Citation

Dobrota N, Stevanovic A, Mitrovic N. Transp. Res. Rec. 2022; 2676(3): 660-684.

Copyright

(Copyright © 2022, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981211055668

PMID

unavailable

Abstract

Current signal retiming policies are deficient in recognizing the potential of emerging traffic datasets and simulation tools to improve signal timings. Consequently, current practice advocates the use of periodically collected (low-resolution) traffic datasets and deterministic (low-fidelity) simulation tools. When deployed in the field, such signal timings require excessive fine-tuning. The most recent trends promote the use of high-resolution data collected at 10 Hz frequency. While such an approach shows promise, the process heavily relies on specific data sets that are neither widely available nor clearly integrated into the existing signal retiming practices and procedures. Interestingly, data collected in an ongoing fashion and aggregated in several-minute bins (referred to here as medium-resolution) have not received much attention in the traditional retiming procedures. This study examines traditional signal retiming practices to provide a contextual framework for the other retiming alternatives. The authors define and classify different resolutions of various traffic data used in the signal retiming process and propose a signal retiming procedure based on widely available medium-resolution data and high-fidelity simulation modeling. The authors apply the traditional (low-resolution and low-fidelity) and a proposed (medium-resolution and high-fidelity) approach to a 28-intersection corridor in southeastern Florida. Signal timing plans developed from the proposed approach outperformed current plans from field and those plans developed in the traditional approach by reducing the average delay anywhere between 6.5 and 26%. With regard to the number of stops, changes for the traditional and proposed approaches were of much lower significance when compared with the field signal timings. The traveling speeds have been increased by 4.1%-18% by the proposed signal timings and delay was not transferred onto the neighboring streets, as was the case for plans developed by the traditional approach. Development, calibration, and validation of models within the proposed approach are more time-consuming and challenging than the modeling needs of the traditional approach. One direction of future research should address the automation of calibration and validation procedures. The other direction for future research should be related to the field evaluation of proposed signal timing plans.

Language: en

Keywords

arterial; clustering; data resolution; operations; optimization; signal timing; traffic signal; traffic signal systems