Freeway Traffic Safety And Efficiency Enhancement Through Adaptive Roadway Lighting And Control Enabled By Connected Infrastructure Networks
MetadataShow full item record
Visibility of the roadway and roadside objects often decreases as light (from natural and artificial sources) diminishes under a certain level. Roadway lighting, when used appropriately for the given context and conditions, can be an effective means for increasing visibility; however, inappropriate lighting can lead to issues such as glare. Recently, adaptive roadway lighting has been given increasing attention as a means to reduce lighting levels to save energy while maintaining safety performance. Adaptive lighting scenarios have the ability to adjust roadway lighting levels on the basis of real-time data such as traffic volume and weather conditions. In this project, an adaptive lighting methodology was developed on the basis of a comprehensive review of the literature, as well as data collected in Washington State at sites where systems capable of adaptive lighting (dimming and on/off operation of specific lights by time of day) were installed by the Washington State Department of Transportation (WSDOT). Data sources considered in the methodology included traffic data, weather data, crash data, etc. The methodology employed an active traffic management component that allowed for provision of advisory messages based on data used in the lighting methodology itself. An adaptive lighting simulation platform was also developed and used to compare the lighting index (a dimensionless quantity based on illuminance) of the developed methodology versus other conventional and common adaptive lighting methodologies. The platform made use of both traffic and communication simulation platforms to enable real-time vehicle detection and influence on lighting conditions. Results from comparing the indices showed that the proposed method was comparably more efficient than existing adaptive methods and hence allowed for energy savings over these conventional methods. Thus, the proposed adaptive methodology has the potential to cut down energy spending remarkably without degrading traffic safety and efficiency.