01618246

Component

https://doi.org/10.3141/2558-04

Turning movement count data (i.e., vehicle volumes broken down by movement, approach, and time periods) are the foundation of signal performance evaluations and a crucial component of a data-driven decision-making process used by transportation agencies. In this paper, the authors show how data available from intersections equipped with radar-based vehicle detection can be used to produce turning movement counts. A classification algorithm developed and discussed by the authors is capable of producing turning movement counts regardless of lane configuration and without the need for definition of detection zones. The algorithm works by using the data produced by vehicle detection systems that go unused and are never communicated to the signal controller. The nature of the data collection process makes the algorithm independent of the controller used. Results from the algorithm are promising; an average error of -0.26 vehicles per 15-min count period (absolute error of 2.31 vehicles) was obtained with the algorithm. Furthermore, the application of the algorithm provides an opportunity beyond signal operations. Processed trajectory data and results from the algorithm could be used to break the boundary that often exists between operations, planning, and safety, and thus show how a monitoring system that relies on the algorithm could help a traffic monitoring program meet the different—and sometimes competing—interests of agencies.

01618024

16-1744

English

pp 30-40

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309441315

Digital/other

Figures; Photos; References; Tables

Data analysis; Intersections; Traffic counts; Traffic lanes; Traffic signals; Turning traffic; Vehicle detectors

Data and Information Technology; Highways; Operations and Traffic Management

TRIS

Nov 30 2016 10:48AM

• Arterial Progression Optimization Using OD-BAND
• Assessing Longitudinal Arterial Performance and Traffic Signal Retiming Outcomes
• Connected Vehicle–Based Adaptive Signal Control and Applications
• Detector-Free Signal Offset Optimization with Limited Connected Vehicle Market Penetration: Proof-of-Concept Study
• Managing User Delay with a Focus on Pedestrian Operations
• Multimodal Intelligent Traffic Signal System Simulation Model Development and Assessment
• Optimal Cycle-Length Formulas for Intersections With or Without Transit Signal Priority
• Use of High-Resolution Signal Controller Data to Identify Red Light Running