Queue length estimation using conventional vehicle detector and probe vehicle data

摘要

The paper presents IntelliFusion, an algorithm that fuses inductive loop detector data with real-time vehicle probe data obtained from Connected Vehicles to enhance back of the queue estimates. The work also presents an evaluation of the data fusion algorithm using datasets produced by eTEXAS, a microscopic traffic simulation model for signalized intersections. Results of the evaluation show queue length estimates produced by the IntelliFusion algorithm are accurate to within the length of a single vehicle even at low levels of market penetration (e.g., LMP= 20%).