Analysis of Traditional and Promising Methods for Managing Passenger Mobility in Urban Bus Systems

Abstract

Reliable passenger-flow data are crucial for both planning and real-time operation of urban bus services. This paper compares traditional manual survey techniques (reporting-statistical, questionnaire, manual counting and ticket-based approaches) with automated solutions based on Automatic Passenger Counting (APC), GNSS positioning and telematics communication. Using a structured literature review, functional-architecture analysis and an illustrative simulation micro-case, the study defines evaluation criteria (accuracy, continuity of monitoring, labor intensity, CAPEX/OPEX, interoperability and privacy risks) and proposes an end -to-end reference architecture for a digital mobility-management ecosystem integrating onboard units, a dispatch- center analytics platform, passenger information services and automated fare collection. A reproducible KPI- based headway/holding rule set is formulated with explicit parameters and linked to a phased deployment roadmap for Nukus. The findings show that manual surveys remain useful for rapid snapshots but cannot support continuous monitoring, whereas automated monitoring enables KPI-driven management and data- driven route and timetable optimization when open standards (GTFS/GTFS-Realtime, SIRI) and basic data- governance controls are applied. The proposed framework is supported by a reproducible simulation micro- case, operational-style data examples, and a pilot-ready validation protocol for phased regional deployment in Nukus. While broader field validation remains a logical next step, the present results already demonstrate the practical feasibility and applied decision-support value of the proposed approach.