Microscopic Estimation of Arterial Vehicle Positions in a Low Penetration Rate Connected Vehicle EnvironmentPoster
Wireless communication among vehicles and roadside infrastructure, known as connected vehicles, is expected to provide higher-resolution real-time vehicle data, which will allow more efficient traffic monitoring and control. Adoption of connected vehicle technology among the vehicle fleet may be gradual or limited, with many drivers unable or unwilling to participate. Additionally, many connected vehicle mobility applications requiring individual vehicle location data need a minimum of 20-30% of roadway vehicles participating to experience benefits. In an effort to improve the performance of connected vehicle applications at low connected vehicle penetration rates, we propose a novel technique to estimate the positions of non-communicating (unequipped) vehicles based on the behaviors of communicating (equipped) vehicles along a signalized arterial. Unequipped vehicle positions are estimated based on observed gaps in a stopped queue, and the forward movement of these estimated vehicles are simulated microscopically using a commercial traffic simulation software package. Based on the effective penetration rate metric, the algorithm makes more correct than incorrect estimates at an accuracy of approximately 7 meters. When applied to a previously-developed connected vehicle traffic signal control strategy, the location estimation algorithm produced small improvements in delays, stops, and stopped delay when compared to an equipped vehicle-only scenario at penetration rates of 25% or less. The location estimation algorithm is generic, and could be applied to other connected vehicle applications to improve performance at low penetration rates.
93rd Annual Meeting of the Transportation Research Board. Washington, DC.
Transportation Research Board
Virginia Department of Transportation