Simulated Vehicle-to-Vehicle Message Propagation Efficiency on Atlanta's I-75 Corridor

Exploitation of in-vehicle information technology (e.g., mobile computing and wireless communications) in surface transportation systems is a clear emerging trend. Equipping vehicles with computing, communication, and sensing capabilities presents significant opportunities for a vast array of transportation services. Vehicle-to-vehicle communication may be considered for applications such as incident detection, traveler information dissemination, network operations, etc. In-vehicle computing systems facilitate the customization of information services to the needs and characteristics of individual travelers. In addition, in-vehicle systems allow coverage to extend beyond areas where roadside equipment has been placed. This study provides the initial investigation needed to test the feasibility of these advanced communication networks. Several observations may be drawn from this study. First, vehicle-to-vehicle communication is a feasible way to propagate information along freeways in metro areas, although propagation performance depends critically on factors such as the density of instrumented vehicles along the end-to-end path. Second, the simulation methodology described within this study allows one to estimate the minimum required fleet penetration ratio for effective communication, given the traffic density and application requirements. Third, the message propagation delay is highly variable when instrumented vehicle density is low. A particular delay may be well below or above the average depending on traffic conditions. For applications requiring highly reliable, minimal message propagation it may be necessary to design networks that provide extra support to avoid such variation. Future research is required to examine additional traffic conditions (e.g., congestion due to an incident) and study the effectiveness of this approach for particular applications. TRB 2005 Annual Meeting CD-ROM Paper revised from original submittal. Wu, H., J. Lee, M. Hunter, R. Fujimoto, R. Guensler, J. Ko 3