Urban bus scheduling considering maximizing TWB under the fixed departure times: A case of Beijing

Abstract

Urban buses play a crucial role in urban transportation, and optimizing bus scheduling has emerged as a significant research area in transportation. However, existing studies have largely overlooked factors like travel satisfaction and subjective well-being when designing bus schedules. To bridge this gap and enhance passengers' well-being while promoting human-centric traffic management, this study employed a multiple linear regression model to establish a connection between passengers' perceived well-being and objective scheduling service attributes, such as perceived in-vehicle congestion, in-vehicle travel time, and waiting time at the station. By deriving a Travel Well-Being (TWB) index from these scheduling attributes, the study aimed to use it as a comprehensive optimization objective for bus timetable optimization. To validate the proposed optimization approach, a bus line in Beijing, China, was selected, and the results obtained using the Differential Evolution (DE) algorithm demonstrated that the scheduling model, incorporating well-being considerations, effectively increased the estimated well-being rate by 29.80% compared to the original timetable. This study contributes to establishing a human-centric and inclusive transportation system by integrating perceived subjective well-being into the optimization of bus timetables.