The application of digital twins (DTs) and artificial intelligence (AI) in public transportation has significantly improved traffic management and efficiency. Techniques such as agent-based modelling, reinforcement learning, and multi-agent systems have been used to dynamically adjust traffic signals and reroute vehicles, reducing congestion and improving traffic flow. Additionally, DT-centric approaches for driver intention prediction and adaptive multi-agent networks have shown potential in managing large-scale IoT systems. This study investigates the integration of DT standards and advanced AI methods, such as multi-agent systems and predictive models, to enhance the decision-making processes in the TransMilenio transportation system. The findings demonstrate that the model proposed can reduce the waiting time of passengers within the system.
AI-Powered Digital Twins for Public Transportation: A Multi-agent Model for Transmilenio in Bogota
Studies Comp.Intelligence
International Workshop on Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future ; 2024 ; Augsburg, Germany September 25, 2024 - September 26, 2024
Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future ; Chapter : 10 ; 133-146
2025-07-03
14 pages
Article/Chapter (Book)
Electronic Resource
English
Bus Rapid Transit weltweit - TransMilenio in Bogotá
Online Contents | 2006
Eine Stadt im Umbruch - TransMilenio in Bogotá
IuD Bahn | 2006
|Applicability of TransMilenio Bus Rapid Transit System of Bogotá, Colombia, to the United States
Online Contents | 2007
|Applicability of TransMilenio Bus Rapid Transit System of Bogotá, Colombia, to the United States
Transportation Research Record | 2007
|