar

[42]

M. Zhang, A non-equilibrium traffic model devoid of gas-like behavior,, Transportation Res. B, 36 (2002), 275.  doi: 10.1016/S0191-2615(00)00050-3.  Google Scholar

show all references

References:
[1]

S. Al-nasur and P. Kachroo, "A Microscopic-to-Macroscopic Crowd Dynamic Model,", Proceedings of the IEEE ITSC 2006, (2006), 17.   Google Scholar

[2]

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

[3]

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

[4]

N. Bellomo and C. Dogbé, On the modelling crowd dynamics: From scaling to second order hyperbolic macroscopic models,, Math. Models Methods Appl. Sci., 18 (2008), 1317.  doi: 10.1142/S0218202508003054.  Google Scholar

[5]

S. Benzoni-Gavage and R. M. Colombo, An $n$-populations model for traffic flow,, European J. Appl. Math., 14 (2003), 587.  doi: 10.1017/S0956792503005266.  Google Scholar

[6]

F. Berthelin, P. Degond, M. Delitala and M. Rascle, A model for the formation and evolution of traffic jams,, Arch. Rat. Mech. Anal., 187 (2008), 185.  doi: 10.1007/s00205-007-0061-9.  Google Scholar

[7]

F. Berthelin, P. Degond, V. Le Blanc, S. Moutari, J. Royer and M. Rascle, A traffic-flow model with constraints for the modeling of traffic jams,, Math. Models Methods Appl. Sci., 18 (2008), 1269.  doi: 10.1142/S0218202508003030.  Google Scholar

[8]

F. Bouchut, Y. Brenier, J. Cortes and J. F. Ripoll, A hierachy of models for two-phase flows,, J. Nonlinear Sci., 10 (2000), 639.  doi: 10.1007/s003320010006.  Google Scholar

[9]

C. Burstedde, K. Klauck, A. Schadschneider and J. Zittarz, Simulation of pedestrian dynamics using a 2-dimensional cellular automaton,, Physica A, 295 (2001), 507.  doi: 10.1016/S0378-4371(01)00141-8.  Google Scholar

[10]

C. Chalons, Numerical approximation of a macroscopic model of pedestrian flows,, SIAM J. Sci. Comput., 29 (2007), 539.  doi: 10.1137/050641211.  Google Scholar

[11]

R. M. Colombo and M. D. Rosini, Pedestrian flows and nonclassical shocks,, Math. Methods Appl. Sci., 28 (2005), 1553.  doi: 10.1002/mma.624.  Google Scholar

[12]

C. Daganzo, Requiem for second order fluid approximations of traffic flow,, Transp. Res. B, 29 (1995), 277.  doi: 10.1016/0191-2615(95)00007-Z.  Google Scholar

[13]

P. Degond and M. Delitala, Modelling and simulation of vehicular traffic jam formation,, Kinet. Relat. Models, 1 (2008), 279.  doi: 10.3934/krm.2008.1.279.  Google Scholar

[14]

P. Degond, J. Hua and L. Navoret, Numerical simulations of the Euler system with congestion constraint,, preprint, ().   Google Scholar

[15]

P. Degond and M. Tang, All speed scheme for the low Mach number limit of the isentropic Euler equations,, Commun. Comput. Phys., 10 (2011), 1.   Google Scholar

[16]

R. Y. Guo and H. J. Huang, A mobile lattice gas model for simulating pedestrian evacuation,, Physica A, 387 (2008), 580.  doi: 10.1016/j.physa.2007.10.001.  Google Scholar

[17]

S. J. Guy, J. Chhugani, C. Kim, N. Satish, M. C. Lin, D. Manocha and P. Dubey, "Clearpath: Highly Parallel Collision Avoidance for Multi-Agent Simulation,", ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA), (2009), 177.   Google Scholar

[18]

D. Helbing, A mathematical model for the behavior of pedestrians,, Behavioral Science, 36 (1991), 298.  doi: 10.1002/bs.3830360405.  Google Scholar

[19]

D. Helbing, A fluid-dynamic model for the movement of pedestrians,, Complex Systems, 6 (1992), 391.   Google Scholar

[20]

D. Helbing and P. Molnàr, Social force model for pedestrian dynamics,, Physical Review E, 51 (1995), 4282.  doi: 10.1103/PhysRevE.51.4282.  Google Scholar

[21]

D. Helbing and P. Molnàr, Self-organization of complex structures. From individual to collective dynamics,, Proceedings of the International Conference held in Berlin, (1995), 24.   Google Scholar

