Lighthill-Whitham-Richards Model for Traffic Flow Mixed with Cooperative Adaptive Cruise Control Vehicles

Published Online:https://doi.org/10.1287/trsc.2021.1057

References

  • Benzoni-Gavage S, Colombo RM (2003) An n-populations model for traffic flow. Eur. J. Appl. Math. 14(05):587–612.CrossrefGoogle Scholar
  • Chen D, Srivastava A, Ahn S, Li T (2020) Traffic dynamics under speed disturbance in mixed traffic with automated and non-automated vehicles. Transportation Res. Part C: Emerging Tech. 113:293–313.CrossrefGoogle Scholar
  • Daganzo CF (1994) The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Res. Part B: Methodological 28(4):269–287.CrossrefGoogle Scholar
  • Daganzo CF (1995) The cell transmission model, part II: network traffic. Transportation Res. Part B: Methodological 29(2):79–93.CrossrefGoogle Scholar
  • Daganzo CF (1997) A continuum theory of traffic dynamics for freeways with special lanes. Transportation Res. Part B: Methodological 31(2):83–102.CrossrefGoogle Scholar
  • Daganzo CF (2002) A behavioral theory of multi-lane traffic flow. Part I: Long homogeneous freeway sections. Transportation Res. Part B: Methodological 36(2):131–158.CrossrefGoogle Scholar
  • Daganzo CF, Lin WH, Del Castillo JM (1997) A simple physical principle for the simulation of freeways with special lanes and priority vehicles. Transportation Res. Part B: Methodological 31(2):103–125.CrossrefGoogle Scholar
  • Davis LC (2004) Effect of adaptive cruise control systems on traffic flow. Physics Rev. E 69(6):066110.CrossrefGoogle Scholar
  • Delis AI, Nikolos IK, Papageorgiou M (2015) Macroscopic traffic flow modeling with adaptive cruise control: Development and numerical solution. Comput. Math. Appl. 70(8):1921–1947.CrossrefGoogle Scholar
  • Fernandes P, Nunes U (2015) Multiplatooning leaders positioning and cooperative behavior algorithms of communicant automated vehicles for hightraffic capacity. IEEE Trans. Intelligent Transportation Systems 16(3):1172–1187.CrossrefGoogle Scholar
  • Ge JI, Orosz G (2014) Dynamics of connected vehicle systems with delayed acceleration feedback. Transportation Res. Part C: Emerging Tech. 46:46–64.CrossrefGoogle Scholar
  • Ge JI, Avedisov SS, He CR, Qin WB, Sadeghpour M, Gabor O (2018) Experimental validation of connected automated vehicle design among human-driven vehicles. Transportation Res. Part C: Emerging Tech. 91:335–352.CrossrefGoogle Scholar
  • Geiger A, Lauer M, Moosmann F, Ranft B, Rapp H, Stiller C, Ziegler J (2012) Team AnnieWAY’s entry to the 2011 Grand Cooperative Driving challenge. IEEE Trans. Intelligent Transportation Systems 13(3):1008–1017.CrossrefGoogle Scholar
  • Gong S, Shen J, Du L (2016) Constrained optimization and distributed computation based car following control of a connected and autonomous vehicle platoon. Transportation Res. Part B: Methodological 94:314–334.CrossrefGoogle Scholar
  • Gong S, Zhou A, Peeta S (2019) Cooperative adaptive cruise control for a platoon of connected and autonomous vehicles considering dynamic information flow topology. Transportation Res. Record 2673(10):185–198.CrossrefGoogle Scholar
  • Guvenc L, Uygan IMC, Kahraman K, Karaahmetoglu R, Altay I, Senturk M, Emirler MT, et al.. (2012) Cooperative adaptive cruise control implementation of Team Mekar at the Grand Cooperative Driving Challenge. IEEE Trans. Intelligent Transportation Systems 13(3):1062–1074.CrossrefGoogle Scholar
  • Holland EN (1998) A generalised stability criterion for motorway traffic. Transportation Res. Part B: Methodological 32(2):141–154.CrossrefGoogle Scholar
