期刊
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
卷 85, 期 -, 页码 377-395出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2017.09.023
关键词
Information flow propagation wave; V2V communications; Epidemic model; Communication kernel; LWR model
资金
- NEXTRANS Center, the USDOT Region 5 University Transportation Center at Purdue University
- National Science Foundation [CMMI-1435866]
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [1435866] Funding Source: National Science Foundation
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.
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