From gridlock to green light: How can AI transform Philippines’ traffic

Written by Raul III "Cricket" Santiago, Managing Director, Fujitsu Philippines

Manila's traffic congestion is amongst the world's worst, significantly impacting the city's economy and the quality of life for Filipinos. In 2023, it held the unenviable title of the world's most congested metro area according to the TomTom Traffic Index.

The daily struggle is a constant reality, requiring innovative solutions.

Driving change with new technology for road traffic in the Philippines

The Philippine government officially launched the Road Safety Action Plan (RSAP) in 2017 as part of its commitment to improving road safety and addressing the country's high rates of traffic-related injuries and fatalities. It provides a framework for the Philippine government to implement a variety of road safety strategies. 

How can artificial intelligence (AI) help the government achieve its goals?

Here are three possible ways how AI can help the Philippines move towards a more efficient, responsive, and safer transportation system:

 

1. Intelligent traffic surveillance: Seeing beyond the gridlock

Current methods of monitoring traffic rely heavily on manual observation and often miss crucial details.

Vision AI uses machine learning to accurately count and classify vehicles, providing a real-time comprehensive picture of traffic flow. The data-driven insights will allow for proactive interventions to prevent accidents and reduce congestion. 

For example, a city like Montreal, once struggled with severe congestion, particularly around its port, drastically improved its traffic flow using Fujitsu's AI-enabled data analysis platform to optimize the management of 2,500 traffic lights. This solution allows the city to make data-driven decisions that improve traffic flow, reduce fuel consumption, and lower air pollution. This is a success story that demonstrates Vision AI's potential for addressing Manila's traffic challenges.

2. Rapid incident response: Seconds that save lives 

In a traffic emergency, prompt action is critical. Traditional methods frequently react too slowly, resulting in escalating incidents and widespread gridlock. 

AI-powered systems can detect road incidents - such as accidents, stalled vehicles, or unusual pedestrian behavior - and notify traffic operators immediately. This will dramatically improve response times, allow for quicker intervention, reduce disruption, and potentially save lives. 

Japan's highway system provides a compelling example of how AI can help contribute directly to the government’s objective of safer roads. Fujitsu's AI-powered traffic management system has significantly improved highway safety, particularly during inclement weather, by providing real-time data that enables proactive accident prevention.

3. Advanced traffic forecasting: Seeing beyond the obvious

Traditional systems frequently struggle to analyze complex traffic conditions in real time, especially in areas with low visibility. 

AI's advanced modeling abilities can overcome these constraints. By analyzing historical data and real-time feeds, AI can identify potential bottlenecks and congestion hotspots, allowing for proactive changes to traffic signals and infrastructure planning. 

Fujitsu and Carnegie Mellon University's collaboration on AI-powered social digital twin technology in Pittsburgh, USA, demonstrates this potential. The system captures highly detailed real-time traffic images, identifying potential hazards even in blind spots, leading to a significant reduction in accidents in Pittsburgh.

We believe that an AI-powered traffic management requires a three-pronged approach

To fully realize AI's potential, a robust data collection system, a scalable cloud infrastructure, and a real-time alert system are required. This strategic approach will enable organizations to make data-driven decisions immediately.

• Robust data collection: Deploying a strategically planned network of high-resolution cameras and sensors across key areas in the Philippines will lay the groundwork for AI-driven insights.
• Scalable cloud architecture: A robust and scalable cloud infrastructure will be implemented to efficiently process the sensor network's massive amount of data. This architecture ensures that system capacity keeps up with future growth and technological advancements.
• Real-time actionable response systems: Seamless integration of AI-driven insights with existing and future traffic management systems will enable real-time, adaptive responses, optimizing traffic flow and enhancing safety.

With these components in place, decision makers can leverage the power of AI to transform the country's approach to traffic safety. This will contribute to a more efficient, safer, and responsive transportation system, achieving the goals of the government's Road Safety Action Plan (RSAP) and improving the lives of all Filipinos.