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

Cécile Appert-Rolland; Pierre Degond; Sébastien Motsch

doi:10.3934/nhm.2011.6.351

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Preface

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

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

Cécile Appert-Rolland ^1, , Pierre Degond ^2, and Sébastien Motsch ^3,

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

Abstract
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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.

Keywords: Pedestrian traffic, Congestion constraint., two-way traffic, Aw-Rascle model, macroscopic model, multi-lane traffic.

Mathematics Subject Classification: 90B20, 35L60, 35L65, 35L67, 35R99, 76L0.

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 IEEE Intelligent Transportation Systems Conference, Toronto, Canada, September, (2006), 17-20. 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), 259-278. 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), 916-938. 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), 1317-1345. 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), 587-612. 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), 185-220. doi: 10.1007/s00205-007-0061-9. Google Scholar
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[9]	C. Burstedde, K. Klauck, A. Schadschneider and J. Zittarz, Simulation of pedestrian dynamics using a 2-dimensional cellular automaton, Physica A, 295 (2001), 507-525, arXiv:cond-mat/0102397. 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), 539-555. 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), 1553-1567. doi: 10.1002/mma.624. Google Scholar
[12]	C. Daganzo, Requiem for second order fluid approximations of traffic flow, Transp. Res. B, 29 (1995), 277-286. 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), 279-293. 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), 1-31, arXiv:0908.1929. Google Scholar
[16]	R. Y. Guo and H. J. Huang, A mobile lattice gas model for simulating pedestrian evacuation, Physica A, 387 (2008), 580-586. 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), 177-187. Google Scholar
[18]	D. Helbing, A mathematical model for the behavior of pedestrians, Behavioral Science, 36 (1991), 298-310. doi: 10.1002/bs.3830360405. Google Scholar
[19]	D. Helbing, A fluid-dynamic model for the movement of pedestrians, Complex Systems, 6 (1992), 391-415. Google Scholar
[20]	D. Helbing and P. Molnàr, Social force model for pedestrian dynamics, Physical Review E, 51 (1995), 4282-4286. 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, September 24-28, 1995, Edited by Frank Schweitzer. Gordon and Breach Science Publishers, Amsterdam, 1997. Google Scholar
[22]	L. F. Henderson, On the fluid mechanics of human crowd motion, Transportation Research, 8 (1974), 509-515. 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), 153-172. doi: 10.1002/oca.727. Google Scholar
[24]	R. L. Hughes, A continuum theory for the flow of pedestrians, Transportation Research B, 36 (2002), 507-535. 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), 169-182. 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), 240-282. Google Scholar
[27]	R. J. LeVeque, "Finite Volume Methods for Hyperbolic Problems," Cambridge Texts in Mathematics, Cambridge University Press, Cambridge, 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), 281-345. 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), 1787-1821. 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), 1245-1250. 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), 726-732, arXiv:cond-mat/0306262. 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), 665-674. 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), 189-198. Google Scholar
[36]	B. Piccoli and A. Tosin, Pedestrian flows in bounded domains with obstacles, Contin. Mech. Thermodyn., 21 (2009), 85-107, arXiv:0812.4390. Google Scholar
[37]	B. Piccoli and A. Tosin, Time-evolving measures and macroscopic modeling of pedestrian flow, Arch. Ration. Mech. Anal., 199 (2011), 707-738, arXiv:0811.3383. Google Scholar
[38]	C. W. Reynolds, "Steering Behaviors for Autonomous Characters," Proceedings of Game Developers Conference 1999, San Jose, California, (1999), 763-782. Google Scholar
[39]	V. Shvetsov and D. Helbing, Macroscopic dynamics of multi-lane traffic, Phys. Rev. E, 59 (1999), 6328-6339, arXiv:cond-mat/9906430. 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), 1274-1294. 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), 668-678. 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), 275-290. 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 IEEE Intelligent Transportation Systems Conference, Toronto, Canada, September, (2006), 17-20. 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), 259-278. 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), 916-938. 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), 1317-1345. 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), 587-612. 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), 185-220. 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), 1269-1298. 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), 639-660. 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), 507-525, arXiv:cond-mat/0102397. 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), 539-555. 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), 1553-1567. doi: 10.1002/mma.624. Google Scholar
[12]	C. Daganzo, Requiem for second order fluid approximations of traffic flow, Transp. Res. B, 29 (1995), 277-286. 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), 279-293. 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), 1-31, arXiv:0908.1929. Google Scholar
[16]	R. Y. Guo and H. J. Huang, A mobile lattice gas model for simulating pedestrian evacuation, Physica A, 387 (2008), 580-586. 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), 177-187. Google Scholar
[18]	D. Helbing, A mathematical model for the behavior of pedestrians, Behavioral Science, 36 (1991), 298-310. doi: 10.1002/bs.3830360405. Google Scholar
[19]	D. Helbing, A fluid-dynamic model for the movement of pedestrians, Complex Systems, 6 (1992), 391-415. Google Scholar
[20]	D. Helbing and P. Molnàr, Social force model for pedestrian dynamics, Physical Review E, 51 (1995), 4282-4286. 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, September 24-28, 1995, Edited by Frank Schweitzer. Gordon and Breach Science Publishers, Amsterdam, 1997. Google Scholar
[22]	L. F. Henderson, On the fluid mechanics of human crowd motion, Transportation Research, 8 (1974), 509-515. 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), 153-172. doi: 10.1002/oca.727. Google Scholar
[24]	R. L. Hughes, A continuum theory for the flow of pedestrians, Transportation Research B, 36 (2002), 507-535. 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), 169-182. 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), 240-282. Google Scholar
[27]	R. J. LeVeque, "Finite Volume Methods for Hyperbolic Problems," Cambridge Texts in Mathematics, Cambridge University Press, Cambridge, 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), 281-345. 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), 1787-1821. 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), 1245-1250. 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), 726-732, arXiv:cond-mat/0306262. 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), 665-674. 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), 189-198. Google Scholar
[36]	B. Piccoli and A. Tosin, Pedestrian flows in bounded domains with obstacles, Contin. Mech. Thermodyn., 21 (2009), 85-107, arXiv:0812.4390. Google Scholar
[37]	B. Piccoli and A. Tosin, Time-evolving measures and macroscopic modeling of pedestrian flow, Arch. Ration. Mech. Anal., 199 (2011), 707-738, arXiv:0811.3383. Google Scholar
[38]	C. W. Reynolds, "Steering Behaviors for Autonomous Characters," Proceedings of Game Developers Conference 1999, San Jose, California, (1999), 763-782. Google Scholar
[39]	V. Shvetsov and D. Helbing, Macroscopic dynamics of multi-lane traffic, Phys. Rev. E, 59 (1999), 6328-6339, arXiv:cond-mat/9906430. 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), 1274-1294. 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), 668-678. 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), 275-290. doi: 10.1016/S0191-2615(00)00050-3. Google Scholar

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