  • Hoogendoorn SP, Bovy PH (2000) Continuum modeling of multiclass traffic flow. Transportation Res. Part B: Methodological 34(2):123–146.CrossrefGoogle Scholar
  • Jerath K, Ray A, Brennan S, Gayah VV (2015) Dynamic prediction of vehicle cluster distribution in mixed traffic: A statistical mechanics-inspired method. IEEE Trans. Intelligent Transportation Systems 16(5):2424–2434.CrossrefGoogle Scholar
  • Jia D, Ngoduy D (2016a) Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication. Transportation Res. Part B: Methodological 90:172–191.CrossrefGoogle Scholar
  • Jia D, Ngoduy D (2016b) Platoon based cooperative driving model with consideration of realistic inter-vehicle communication. Transportation Res. Part C: Emerging Tech. 68:245–264.CrossrefGoogle Scholar
  • Jin WL (2013) A multi-commodity Lighthill-Whitham-Richards model of lane-changing traffic flow. Procedia Soc. Behav. Sci. 80:658–677.CrossrefGoogle Scholar
  • Jin WL (2016) On the equivalence between continuum and car-following models of traffic flow. Transportation Res. Part B: Methodological 93:543–559.CrossrefGoogle Scholar
  • Jin WL, Gan QJ, Lebacque JP (2015) A kinematic wave theory of capacity drop. Transportation Res. Part B: Methodological 81:316–329.CrossrefGoogle Scholar
  • Kerner BS (2016) Failure of classical traffic flow theories: Stochastic highway capacity and automatic driving. Phys. A 450:700–747.CrossrefGoogle Scholar
  • Kesting A, Treiber M (2008) Calibrating car-following models by using trajectory data: Methodological study. Transportation Res. Record J. Transportation Res. Board 2088:148–156.CrossrefGoogle Scholar
  • Kesting A, Treiber M, Helbing D (2010). Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity. Philos. Trans. Roy. Soc. London A: Math. Physical Engrg. Sci. 368(1928):4585–4605.Google Scholar
  • Kesting A, Treiber M, Schonhof M, Helbing D (2008) Adaptive cruise control design for active congestion avoidance. Transportation Res. Part C: Emerging Tech. 16(6):668–683.CrossrefGoogle Scholar
  • Levin MW, Boyles SD (2016a) A cell transmission model for dynamic lane reversal with autonomous vehicles. Transportation Res. Part C: Emerging Tech. 68:126–143.CrossrefGoogle Scholar
  • Levin MW, Boyles SD (2016b) A multiclass cell transmission model for shared human and autonomous vehicle roads. Transportation Res. Part C: Emerging Tech. 62:103–116.CrossrefGoogle Scholar
  • Li J, Chen QY, Wang H, Ni D (2012) Analysis of LWR model with fundamental diagram subject to uncertainties. Transportmetrica 8(6):387–405.CrossrefGoogle Scholar
  • Lighthill MJ, Whitham GB (1955) On kinematic waves. II. A theory of traffic flow on long crowded roads. Philos. Trans. Roy. Soc. London A: Math. Physical Engrg. Sci. 229(1178):317–345.CrossrefGoogle Scholar
  • Logghe S, Immers LH (2008) Multi-class kinematic wave theory of traffic flow. Transportation Res. Part B: Methodological 42(6):523–541.CrossrefGoogle Scholar
  • Mahmassani HS (2016) 50th anniversary invited article—Autonomous vehicles and connected vehicle systems: Flow and operations considerations. Transportation Sci. 50(4):1140–1162.LinkGoogle Scholar
  • Milakis D, Van Arem B, Van Wee B (2017) Policy and society related implications of automated driving: A review of literature and directions for future research. J. Intelligent Transportation Systems 21(4):324–348.CrossrefGoogle Scholar
  • Milanés V, Shladover SE (2014) Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data. Transportation Res. Part C: Emerging Tech. 48:285–300.CrossrefGoogle Scholar
