Data-Driven Decision Support Platform for Selection of Intersections for Adaptive Traffic Signal Control

Abstract

Adaptive traffic control systems (ATCSs) represent one of the most advanced traffic signal control strategies currently deployed in urban areas worldwide. One of the most important questions in the deployment of such a system is related to the determination of location (i.e., intersection/s, corridor) where ATCS should be deployed. Several past studies addressed this problem either for the specific “corridor-level” analysis or by using inadequate approaches that prevent agencies from observing how existing assets and their operational characteristics affect agency-wide deployment of ATCS. This study proposes a data-driven dashboard that uses the operational attributes of existing assets (usually readily available to many agencies nowadays) to rank assets/corridors in the network based on their “appropriateness” for the installation of ATCS systems. The core components of the proposed tool are a robust scoring engine that incorporates the signal parameters important for ATCS deployment, and a spatial module that aggregates the computed scores on a desired spatial level. These core components are encapsulated in a web-based map tool deployed on the cloud. The proposed tool has been deployed in a case study to support the installation of 1,100 ATCS signals in the road network of Miami-Dade County, Florida. The proposed tool was useful for producing an initial solution in the decision-making process on where to install ATCS. The developed tool is robust enough to be applied to other networks.