Modeling heterogeneous traffic flow: A pragmatic approach

Transportation Research Part B: Methodological

Volumn 99, Issue , 2017, Pages 183-204

  Li, Jia ^b   Li, Xiaopeng ^c   Zhang, Michael ^d   Wang, Haizhong ^e  

^a Sean) Qian, Zhen   (United States)

^b The University of Texas at Austin   (United States)

^c University of South Florida   (United States)

^d University of California Davis   (United States)

^e Oregon State University   (United States)

Author keywords

Data driven; Fundamental diagram; Heterogeneous traffic flow; LWR; Multi class; Multi modal; NGSIM

Indexed keywords

COMPLEX NETWORKS; EQUIVALENCE CLASSES; MOTOR TRANSPORTATION; TRAFFIC CONTROL; TRAVEL TIME; VEHICLES;

DATA DRIVEN; FUNDAMENTAL DIAGRAM; HETEROGENEOUS TRAFFIC FLOW; MULTI-CLASS; MULTI-MODAL; NGSIM;

TRAFFIC CONGESTION;

HYDRODYNAMICS; MODEL VALIDATION; MODELING; NETWORK ANALYSIS; TRAFFIC CONGESTION; TRANSPORT VEHICLE; TRANSPORTATION SYSTEM;

EID: 85012253786     PISSN: 01912615     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trb.2017.01.011     Document Type: Article

References (32)

1. Cassidy, M., Bivariate relations in nearly stationary highway traffic. Transp. Res. Part B 32:1 (1998), 49–59.
2. Chanut, S., Buisson, C., Macroscopic model and its numerical solution for two-flow mixed traffic with different speeds and lengths. Transp. Res. Rec. 1852:1 (2003), 209–219.
3. Costeseque, G., Lebacque, J.-P., A variational formulation for higher order macroscopic traffic flow models: numerical investigation. Transp. Res. Part B 70 (2014), 112–133.
4. Dafermos, C., Hyperbolic Conservation Laws in Continuum Physics. 325, 2005, Springer Verlag.
5. Daganzo, C., The cell transmission model: a dynamic representation of highway traffic consistent with the hydrodynamic theory. Transp. Res. Part B 28:4 (1994), 269–287.
6. Daganzo, C., A variational formulation of kinematic waves: basic theory and complex boundary conditions. Transp. Res. Part B 39:2 (2005), 187–196.
7. Fan, S., Seibold, B., 2013. Effect of the choice of stagnation density in data-fitted first-and second-order traffic models. arXiv preprint arXiv:1308.0393.
8. Hoogendoorn, S.P., Bovy, P.H., Continuum modeling of multiclass traffic flow. Transp. Res. Part B 34:2 (2000), 123–146.
9. Jin, W.-L., A kinematic wave theory of multi-commodity network traffic flow. Transp. Res. Part B 46:8 (2012), 1000–1022.
10. Jin, W.-L., On the stability of stationary states in general road networks. Transp. Res. Part B 98 (2017), 42–61.
11. Kontorinaki, M., Spiliopoulou, A., Papamichail, I., Papageorgiou, M., Tyrinopoulos, Y., Chrysoulakis, J., Overview of nonlinear programming methods suitable for calibration of traffic flow models. Oper. Res. 15:3 (2015), 327–336.
12. Laval, J., Daganzo, C., Lane-changing in traffic streams. Transp. Res. Part B 40:3 (2006), 251–264.
13. Laval, J.A., Chilukuri, B.R., Symmetries in the kinematic wave model and a parameter-free representation of traffic flow. Transp. Res. Part B 89 (2016), 168–177.
14. Lebacque, J., The Godunov scheme and what it means for first order traffic flow models. Internaional Symposium on Transportation and Traffic Theory, 1996, 647–677.
15. Lebacque, J., Lesort, J., Giorgi, F., Introducing buses into first-order macroscopic traffic flow models. Transp. Res. Rec 1644 (1998), 70–79.
16. LeVeque, R., Numerical Methods for Conservation Laws. 1992, Birkhäuser.
17. Li, J., Zhang, H., Modeling space–time inhomogeneities with the kinematic wave theory. Transp. Res. Part B 54 (2013), 113–125.
18. Lighthill, M., Whitham, G., On kinematic waves. II. a theory of traffic flow on long crowded roads. Proc. R. Soc. London. Ser.A Math. Phys. Sci. (1934–1990) 229:1178 (1955), 317–345.
19. Logghe, S., 2003. Dynamic modeling of heterogeneous vehicular traffic.
20. Logghe, S., Immers, L., Multi-class kinematic wave theory of traffic flow. Transp. Res. Part B 42:6 (2008), 523–541.
21. Mohan, R., Ramadurai, G., Heterogeneous traffic flow modelling using second-order macroscopic continuum model. Phys. Lett. A 381:3 (2017), 115–123.
22. Nagel, K., Schreckenberg, M., A cellular automaton model for freeway traffic. J. Phys. I 2:12 (1992), 2221–2229.
23. Ngoduy, D., Liu, R., Multiclass first-order simulation model to explain non-linear traffic phenomena. Physica A 385:2 (2007), 667–682.
24. NGSIM, 2006. Next generation simulation. http://ops.fhwa.dot.gov/trafficanalysistools/ngsim.htm. [Online; accessed 25-July-2014].
25. Richards, P., Shock waves on the highway. Oper. Res. 4:1 (1956), 42–51.
26. Tian, J., Li, G., Treiber, M., Jiang, R., Jia, N., Ma, S., Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow. Transp. Res. Part B 93 (2016), 560–575.
27. Toro, E.F., Riemann Solvers and Numerical Methods for Fluid Dynamics: A Practical Introduction. 2009, Springer.
28. van Lint, J.W., Hoogendoorn, S.P., Schreuder, M., Fastlane: new multiclass first-order traffic flow model. Transp. Res. Rec. 2088:1 (2008), 177–187.
29. van Wageningen-Kessels, F., van Lint, H., Hoogendoorn, S.P., Vuik, K., Lagrangian formulation of multiclass kinematic wave model. Transp. Res. Rec. 2188:1 (2010), 29–36.
30. Whitham, G., Linear and Nonlinear Waves. 1974, Wiley-Interscience.
31. Wong, G., Wong, S., A multi-class traffic flow model–an extension of LWR model with heterogeneous drivers. Transp. Res. Part A 36:9 (2002), 827–841.
32. Zhang, P., Wong, S., Shu, C., A weighted essentially non-oscillatory numerical scheme for a multi-class traffic flow model on an inhomogeneous highway. J. Comput. Phys. 212:2 (2006), 739–756.