AI-Driven Approach for Enhancing Sustainability in Urban Public Transportation

Sustainability, Год журнала: 2024, Номер 16(17), С. 7763 - 7763

Опубликована: Сен. 6, 2024

The functioning of modern urban environments relies heavily on the public transport system. Given spatial, economic, and sustainability criteria, in larger areas is unrivaled. system’s role depends quality service it offers. Achieving desired requires a design that meets demands. This paper uses data-driven approach to address headway deviations lines explores ways improve regularity during phase. Headway critical dynamic element for organization passenger quality. Deviations between planned actual headways represent disturbances. On with under 15 min, passengers typically do not consult schedules, making punctuality less crucial. Reduced affects average travel time, time uncertainty, comfort. Ideally, system operates regular headways. However, disturbances can spread affect subsequent departures, leading vehicle bunching. While previous research focused single primary disturbances, this study, help AI (reinforcement learning), examines multiple cities Belgrade, Novi Sad, Niš. goal model cumulative impact these movement. By ranking parameter influences using automatic optimization static line elements, aims increase resilience results could also be useful developing adaptive management systems leverage IoT technologies continuously optimize response real-time data, ultimately enhancing satisfaction.

Язык: Английский

Network extension planning towards resilient urban critical infrastructures using deep reinforcement learning

Applied Soft Computing, Год журнала: 2025, Номер 176, С. 113163 - 113163

Опубликована: Апрель 16, 2025

Язык: Английский

Optimizing Safe and Sustainable Public Transit for Wellness Tourism: Southeast Asian Case Studies

Journal of Cleaner Production, Год журнала: 2024, Номер unknown, С. 143656 - 143656

Опубликована: Сен. 1, 2024

Язык: Английский