Public Transport Systems in Growing Cities: Planning, Operational Performance and the Commuter Experience

Urban areas across the world are experiencing unprecedented growth, placing increasing pressure on transportation infrastructure and public transport networks. Rapid urbanization, population expansion, economic development, and changing travel patterns have intensified challenges such as crowding, service unreliability, declining off-peak ridership, fare-policy strain, and unequal access to transit. In many cities, existing public transport systems struggle to meet growing demand while maintaining efficiency, reliability, affordability, and service quality. At the same time, post-pandemic shifts in commuting patterns and competition from private and ride-hailing modes have raised new questions about how transit agencies plan their networks, measure operational performance, and respond to rider expectations. Addressing these challenges increasingly relies on quantitative and model-based reasoning — from demand forecasting and network optimization to simulation of service operations — to translate complex urban dynamics into actionable, evidence-based decisions.The goal of this Research Topic is to advance understanding of the challenges and opportunities associated with public transport planning, operational performance, and commuter experience in rapidly evolving urban environments through quantitative and model-based research. It aims to bring together interdisciplinary contributions that apply quantitative methods, simulation frameworks, optimization techniques, and data-driven modelling approaches to examine how service planning strategies, operational performance metrics, technological tools for operations, and user-centred design can contribute to more efficient, inclusive, reliable, and rider-responsive transportation systems. By foregrounding analytical and modelling perspectives, this Research Topic seeks to encourage rigorous scholarly discussion and practical insights that support policymakers, planners, transit agencies, and operators in evidence-based service-delivery decisions for bus, BRT, metro, and rail networks.This Research Topic welcomes original research articles, review papers, case studies, methodological contributions, and policy-oriented studies addressing public transport systems and the commuter experience. In line with the scope of the Transportation Systems Modelling section, submissions are expected to include an analytical or model-based perspective — demonstrating how quantitative analysis, simulation, optimization, or data-driven modelling informs the questions addressed — while preserving the interdisciplinary nature of the topic across engineering, planning, economics, and the social sciences.The scope includes, but is not limited to:• Public transport network and service planning through optimization and mathematical programming;• Transit operations and scheduling, including timetabling, crew/vehicle scheduling, and simulation of service reliability, headway regularity, and bus bunching;• Service quality, reliability, and punctuality assessment using quantitative performance models;• Public transport performance evaluation and data-driven benchmarking;• Transit accessibility and first-/last-mile integration via accessibility and network models;• Traveller behaviour, commuter satisfaction, mode choice, and travel demand modelling for transit (including discrete choice and activity-based models);• Fare policy and ridership recovery analysed through demand and elasticity models;• Transit-oriented development assessed with land-use/transport interaction models;• Use of operational data analytics (AFC, AVL, smartcard, GTFS) for data-driven modelling and management of bus, metro, and rail services. Source: https://www.frontiersin.org/research-topics/82302/public-transport-systems-in-growing-cities-planning-operational-performance-and-the-commuter-experience