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The effective performance of arterial corridors is essential to communitysafety and vitality. Managing this performance, considering the dynamic natureof demand requires updating traffic signal timings through various strategies.Agency resources for these activities are commonly scarce and are primarily bypublic complaints. This paper provides a data-driven prioritization approachfor traffic signal re-timing on a corridor. In order to remove any dependenceon available detection, probe-based data are used for assessing the performancemeasures. Probe-based data are derived from in-vehicle global positioningsystem observations, eliminating the need for installing on-field trafficinfrastructure. The paper provides a workflow to measure and compare differentsegments on arterial corridors in terms of probe-based signal performancemeasures that capture different aspects of signal operations. The proposedmethod can serve as a tool to guide agencies looking to alter their signalcontrol. The methodology identifies a group of dynamic days followed byevaluation of travel rate based upon non-dynamic days. Dynamic days representthe variability of traffic on a segment. Performance measures on non-dynamicdays include Median Travel Rate, Within-Day Variability of travel rate,between-days variability of travel rate Minimum Travel Rate Dispersion, and twovariables which include Overall Travel Rate Variabilities. Consequently, acorridor having high number of dynamic segments along with poor performanceduring normal days would be a candidate for adaptive control. A case study wasconducted on 11 corridors within Des Moines, Iowa where Merle Hay Road andUniversity Avenue were identified suitable for adaptive control.

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