Systems based on AI monitor and manage traffic flow in real time

Summary: 

The AI-powered platform integrates data from various IoT sources to predict and detect potential rail anomalies, providing 24/7 visibility across the network. The system’s predictive capabilities enable the anticipation of about 90 percent of incidents, improving overall operational efficiency and commuter satisfaction.

Client: 

Singapore’s Land Transit Authority (LTA)

Problem Statement: 

Singapore’s urban mass transit system relies on sensors to collect information, oversee operations, and gather data for AI models that predict disturbances. While the previous system monitored the current and expected conditions of the rail network, it did not consider commuters’ experiences. To address this, Singapore’s Land Transport Authority (LTA) aimed to enhance the customer experience by employing IoT sensing, situation assessment, and incident response planning.

Results: 

• Ability for staff to make well-informed and thoroughly considered decisions.
• Rapid and efficient responses to large-scale disruptions.
• Ability to predict about 90 percent of impending incidents. 
• Possibility for rail operations staff to respond to most flow disturbances proactively, often several minutes or more before they occur.
• Increased productivity of the rail operations monitoring team. By the end of 2021, a team of four monitoring officers per shift was overseeing twice the number of stations that their counterparts in 2012 had managed.

AI Solution Overview:

The LTA  in collaboration with GovTech, developed the Fusion AnalyticS for public Transport Event Response (FASTER) system.

FASTER is an AI-driven data platform that gathers information from various IoT sources, including video streams, WiFi and cellular signals, farecard data, train engineering and flow data, as well as taxi and other transport data, to provide immediate warnings of potential rail anomalies. 

The system offers 24/7 visibility of the entire urban rail network, detecting unusual events and automatically issuing alerts when it predicts disturbances.

When a disturbance is either predicted or occurring, FASTER enhances real-time visibility for rail operations staff at both micro and macro levels. This allows them to observe how the event is impacting other rail stations and assess its system-wide effects.

 References: 

1. Singapore’s AI Applications in the Public Sector: Six Examples. https://mbrjournal.com/2023/07/25/singapores-ai-applications-in-the-public-sector-six-examples/ 
2. Steven M. Miller and Thomas H. Davenport, “A Smarter Way to Manage Mass Transit in a Smart City: Rail Network Management at Singapore’s Land Transport Authority,” AI Singapore website, May 27 2021, https://aisingapore.org/2021/05/a-smarter-way-to-manage-mass-transit-in-a-smart-city-rail-network-management-at-singapores-land-transport-authority/ 

Industry: Transport Services

Vendor: GovTech

Client: Singapore’s Land Transit Authority (LTA)

Publication Date: 2018