[22]

L. F. Henderson, On the fluid mechanics of human crowd motion,, Transportation Research, 8 (1974), 509.  doi: 10.1016/0041-1647(74)90027-6.  Google Scholar

[23]

S. Hoogendoorn and P. H. L. Bovy, Simulation of pedestrian flows by optimal control and differential games,, Optimal Control Appl. Methods, 24 (2003), 153.  doi: 10.1002/oca.727.  Google Scholar

[24]

R. L. Hughes, A continuum theory for the flow of pedestrians,, Transportation Research B, 36 (2002), 507.  doi: 10.1016/S0191-2615(01)00015-7.  Google Scholar

[25]

R. L. Hughes, The flow of human crowds,, Ann. Rev. Fluid Mech., 35 (2003), 169.  doi: 10.1146/annurev.fluid.35.101101.161136.  Google Scholar

[26]

A. Kurganov and E. Tadmor, New high-resolution central schemes for nonlinear conservation laws and convection-diffusion equations,, J. Comput. Phys., 160 (2000), 240.   Google Scholar

[27]

R. J. LeVeque, "Finite Volume Methods for Hyperbolic Problems,", Cambridge Texts in Mathematics, (2002).  doi: 10.1017/CBO9780511791253.  Google Scholar

[28]

M. J. Lighthill and J. B. Whitham, On kinematic waves. I: Flow movement in long rivers. II: A theory of traffic flow on long crowded roads,, Proc. Roy. Soc., A229 (1955), 281.   Google Scholar

[29]

B. Maury, A. Roudneff-Chupin and F. Santambrogio, A macroscopic crowd motion model of gradient flow type,, Math. Models Methods Appl. Sci., 20 (2010), 1787.  doi: 10.1142/S0218202510004799.  Google Scholar

[30]

B. Maury and J. Venel, A mathematical framework for a crowd motion model,, C. R. Acad. Sci. Paris, 346 (2008), 1245.   Google Scholar

[31]

K. Nishinari, A. Kirchner, A. Namazi and A. Schadschneider, Extended floor field CA model for evacuation dynamics,, IEICE Transp. Inf. & Syst., E87-D (2004), 726.   Google Scholar

[32]

J. Ondřej, J. Pettré, A.-H. Olivier and S. Donikian, "A Synthetic-Vision Based Steering Approach for Crowd Simulation,", SIGGRAPH '10, (2010).   Google Scholar

[33]

S. Paris, J. Pettré and S. Donikian, Pedestrian reactive navigation for crowd simulation: A predictive approach,, Eurographics, 26 (2007), 665.   Google Scholar

[34]

Pedigree team, Pedestrian flow measurements and analysis in an annular setup,, in preparation., ().   Google Scholar

[35]

J. Pettré, J. Ondřej, A.-H. Olivier, A. Cretual and S. Donikian, "Experiment-Based Modeling, Simulation and Validation of Interactions Between Virtual Walkers,", SCA '09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, (2009), 189.   Google Scholar

[36]

B. Piccoli and A. Tosin, Pedestrian flows in bounded domains with obstacles,, Contin. Mech. Thermodyn., 21 (2009), 85.   Google Scholar

[37]

B. Piccoli and A. Tosin, Time-evolving measures and macroscopic modeling of pedestrian flow,, Arch. Ration. Mech. Anal., 199 (2011), 707.   Google Scholar

[38]

C. W. Reynolds, "Steering Behaviors for Autonomous Characters,", Proceedings of Game Developers Conference 1999, (1999), 763.   Google Scholar

[39]

V. Shvetsov and D. Helbing, Macroscopic dynamics of multi-lane traffic,, Phys. Rev. E, 59 (1999), 6328.  doi: 10.1103/PhysRevE.59.6328.  Google Scholar

[40]

J. van den Berg and H. Overmars, Planning time-minimal safe paths amidst unpredictably moving obstacles,, Int. Journal on Robotics Research, 27 (2008), 1274.  doi: 10.1177/0278364908097581.  Google Scholar

[41]

W. G. Weng, S. F. Shena, H. Y. Yuana and W. C. Fana, A behavior-based model for pedestrian counter flow,, Physica A, 375 (2007), 668.  doi: 10.1016/j.physa.2006.09.028.  Google Scholar

[42]

M. Zhang, A non-equilibrium traffic model devoid of gas-like behavior,, Transportation Res. B, 36 (2002), 275.  doi: 10.1016/S0191-2615(00)00050-3.  Google Scholar

