Stable headway prediction of vehicle platoon based on the 5-degree-of-freedom vehicle model

Abstract

Vehicular ad hoc network and cooperative adaptive cruise control system make vehicle platooning with small headway feasible. In the study of the autonomous vehicle platoon system under the vehicular ad hoc network condition, the linear vehicle model is usually used to analyze the minimum space-gap, safety space-gap, and so on. However, the stability of nonlinear vehicle system shows that there are limitations when using the linearized vehicle model to analyze vehicle stability. The linear model cannot reflect the influence of the system nonlinear coupling on the vehicle stability. Therefore, in this paper, we use the validated 5-degree-of-freedom (longitudinal velocity, lateral velocity, yaw rate, front wheel rotational velocity, and rear wheel rotational velocity) nonlinear model to analyze the stable intra-platoon spacing of the autonomous vehicle platoon system under the condition of VANET. In order to study the safety intra-platoon spacing of vehicle platoon running in the complex path, a following controller is designed for vehicle platoon running in the corners. The controller adopts the method of vertical and horizontal decentralized control. The longitudinal control is to realize the expected space-gap of vehicles in vehicle platoon, and the lateral control is to achieve the position and orientation following of the preceding vehicle. Based on the stability verification of the following controller, the following control characteristics of vehicle system are analyzed, and the stable headway required for vehicles in vehicle platoon running in the complex path is predicted by the method of simulation experiment.

Keywords

5-degree-of-freedom model Magic Formula following controller vehicle stability stable headway

Get full access to this article

View all access options for this article.

References

Michael

Godbole

Lygeros

et al . Capacity analysis of traffic flow over a single-lane automated highway system. J Intell Transport S 1998; 4: 49–80.

Amoozadeh

Deng

Chuah

et al . Platoon management with cooperative adaptive cruise control enabled by VANET. Veh Commun 2015; 2: 110–123.

Hall

Chin

Vehicle sorting for platoon formation: impacts on highway entry and throughput. Transport Res C: Emer 2005; 13: 405–420.

Van Arem

Van Driel

CJG

Visser

. The impact of cooperative adaptive cruise control on traffic-flow characteristics. IEEE T Intell Transp 2006; 7: 429–436.

Wang

Han

. Stability of an automated vehicle platoon. In: Proceedings of the American control conference, Philadelphia, PA, 26 June 1998, pp.950–954. New York: IEEE.

Naus

Vugts

Ploeg

et al . Cooperative adaptive cruise control, design and experiments. In: Proceedings of the American control conference, Baltimore, MD, 30 June–2 July 2010. New York: IEEE.

Ploeg

Shukla

van de Wouw

et al . Controller synthesis for string stability of vehicle platoons. IEEE T Intell Transp 2014; 15: 854–865.

Milanés

Shladover

Spring

et al . Cooperative adaptive cruise control in real traffic situations. IEEE T Intell Transp 2014; 15: 296–305.

Chehardoli

Homaeinezhad

MR.

Third-order safe consensus of heterogeneous vehicular platoons with MPF network topology: constant time headway strategy. Proc IMechE, Part D: J Automobile Engineering 2018; 232: 1402–1413.

10.

Chehardoli

Ghasemi

Adaptive centralized/decentralized control and identification of 1-D heterogeneous vehicular platoons based on constant time headway policy. IEEE T Intell Transp 2018; PP: 1–11.

11.

True

On the theory of nonlinear dynamics and its applications in vehicle systems dynamics. Vehicle Syst Dyn 1999; 31: 393–421.

12.

Shen

Veldpaus

FE.

Analysis and control of a flywheel hybrid vehicular powertrain. IEEE T Contr Syst T 2004; 12: 645–660.

13.

Inagaki

Kushiro

Yamamoto

Analysis on vehicle stability in critical cornering using phase-plane method. JSAE Rev 1995; 2: 216.

14.

Lee

JM.

Estimation of the stability region of a vehicle in plane motion using a topological approach. Int J Vehicle Des 2002; 30: 181–192.

15.

Sadri

Stability analysis of a nonlinear vehicle model in plane motion using the concept of Lyapunov exponents. Vehicle Syst Dyn 2013; 51: 906–924.

16.

Liaw

Chiang

Lee

TT.

Elucidating vehicle lateral dynamics using a bifurcation analysis. IEEE T Intell Transp 2007; 8: 195–207.

17.

Liu

Shi

Shen

et al . Vehicle planar motion stability study for tyres working in extremely nonlinear region. Chin J Mech Eng 2010; 23: 185.

18.

Horiuchi

Okada

Nohtomi

Analysis of accelerating and braking stability using constrained bifurcation and continuation methods. Vehicle Syst Dyn 2008; 46: 585–597.

19.

Horiuchi

Evaluation of chassis control method through optimisation-based controllability region computation. Vehicle Syst Dyn 2012; 50: 19–31.

20.

Mitschke

Wallentowitz

Dynamik der Kraftfahr-zeuge. 4. Auflage. Berlin: Springer, 2004.

21.

Wang

Shi

Liu

et al . Analysis of driving mode effect on vehicle stability. Int J Automot Techn 2013; 14: 363–373.

22.

Wang

Shi

Analysis of vehicle steering and driving bifurcation characteristics. Math Probl Eng 2015; 2015: 847258.

23.

Shi

Wang

et al . Analysis of the vehicle driving stability region based on the bifurcation of the driving torque and the steering angle. Proc IMechE, Part D: J Automobile Engineering 2017; 231: 984–988.

24.

Song

CK.

Vehicle modeling with nonlinear tires for vehicle stability analysis. Int J Automot Techn 2010; 11: 339–344.

25.

Pacejka

HB.

Tyre and vehicle dynamics. Oxford: Elsevier, 2006.

26.

Ono

Hosoe

Tuan

et al . Bifurcation in vehicle dynamics and robust front wheel steering control. IEEE T Contr Syst T 1998; 6: 412–420.

27.

Wang

Shi

Jin

. Modeling and analysis on effect of driving force for vehicle stability. In: International conference on transportation, mechanical, and electrical engineering (TMEE), Changchun, China, 16–18 December 2011, pp.1228–1231. New York: IEEE.

28.

Khatir

Davison

. A decentralized lateral-longitudinal controller for a platoon of vehicles operating on a plane. In: Proceedings of the American control conference, Minneapolis, MN, 14–16 June 2006. New York: IEEE.

29.

Rajamani

Vehicle dynamics and control. Berlin: Springer, 2011.

30.

Ploeg

Scheepers

BTM

Van Nunen

et al . Design and experimental evaluation of cooperative adaptive cruise control. In: 14th international IEEE conference on intelligent transportation systems (ITSC), Washington, DC, 5–7 October 2011, pp.260–265. New York: IEEE.

31.

Naus

GJL

Vugts

RPA

Ploeg

et al . String-stable CACC design and experimental validation: a frequency-domain approach. IEEE T Veh Technol 2010; 59: 4268–4279.

32.

Bai

Ease of control evaluation via stochastic driver model. PhD Thesis, Jilin University, Changchun, China, 2012.

33.

Guo

Preview optimal curvature model of handling movement of closed-loop system composed of driver-automotive. Automot Eng 1984, 6(3): 1–16.

34.

Guo

Automotive handling dynamics. Changchun, China: Jilin Science and Technology Press, 1991.

35.

Automobile theory. Beijing, China: China Machine Press, 2009.