DOI

10.5703/1288284317755

Abstract

Identification of congested traffic signals that require capital investment to increase capacity has historically been a time-consuming process. Signalized intersections with congestion were analyzed to see if they could be improved through retiming, and capital investment was only considered if retiming is deemed infeasible. Automated Traffic Signal Performance Measures (ATSPMs), and more recently, signal performance measures (SPMs) derived from connected vehicle (CV) trajectory data, have already been used to streamline the process of identifying signalized intersections that can be improved through retiming. However, to date, similar efforts have not been used to identify intersections that may benefit from capital investment. This study developed a CV-based methodology to assess whether signal retiming could potentially be feasible for a given signalized intersection using the split failure percentage (SF) SPM. For intersections where retiming is not feasible, a ranking metric of critical path split failing trajectory counts (SfnCP) was developed for prioritization by capacity improvement necessity. This metric was implemented statewide to over 2,300 INDOT-managed signalized intersections over a 17-month timespan to demonstrate the effectiveness, efficiency, and scalability of the proposed approach. Additionally, the utility of CV data for similar ranking of unsignalized intersections and road segments was also discussed. To aid INDOT engineers with rapid identification and prioritization of intersections that can be considered for capital investments, performance reports containing various attributes were proposed and generated.

Report Number

FHWA/IN/JTRP-2024/20

Keywords

traffic signal, intersection, road segment, performance measure, capacity, connected vehicle, big data, capital investment

SPR Number

4857

Performing Organization

Joint Transportation Research Program

Publisher Place

West Lafayette, Indiana

Date of this Version

2024

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