Modeling the information flow propagation wave under vehicle-to-vehicle communications

被引:19
作者
Kim, Yong Hoon [1 ]
Peeta, Srinivas [2 ]
He, Xiaozheng [3 ]
机构
[1] Univ Windsor, Civil & Environm Engn, 401 Sunset Ave, Windsor, ON N9B 3P4, Canada
[2] Purdue Univ, Sch Civil Engn, 550 Stadium Mall Dr, W Lafayette, IN 47907 USA
[3] Rensselaer Polytech Inst, Dept Civil & Environm Engn, 110 8th St, Troy, NY 12180 USA
基金
美国国家科学基金会;
关键词
Information flow propagation wave; V2V communications; Epidemic model; Communication kernel; LWR model; CELL TRANSMISSION MODEL; CONNECTIVITY; SPREAD; NETWORK; SAFETY; MOBILE;
D O I
10.1016/j.trc.2017.09.023
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Vehicle-to-vehicle (V2V) communications under the connected vehicle context have the potential to provide new paradigms to enhance the safety, mobility and environmental sustainability of surface transportation. Understanding the information propagation characteristics in space and time is a key enabler for V2V-based traffic systems. Most existing analytical models assume instantaneous propagation of information flow through multi-hop communications. Such an assumption ignores the spatiotemporal relationships between the traffic flow dynamics and V2V communication constraints. This study proposes a macroscopic two-layer model to characterize the information flow propagation wave (IFPW). The traffic flow propagation is formulated in the lower layer as a system of partial differential equations based on the Lighthill-Whitham-Richards model. Due to their conceptual similarities, the upper layer adapts and modifies a spatial Susceptible-Infected epidemic model to describe information dissemination between V2V-equipped vehicles using integro-differential equations. A closed-form solution is derived for the IFPW speed under homogeneous conditions. The IFPW speed is numerically determined for heterogeneous conditions. Numerical experiments illustrate the impact of traffic density and market penetration of V2V-equipped vehicles on the IFPW speed. The proposed model can capture the spatiotemporal relationships between the traffic and V2V communication layers, and aid in the design of novel information propagation strategies to manage traffic conditions under V2V-based traffic systems.
引用
收藏
页码:377 / 395
页数:19
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