Artificial Intelligence is the next big thing at most government departments in the UAE and the Roads and Transport Authority (RTA) of Dubai seems to be leading the way in adopting the phenomenon.

From customer service and feedback management to drivers’ training and mass transit, AI is rapidly becoming instrumental in shaping Dubai’s expanding mobility sector. Long before the phrase was being used commonly, Dubai Metro hit the tracks as the world’s longest autonomous train network, piloted by artificial intelligence. RTA also conducted a test flight of the two-seater Autonomous Air Taxi (AAT) in September 2017, with the prototype provided by Volocopter, a German manufacturer of autonomous aerial vehicles.

The Volocopter autonomous air taxi on its test flight.

AI is now the RTA’s prime focus, with an aim to have one in four public transport journeys driverless by 2030. AI will also be employed in pedestrian crossings, driver training, monitoring of drivers, and communications.

Mohammad Al Khayyat, RTA’s Director of Smart Services, said, “RTA aspires to implement AI in many focus areas to deliver value to its core business as well as corporate aspects. These areas include traffic management, getting around Dubai, customer experience, cognitive licensing services, safety and, security, crisis management, intelligent administration, asset management, knowledge and innovation management.”

These are the key areas where the RTA is introducing artificial intelligence in:

Autonomous Transport

RTA Autonomous taxi on display at the GITEX 2018 tech exhibition.

“The future is autonomous and driverless transport and it heavily uses artificial intelligence technologies such as machine learning, deep learning, computer visions and robotics. With the aim of making one in four journeys on mass transit driverless in Dubai by 2020, RTA has developed a strategy to realise autonomous public transport that is more efficient, cleaner and safer,” said Mohammad Al Khayyat. He added that the RTA is planning to introduce AI-driven vehicles in different sectors of Dubai’s public transport including buses and taxis along with expanding the already autonomous Dubai Metro.

Customer Service

Mohammad Al Khayyat demonstrating the AI-driven Mahboub robot that can answer any question and offer as many as 90 RTA services.

“We are trying to engage more customers by developing self-service offerings. The customers’ happiness meter is based on AI and it gauges customer’s happiness through facial expression recognition,” said Al Khayat.

Safety and Efficiency

Al Raqeeb is an AI-driven safety and efficiency system for public buses that keeps an eye on bus drivers and alerts the command centre if it detects unusual activity. It has a sophisticated device fitted in front of the bus driver to monitor indications of fatigue, tiredness, or illness on the driver which are transmitted to the Control Room at the RTA where the case can be immediately responded to.

A trial phase of the system has shown that these monitoring devices have helped reduce fatigue-related cases by up to 88 percent.

Electric-Bus-AMENA-Auto-Dubai-UAE (2)
AI-driven monitoring will be fitted to buses to gauge signs of fatigue on drivers.

Smart pedestrian signals are run by a system based on sensors connected to a ground optical system synced to the signal’s light operation. It uses AI to detect pedestrian movement and readjusts the remaining time based on the inputs “for safe crossing for the largest possible number of pedestrians in a smooth manner with minimal impact on the movement of vehicles,” according to Al Khayyat.

Traffic Management

The Enterprise Command and Control Center (EC3) is also driven by AI, providing secure, scalable, and flexible operations. It serves as a city-wide crisis and traffic management centre. “The Big Data platform in EC3 has machine learning capabilities to enable traffic model calibration and multi-agent simulation for vehicle and people. In event planning, EC3 utilises AI for the management of accidents and crises, simulating various scenarios and reducing response time and human error,” said Al Khayyat.

This piece is adapted from the original article published in Gulf News.

All Images Credit: Gulf News