Evaluation and prioritization of public transport infrastructure remain pivotal challenges for urban planners and transport agencies. Traditional Level of Service (LoS) metrics, while useful, often overlook the compounded impacts of delays on passengers, particularly on heavily used transport corridors. This paper introduces the "Man-Hours (M-H) Factor", a novel evaluation metric that integrates vehicle operational data, travel time deviations, and passenger occupancy to quantify the potential cumulative burden of delays on passenger time. Using Manhattan’s and Kaohsiung’s public bus network as a case study, the methodology uses extensive data, including GPS-based travel times and hourly passenger counts, to recalibrate LoS metrics and identify high-priority inter-stop sections for intervention. The results reveal significant man-hour savings potential in select inter-stop sections and demonstrate how Man-Hours (M-H) Factor shifts prioritization to heavily utilized routes, offering a more equitable and actionable framework for decision-making. By incorporating passenger-centric metrics, this study provides a scalable, data-driven approach to the evaluation and planning of transport infrastructure, with broad implications for sustainable and equitable urban mobility systems. • Introduces the Man-Hours (M-H) Factor for passenger-centric delay evaluation. • Integrates GPS travel times and occupancy to enhance Level of Service metrics. • Identifies high-impact inter-stop segments in Manhattan and Kaohsiung bus networks. • Offers a scalable method for equitable and data-driven transport prioritization. • Shows M-H rankings are robust under moderate passenger demand fluctuations.
Jirmanova et al. (Thu,) studied this question.