Vehicle-to-vehicle connectivity on parallel roadways with large road separation

Wang, Xiubin Bruce; Yin, Kedong; Yan, Xuedong

doi:10.1016/j.trc.2015.01.003

Cited by 8 publications

(5 citation statements)

References 9 publications

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“…In this study, the information propagation process between two RSUs is modelled using a transmission‐region‐based method. A similar modelling method was applied to inter‐vehicle information propagation analysis in [32–35]. Herein, we consider a system with two parallel roadways, as shown in Fig.…”

Section: Modelling the Information Propagation Processmentioning

confidence: 99%

“…Under condition

d > \sqrt{3} R / 2

, no parallelogram ABCD is completely contained within the transmission range of vehicle A . This requires different modelling methods from that used in the present study [34]. The problem of information propagation between two RSUs under the condition of

d > \sqrt{3} R / 2

will be addressed in a future study.…”

Section: Modelling the Information Propagation Processmentioning

confidence: 99%

“…Studies on information propagation in VANETs have been driven by several research and standardisation efforts. Studies included a focus on communication networks that are both one‐dimensional [24–35] and two‐dimensional [16, 22, 23, 36–39]. Interest in information propagation on two parallel roadways has emerged in recent years.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, most existing studies on RSU location assumed that the vehicle headway follows an exponential distribution. However, as indicated in [30, 32–34], this assumption causes significant errors in the information travel time calculation. Therefore, it is necessary to extend the RSU location model by considering a general vehicle headway distribution.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Roadside unit location for information propagation promotion on two parallel roadways with a general headway distribution

Liang

Tian

et al. 2018

IET Intelligent Transport Systems

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Section: Modelling the Information Propagation Processmentioning

confidence: 99%

“…Under condition

d > \sqrt{3} R / 2

d > \sqrt{3} R / 2

will be addressed in a future study.…”

Section: Modelling the Information Propagation Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Roadside unit location for information propagation promotion on two parallel roadways with a general headway distribution

Liang

Tian

et al. 2018

IET Intelligent Transport Systems

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“…They factor the effects of the random positions of equipped vehicles in the traffic stream on information flow propagation. Simulation and analytical models have been developed to analyze V2V propagation performance in terms of the expected information propagation distance (Wang, 2007;Wang et al, 2010;Wang et al, 2011;Wang et al, 2012; Yin et al, 2013;Wang et al, 2015;Du and Dao, 2015;Du et al, 2016), under different traffic flow scenarios. However, these models oversimplify the effects of communication constraints by assuming that information can be retransmitted instantaneously.…”

mentioning

confidence: 99%

Multiclass information flow propagation control under vehicle-to-vehicle communication environments

Wang

Peeta

et al. 2019

Transportation Research Part B: Methodological

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Most existing models for information flow propagation in a vehicle-to-vehicle (V2V) communications environment are descriptive. They lack capabilities to control information flow, which may preclude their ability to meet application needs, including the need to propagate different information types simultaneously to different target locations within corresponding time delay bounds. This study proposes a queuing-based modeling approach to control the propagation of information flow of multiple classes. Two control parameters associated with a vehicle, the number of communication servers and the mean communication service rate, are leveraged to control the propagation performance of different information classes. A two-layer model is developed to characterize the information flow propagation wave (IFPW) under the designed queuing strategy. The upper layer is formulated as integrodifferential equations to characterize the spatiotemporal information dissemination due to V2V communication. The lower layer characterizes the traffic flow dynamics using the Lighthill-Whitham-Richards model. The analytical solution of the asymptotic density of informed vehicles and the necessary condition for existence of the IFPW are derived for homogeneous traffic conditions. Numerical experiments provide insights on the impact of the mean communication service rate on information spread and its spatial coverage. Further, a numerical solution method is developed to solve the two-layer model, which aids in estimating the impacts of the control parameters in the queuing strategy on the IFPW speed under homogenous and heterogeneous conditions. The proposed modeling approach enables controlling the propagation of information of different information classes to meet application needs, which can assist traffic managers to design effective and efficient traffic management and control strategies under V2V communications.Keywords: Vehicle-to-vehicle communications, multiclass information flow propagation, queuing system, density of informed vehicles, information flow propagation speed. (S. Peeta) 2 and/or network-level traffic management strategies. Further, V2V-based traffic systems enable decentralized information generation and dissemination. Vehicles in a V2V-based system can generate information and relay it to other vehicles through multi-hop processes. Unlike centralized information systems, a V2V-based traffic system can potentially provide timely information in emergency/disaster situations by avoiding delays associated with data collection and communication with control center.Understanding the characteristics of spatiotemporal information flow propagation in a V2V-based traffic system is important as most applications require timely and reliable information delivery. However, modeling information flow propagation in space and time is challenging. Factors from both traffic flow domain and communications domain significantly affect the reliability of V2V communication and information propagation. The traffic flow dynamics affect occurre...

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