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A joint big data analytics initiative between Grab, The World Bank, and the Philippines' Department of Transportation and Communications (DOTC) aims to tap real-time traffic data to ease traffic congestion and address road safety issues.

Called OpenTraffic, the open source platform is scheduled to soon provide traffic management agencies and city planners access to the data to monitor traffic flows within the Philippines's Cebu City and Metro Manila.

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The World Bank and Grab had developed the analytics platform using "free, open source tools" that would convert the ride-sharing operator's driver GPS data into anonymised data, such as traffic flows, speeds, and intersection delays. According to the joint statement, this information could be used to identify road incident hotspots and improve emergency response time.

The OpenTraffic platform would be made available "in the near future" to other government agencies and city planners across Southeast Asia, the companies said. Grab's ride-sharing services are available in six countries in the region including Singapore, Indonesia, Thailand, and Vietnam.

DOTC Secretary Joseph Emilio A. Abaya said: "Using big data is one of the potential solutions to the challenges faced by our transport systems. Through this, we can provide accurate, real-time information that can help alleviate traffic congestion and improve road safety."

The World Bank and DOTC last month trained more than 200 government officials across several local agencies, including the Philippine National Police and Metro Manila Development Authority.

Pilot trials on the platform would focus on various areas including peak hour analysis along key corridors, travel time reliability, and road incident hotspots.

Traffic data generated through OpenTraffic also eventually would be used to support another application, called Data for Road Incident Visualisation, Evaluation, and Reporting (DRIVER). Developed by The World Bank, the app would facilitate road incident reporting and analysis as well as enable engineering personnel to identify areas prone to accidents and prioritise these for interventions as well as to improve emergency response.

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