  • Milanés V, Shladover SE, Spring J, Nowakowski C, Kawazoe H, Nakamura M (2014) Cooperative adaptive cruise control in real traffic situations. IEEE Trans. Intelligent Transportation Systems 15(1):296–305.CrossrefGoogle Scholar
  • Navas F, Milanés V (2019) Mixing V2V-and non-V2V-equipped vehicles in car following. Transportation Res. Part C: Emerging Tech. 108:167–181.CrossrefGoogle Scholar
  • Ngoduy D (2010) Multiclass first-order modelling of traffic networks using discontinuous flow-density relationships. Transportmetrica 6(2):121–141.CrossrefGoogle Scholar
  • Ngoduy D (2011) Multiclass first-order traffic model using stochastic fundamental diagrams. Transportmetrica 7(2):111–125.CrossrefGoogle Scholar
  • Ngoduy D (2013a) Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach. Commun. Nonlinear Sci. Numerical Simulations 18(10):2838–2851.CrossrefGoogle Scholar
  • Ngoduy D (2013b) Platoon-based macroscopic model for intelligent traffic flow. Transportmetrica B: Transport Dynamics 1(2):153–169.CrossrefGoogle Scholar
  • Ngoduy D, Li T (2021) Hopf bifurcation structure of a generic car-following model with multiple time delays. Transportmetrica A: Transportation Sci. 17(4):878–896.CrossrefGoogle Scholar
  • Ngoduy D, Liu R (2007) Multiclass first-order simulation model to explain non-linear traffic phenomena. Phys. A 385(2):667–682.CrossrefGoogle Scholar
  • Ni D (2015) Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques (Butterworth-Heinemann, Oxford, England).Google Scholar
  • Ni D, Leonard JD, Jia C, Wang J (2015) Vehicle longitudinal control and traffic stream modeling. Transportation Sci. 50(3):1016–1031.LinkGoogle Scholar
  • Ploeg J, Scheepers BT, van Nunen E, van de Wouw N, Nijmeijer H (2011) Design and experimental evaluation of cooperative adaptive cruise control. Proc. 2011 14th Internat. IEEE Conf. on Intelligent Transportation Systems (IEEE, New York), 260–265.Google Scholar
  • Ploeg J, Semsar-Kazerooni E, Lijster G, van de Wouw N, Nijmeijer H (2015) Graceful degradation of cooperative adaptive cruise control. IEEE Trans. Intelligent Transportation Systems 16(1):488–497.CrossrefGoogle Scholar
  • Qian ZS, Li J, Li X, Zhang M, Wang H (2017) Modeling heterogeneous traffic flow: A pragmatic approach. Transportation Res. Part B: Methodological 99:183–204.CrossrefGoogle Scholar
  • Rad SR, Farah H, Taale H, van Arem B, Hoogendoorn SP (2020) Design and operation of dedicated lanes for connected and automated vehicles on motorways: A conceptual framework and research agenda. Transportation Res. Part C: Emerging Tech. 117:102664.CrossrefGoogle Scholar
  • Richards PI (1956) Shock waves on the highway. Oper. Res. 4(1):42–51.LinkGoogle Scholar
  • Shiomi Y, Taniguchi T, Uno N, Shimamoto H, Nakamura T (2015) Multilane first-order traffic flow model with endogenous representation of lane-flow equilibrium. Transportation Res. Part C: Emerging Tech. 59:198–215.CrossrefGoogle Scholar
  • Shladover SE, Nowakowski C, Lu XY, Ferlis R (2015) Cooperative adaptive cruise control: definitions and operating concepts. Transportation Res. Record J. Transportation Res. Board 2489:145–152.CrossrefGoogle Scholar
  • Talebpour A, Mahmassani HS (2016) Influence of connected and autonomous vehicles on traffic flow stability and throughput. Transportation Res. Part C: Emerging Tech. 71:143–163.CrossrefGoogle Scholar
  • Tang TQ, Wang YP, Yu GZ, Huang HJ (2012) A stochastic LWR model with consideration of the driver’s individual property. Commun. Theoretical Phys. (Beijing) 58(4):583.CrossrefGoogle Scholar
  • Treiber M, Helbing D (1999) Macroscopic simulation of widely scattered synchronized traffic states. J. Phys. Math. General 32(1):L17–L23.CrossrefGoogle Scholar
