01520072

Component

Recent technological developments enable vehicles in a traffic network to communicate with each other and share travel experience data through vehicle-to-vehicle (V2V) communications. A V2V communications-capable vehicle continuously updates its knowledge using its own experience and anonymously obtained travel experience data through V2V communications. Dynamics of traffic flow and V2V communication events lead to the dynamics of information flow which is a key dimension in V2V communication-based traffic management systems. However, less attention has been focused on understanding and modeling the dynamics of information flow explicitly. In this context, this study proposes a graph theoretical representation of the dynamics of information flow under V2V communications, and a graph-based search model to characterize the evolution of traffic information. It provides insights into the interactions between the dynamic traffic flow, V2V communication events, and the dynamic information flow and enables the travel information system to track the spatiotemporal mechanisms of V2V communications. Results from synthetic experiments indicate that sharing of nodes and links to represent the evolution of traffic information leads to more efficient memory usage compared to a simulation-based approach which needs to individually store the traffic information for each vehicle to update the knowledge of other vehicles. Further, the graph-based search model leads to implementation efficiency by circumventing redundant updates of vehicle knowledge. The proposed graph theoretical model bridges key methodological gaps in the context of V2V communication based real-time traffic information systems, in terms of modeling efficiency and the need to understand the evolution of traffic information.

This paper was sponsored by TRB committee ADB30(8) Paper Review Group #4.

01503729

14-3144

English

19p

2014

Transportation Research Board 93rd Annual Meeting

Digital/other

Figures; References; Tables

Driver information systems; Graph theory; Information dissemination; Network links; Network nodes; Real time information; Traffic flow; Vehicle to vehicle communications

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2014 Paper #14-3144

TRIS, TRB, ATRI

Jan 27 2014 3:05PM