“Rama IV Model”: A traffic problem solution and management project for Rama IV road

     When asked what problem the people of Bangkok would like most urgently addressed, many would undoubtedly cite "traffic congestion". Traffic congestion, a complex issue, has been a longstanding problem, significantly affecting the residents of Bangkok. Commuting takes longer, causing missed opportunities, wasted time, and negatively impacting health.

     The "Rama IV Model" project, launched to unlock traffic data for a better future, is a collaborative initiative of the Ministry of Transport, Bangkok Metropolitan Administration (BMA), Metropolitan Police Bureau, Chulalongkorn University, GRAB Thailand, and Toyota Mobility Foundation. This partnership aims to investigate and solve Bangkok's traffic problems using advanced technologies and data gathered from various related agencies. These data will be used to study, analyze, and predict traffic patterns to improve traffic management on Rama IV Road, which stretches for 12 kilometers, arguably Bangkok's busiest road, covering large community areas and broadly impacting residents.

The data used in this project comes from both public and private sector databases:

• GPS data of vehicles provided by GRAB via its mobile application
• GPS data of other types of public transport from the Ministry of Transport
• Images from CCTV cameras and traffic data from the BMA
• Accident statistics from the Metropolitan Police Bureau

     These data will be analyzed using modern technologies like AI and Machine Learning by Chulalongkorn University. This will provide a multifaceted understanding of the issues and predict future traffic patterns. The findings will be beneficial for designing and planning traffic management systems, developing transport networks, and improving city planning for future suitability.

The project has three main expectations:

1. Use data to enhance traffic visualization and interlink various data sets.
2. Identify the real causes and possible solutions to traffic congestion and other events using deep data insights from various data sets and validate them through quality measurements.
3. Summarize and share learned lessons and suggestions in terms of methods/principles with the relevant parties.

Source: Chulalongkorn University
Tel. +66 2215 3555
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