Passengers-using-a-wooden-abra-boat-to-cross-the-Creek-in-Dubai-pic-by-RTA-1715608628911
People onboard a traditional wooden boat, called abra, in Dubai Creek Image Credit: Supplied

Dubai: Public marine transport timings in Dubai are now changing according to the season of the year.

The Roads and Transport Authority (RTA) has recently started implementing the ‘Seasonal Network’ operational schedule for marine transport services. This initiative uses big data to analyse daily passenger patterns to match them with trip timetables and service frequencies to suit various seasons - mainly summer and winter.

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The initiative targets all operated maritime transport services and lines (Dubai Ferry, Abra, Dubai Water Taxi). The operational timing will be adjusted to suit the nature of each season and the movement of residents, tourists, and visitors throughout the year. The initiative was developed to ensure the sustainability of services, meet customer needs, and improve the occupancy rate of maritime transport while reducing operational expenses.

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RTA embarked on this summer plan by leveraging big data, which provides access to all information related to marine transport services, such as passenger numbers, revenues, and detailed occupancy rates. Such inputs enrich service development studies and significantly improve the efficiency of the network, the RTA said.

The use of big data and analysis of marine transport riders’ patterns allow for greater flexibility in preparing and implementing the seasonal network initiative for maritime transport. This includes the use of predictive analysis to study and analyse network data, besides predicting the impact of changes, flexible operating schedules and journey frequency on passenger numbers, occupancy rates, revenues, and ridership.

The project study involved developing internal algorithms, analysing, and processing big data from multiple sources, and creating a flexible operating plan for the marine transport network. Such a plan should be used to align future marine transport operations with customer needs and predict future passenger patterns in the sector.