  • Treiber M, Kesting A (2013) Traffic Flow Dynamics: Data. Models and Simulation (Springer-Verlag, Berlin).CrossrefGoogle Scholar
  • Treiber M, Hennecke A, Helbing D (2000) Congested traffic states in empirical observations and microscopic simulations. Phys. Rev. E 62(2):1805.CrossrefGoogle Scholar
  • Van Arem B, Van Driel CJ, Visser R (2006) The impact of cooperative adaptive cruise control on traffic-flow characteristics. IEEE Trans. Intelligent Transportation Systems 7(4):429–436.CrossrefGoogle Scholar
  • Van Lint J, Hoogendoorn S, Schreuder M (2008) Fastlane: New multiclass first-order traffic flow model. Transportation Res. Record J. Transportation Res. Board 2088:177–187.CrossrefGoogle Scholar
  • van Nunen E, Kwakkernaat MR, Ploeg J, Netten BD (2012) Cooperative competition for future mobility. IEEE Trans. Intelligent Transportation Systems 13(3):1018–1025.CrossrefGoogle Scholar
  • van Wageningen-Kessels F (2016) Framework to assess multiclass continuum traffic flow models. Transportation Res. Record J. Transportation Res. Board 2553:150–160.CrossrefGoogle Scholar
  • van Wageningen-Kessels F, Van Lint H, Hoogendoorn S, Vuik K (2014) New generic multiclass kinematic wave traffic flow model: Model development and analysis of its properties. Transportation Res. Record J. Transportation Res. Board 2422:50–60.CrossrefGoogle Scholar
  • Wang H, Qin Y, Wang W, Chen J (2019) Stability of CACC-manual heterogeneous vehicular flow with partial CACC performance degrading. Transportmetrica B: Transport Dynamics 7(1):788–813.CrossrefGoogle Scholar
  • Wang Y, Li X, Tian J, Jiang R (2020) Stability analysis of stochastic linear car-following models. Transportation Sci. 54(1):274–297.LinkGoogle Scholar
  • Weinberger M, Winner H, Bubb H (2001) Adaptive cruise control field operational test—The learning phase. JSAE Rev. 22(4):487–494.CrossrefGoogle Scholar
  • Wong GCK, Wong SC (2002) A multi-class traffic flow model–an extension of LWR model with heterogeneous drivers. Transportation Res. Part A: Policy Practice 36(9):827–841.CrossrefGoogle Scholar
  • Xiao L, Wang M, van Arem B (2019) Traffic flow impacts of converting an HOV lane into a dedicated CACC lane on a freeway corridor. IEEE Intelligent Transportation Systems Mag. 12(1):60–73.CrossrefGoogle Scholar
  • Zhang H, Jin W (2002). Kinematic wave traffic flow model for mixed traffic. Transportation Res. Record: J. Transportation Res. Board 1802:197–204.Google Scholar
  • Zhong ZJ, Lee J (2019) The effectiveness of managed lane strategies for the near-term deployment of cooperative adaptive cruise control. Transportation Res. Part A: Policy Practice 129:257–270.CrossrefGoogle Scholar
  • Zhou Y, Ahn S (2019) Robust local and string stability for a decentralized car following control strategy for connected automated vehicles. Transportation Res. Part B: Methodological 125:175–196.CrossrefGoogle Scholar
  • Zhou J, Zhu F (2020) Modeling the fundamental diagram of mixed human-driven and connected automated vehicles. Transportation Res. Part C: Emerging Tech. 115:102614.CrossrefGoogle Scholar
  • Zhou J, Zhu F (2021) Analytical analysis of the effect of maximum platoon size of connected and automated vehicles. Transportation Res. Part C: Emerging Tech. 122:102882.CrossrefGoogle Scholar
  • Zhong Z, Lee EE, Nejad M, Lee J (2020) Influence of CAV clustering strategies on mixed traffic flow characteristics: An analysis of vehicle trajectory data. Transportation Res. Part C: Emerging Tech. 115:102611.CrossrefGoogle Scholar
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