Enhancing Smart Urban Mobility through Digital Twin-driven Autonomous Transportation and Predictive Maintenance
Aderibigbe, Michael Oluwaseyi *
Department of Industrial and Production Engineering, Federal University of Technology, Akure, Nigeria.
Kehinde Temitope Olubanjo
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
Musa Abdulganiyu Babatunde
Department of Industrial and Production Engineering, Federal University of Technology, Akure, Nigeria.
Rasheed Adebayo Bello
Department of Civil Engineering, Olabisi Onabanjo University, Nigeria.
Abubakre Ademola Lawal
Department of Civil Engineering, Olabisi Onabanjo University, Nigeria.
Confidence Adimchi Chinonyerem
Abia State Polytechnic, Abia State, Nigeria.
Adeoti Shuaib Olamilekan
Department of Civil Engineering, University of Ilorin, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
The research formulates a digital twin-focused autonomous transport system with a double functionality of predictive maintenance and traffic control. Through a simulation-based approach, real-time traffic flow data and vehicle health data were consolidated into a digital twin platform for autonomous transport in a Lagos urban transport model. Artificial intelligence software, including anomaly detection, predictive repair, and reinforcement learning, as well as adaptive traffic management, was incorporated into the digital twin platform. Results indicate that the framework achieved a 27% decline in vehicle downtime, an 18% increase in component lifespan, and a 22% decline in maintenance expenditures. Concomitantly, traffic optimization results achieved a 31% decline in congestion and a 24% average improvement in travel time in the simulated urban corridors. The results support the capacity of digital twin technology to achieve real-time decision-making, increase operating reliability, and facilitate sustainable mobility in future urban environments. The study emphasizes the potential of digital twins as a new technology for future autonomous transportation systems.
Keywords: Digital twin, autonomous transport, predictive maintenance, traffic optimization, vehicle-to-infrastructure communication, reinforcement learning, smart mobility, sustainable urban development