Massively Parallelizable Approach for Evaluating Signalized Arterial Performance Using Probe-based data

TL;DR

This paper introduces a scalable, probe-based data-driven method for evaluating and prioritizing arterial corridor segments for traffic signal re-timing, supporting adaptive control without additional infrastructure.

Contribution

It presents a novel workflow using GPS probe data to assess signal performance and identify segments suitable for adaptive control, reducing reliance on traditional detection methods.

Findings

Case study identified Merle Hay Road and University Avenue as candidates for adaptive control.

Method effectively measures signal performance using GPS probe data.

Workflow enables prioritization of corridor segments for re-timing improvements.

Abstract

The effective performance of arterial corridors is essential to community safety and vitality. Managing this performance, considering the dynamic nature of demand requires updating traffic signal timings through various strategies. Agency resources for these activities are commonly scarce and are primarily by public complaints. This paper provides a data-driven prioritization approach for traffic signal re-timing on a corridor. In order to remove any dependence on available detection, probe-based data are used for assessing the performance measures. Probe-based data are derived from in-vehicle global positioning system observations, eliminating the need for installing on-field traffic infrastructure. The paper provides a workflow to measure and compare different segments on arterial corridors in terms of probe-based signal performance measures that capture different aspects of signal operations. The proposed method can serve as a tool to guide agencies looking to alter their signal control. The methodology identifies a group of dynamic days followed by evaluation of travel rate based upon non-dynamic days. Dynamic days represent the variability of traffic on a segment. Performance measures on non-dynamic days include Median Travel Rate, Within-Day Variability of travel rate, between-days variability of travel rate Minimum Travel Rate Dispersion, and two variables which include Overall Travel Rate Variabilities. Consequently, a corridor having high number of dynamic segments along with poor performance during normal days would be a candidate for adaptive control. A case study was conducted on 11 corridors within Des Moines, Iowa where Merle Hay Road and University Avenue were identified suitable for adaptive control.