Abstract
An extended car following model is presented by considering the effect of Multi-Headway Variation Forecast (MHVF) effect in the real world. The model’s linear stability criterion was obtained by employing the linear stability theory. Theoretical analysis result shows that the new consideration leads to the stabilization of traffic systems. By means of nonlinear analysis method, the modified Korteweg-deVries (mKdV) equation near the critical point was derived, thus the propagation behavior of traffic jam can be characterized by the kink-antikink soliton solution for the mKdV equation. Numerical simulation is carried out and its results is in good agreement with the aforementioned theoretical analysis. Both of them show that the MHVF effect can suppress the emergence of traffic jamming and stabilize the vehicular system.
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References
Tang TQ, Wang YP, Yang XB, Wu YH (2012) A new car-following model accounting for varying road condition. Nonlinear Dynam 70:1397–1405
Kaur R, Sharma S (2017) Analysis of driver’s characteristics on a curved road in a lattice model. Phys A 471:59–67
Peng GH, Kuang H, Qing L (2018) Feedback control method in lattice hydrodynamic model under honk environment. Phys A 509:651–656
Peng GH, Yang SH, Zhao HZ (2018) New feedback control model in the lattice hydrodynamic model considering the historic optimal velocity difference effect. Commun Theor Phys 70:803–807
Sun DH, Kang YR, Yang SH (2015) A novel car following model considering average speed of preceding vehicles group. Phys A 436:103–109
Tang TQ, Huang HJ, Shang HY (2010) A new macro model for traffic flow with the consideration of the driver’s forecast effect. Phys Lett A 374:1668–1672
Jiang R, Wu QS, Zhu ZJ (2002) A new continuum model for traffic flow and numerical tests. Transp Res B 36:405–419
Zhou J, Shi ZK (2016) Lattice hydrodynamic model for traffic flow on curved road. Nonlinear Dyn 83:1217–1236
Watanabe MS (2006) Dynamics of group motions controlled by signal processing: a cellular-automaton model and its applications. Commun Nonlinear Sci Numer Simul 11:624–634
Bando M, Hasebe K, Shibata A, Sugiyama Y (1995) Dynamical model of traffic congestion and numerical simulation. Phys Rev E 51:1035–1042
Nagatani T (1996) Gas kinetic approach to two-dimensional traffic flow. J Phys Soc Jpn 65:3150–3152
Felipe S, Omer V, Joshua A (2019) Mesoscopic traffic flow model for agent-based simulation. Procedia Comput Sci 151:858–863
Helbing D, Tilch B (1998) Generalized force model of traffic dynamics. Phys Rev E 58:133–138
Jiang R, Wu QS, Zhu ZJ (2001) Full velocity difference model for a car-following theory. Phys Rev E 64:017101–017104
Ge HX, Dai SQ, Xue Y, Dong LY (2005) Stabilization analysis and modified Korteweg–de Vries equation in a cooperative driving system. Phys Rev E 71:066119
Ge HX, Cheng RJ, Li ZP (2008) Two velocity difference model for a car following theory. Phys A 387:5239–5245
Ma GY, Ma MH, Liang SD, Wang SY, Zhang YZ (2020) An improved car-following model accounting for the time-delayed velocity difference and backward looking effect. Commun Nonlinear Sci Numer Simul 85:105221
Tang TQ, Li CY, Huang HJ (2010) A new car-following model with the consideration of the driver’s forecast effect. Phys Lett A 374:3951–3956
Zhang LD, Jia L, Zhu WX (2012) Curved road traffic flow car-following model and stability analysis. Acta Phys Sin 61(7):074501
Tang TQ, Huang HJ, Wong SC, Jiang R (2009) A new car-following model with consideration of the traffic interruption probability. Chin Phys B 18(3):975–983
Zheng LJ, Tian C, Sun DH, Liu WN (2012) A new car-following model with consideration of anticipation driving behavior. Nonlinear Dynam 70:1205–1211
Wang T, Li GY, Zhang J, Li SB, Sun T (2019) The effect of Headway Variation Tendency on traffic flow: modeling and stabilization. Phys A 525:566–575
Zhang J, Wang B, Li SB, Sun T, Wang T (2020) Modeling and application analysis of car-following model with predictive headway variation. Phys A 540:123171
Wang T, Zang RD, Xu KY, Zhang J (2019) Analysis of predictive effect on lattice hydrodynamic traffic flow model. Phys A 526:120711
Kaur D, Sharma S (2020) A new two-lane lattice model by considering predictive effect in traffic flow. Phys A 539:122913
Ge HX, Cheng RJ, Dai SQ (2005) KdV and kink-antikink solitons in car-following models. Phys A 357:466–476
Acknowledgements
This work is supported by Science and Technology Plan Projects of Guizhou Province: (No.[2018]1059) and Natural Science Foundation of Guangxi (No.2018GXNSFAA050020).
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Kang, Yr., Yang, Sh. (2023). A New Car Following Model Considering the Multi-headway Variation Forecast Effect. In: Wang, W., Wu, J., Jiang, X., Li, R., Zhang, H. (eds) Green Transportation and Low Carbon Mobility Safety. GITSS 2021. Lecture Notes in Electrical Engineering, vol 944. Springer, Singapore. https://doi.org/10.1007/978-981-19-5615-7_39
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DOI: https://doi.org/10.1007/978-981-19-5615-7_39
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