RTA uses AI to optimise seasonal marine transport network

Dubai: Dubai's Roads and Transport Authority (RTA) has enhanced its Seasonal Network initiative for marine transport services by deploying flexible scientific and technical methods powered by artificial intelligence and predictive analytics.

The initiative strengthens operational agility and enables the network to respond effectively to demand fluctuations during seasons, public holidays and major events across the emirate.

The initiative forms part of RTA's ongoing efforts to develop the marine public transport network and strengthen its integration with various transport modes across the emirate, keeping pace with rapid growth and meeting the aspirations of residents and visitors alike.

The implementation of the summer season operating plan will begin in July, noting that the plan is built on an integrated big-data repository containing detailed information on passenger numbers, revenue and occupancy rates. The data will enhance forecast accuracy and support more effective operational decision-making.

Khalaf Belghuzooz Al Zarooni, Director of Marine Transport at RTA's Public Transport Agency, said, "The Seasonal Network was developed using advanced in-house algorithms and AI-powered analytical and predictive tools capable of processing and analysing big data from multiple sources. These tools support flexible and dynamic operating plans for the marine transport network. They also help forecast future demand and apply season-specific operating models, striking a balance between meeting customers' needs and enhancing operational efficiency."

He stated that the network's development integrates the human element and customer needs alongside the technical dimension. Customer requirements are embedded in service design by capturing suggestions and requirements submitted through approved channels, ensuring alignment between the human and technical aspects.

Al Zarooni added, "The project methodology used predictive analytics to study marine transport usage patterns and assess the impact of different variables on operating schedules and service headways, in line with passenger numbers, occupancy rates and operational revenues, reflecting positively on service quality and sustainability.

"Big-data analytics and modern computing applications have enabled us to develop a flexible operating model capable of simulating customer behaviour patterns and forecasting demand for marine transport services. The model contributes to improving network efficiency and achieving optimal performance levels in line with precise schedules and international standards."

The Seasonal Network initiative is implemented independently for each season, ensuring that customer requirements are not affected while advancing the targets of the marine transport sector. The approach supports financial and operational sustainability and reinforces Dubai's position as a leading city in adopting smart and innovative solutions in the transport sector.