[1]

Caterina Balzotti, Simone Göttlich. A two-dimensional multi-class traffic flow model. Networks & Heterogeneous Media, 2020  doi: 10.3934/nhm.2020034

[2]

Raimund Bürger, Christophe Chalons, Rafael Ordoñez, Luis Miguel Villada. A multiclass Lighthill-Whitham-Richards traffic model with a discontinuous velocity function. Networks & Heterogeneous Media, 2021  doi: 10.3934/nhm.2021004

[3]

Shipra Singh, Aviv Gibali, Xiaolong Qin. Cooperation in traffic network problems via evolutionary split variational inequalities. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2020170

[4]

Mahdi Karimi, Seyed Jafar Sadjadi. Optimization of a Multi-Item Inventory model for deteriorating items with capacity constraint using dynamic programming. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2021013

[5]

A. M. Elaiw, N. H. AlShamrani, A. Abdel-Aty, H. Dutta. Stability analysis of a general HIV dynamics model with multi-stages of infected cells and two routes of infection. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020441

[6]

Ömer Arslan, Selçuk Kürşat İşleyen. A model and two heuristic methods for The Multi-Product Inventory-Location-Routing Problem with heterogeneous fleet. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2021002

[7]

Kengo Nakai, Yoshitaka Saiki. Machine-learning construction of a model for a macroscopic fluid variable using the delay-coordinate of a scalar observable. Discrete & Continuous Dynamical Systems - S, 2021, 14 (3) : 1079-1092. doi: 10.3934/dcdss.2020352

[8]

Gi-Chan Bae, Christian Klingenberg, Marlies Pirner, Seok-Bae Yun. BGK model of the multi-species Uehling-Uhlenbeck equation. Kinetic & Related Models, 2021, 14 (1) : 25-44. doi: 10.3934/krm.2020047

[9]

Zhouchao Wei, Wei Zhang, Irene Moroz, Nikolay V. Kuznetsov. Codimension one and two bifurcations in Cattaneo-Christov heat flux model. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2020344

[10]

Yanhong Zhang. Global attractors of two layer baroclinic quasi-geostrophic model. Discrete & Continuous Dynamical Systems - B, 2021  doi: 10.3934/dcdsb.2021023

[11]

H. M. Srivastava, H. I. Abdel-Gawad, Khaled Mohammed Saad. Oscillatory states and patterns formation in a two-cell cubic autocatalytic reaction-diffusion model subjected to the Dirichlet conditions. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020433

[12]

Lu Xu, Chunlai Mu, Qiao Xin. Global boundedness of solutions to the two-dimensional forager-exploiter model with logistic source. Discrete & Continuous Dynamical Systems - A, 2020  doi: 10.3934/dcds.2020396

[13]

Yan'e Wang, Nana Tian, Hua Nie. Positive solution branches of two-species competition model in open advective environments. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2021006

[14]

Simone Göttlich, Elisa Iacomini, Thomas Jung. Properties of the LWR model with time delay. Networks & Heterogeneous Media, 2020  doi: 10.3934/nhm.2020032

[15]

Ténan Yeo. Stochastic and deterministic SIS patch model. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2021012

[16]

M. Dambrine, B. Puig, G. Vallet. A mathematical model for marine dinoflagellates blooms. Discrete & Continuous Dynamical Systems - S, 2021, 14 (2) : 615-633. doi: 10.3934/dcdss.2020424

[17]

Craig Cowan, Abdolrahman Razani. Singular solutions of a Lane-Emden system. Discrete & Continuous Dynamical Systems - A, 2021, 41 (2) : 621-656. doi: 10.3934/dcds.2020291

[18]

Laurence Cherfils, Stefania Gatti, Alain Miranville, Rémy Guillevin. Analysis of a model for tumor growth and lactate exchanges in a glioma. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020457

[19]

Laurent Di Menza, Virginie Joanne-Fabre. An age group model for the study of a population of trees. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020464

[20]

Eduard Feireisl, Elisabetta Rocca, Giulio Schimperna, Arghir Zarnescu. Weak sequential stability for a nonlinear model of nematic electrolytes. Discrete & Continuous Dynamical Systems - S, 2021, 14 (1) : 219-241. doi: 10.3934/dcdss.2020366

2019 Impact Factor: 1.053

Metrics

  • PDF downloads (69)
  • HTML views (0)
  • Cited by (30)

[Back to Top]