Singapore's Land Transport Authority (LTA): A Case Study of Predictive AI and Centralized Coordination in Urban Traffic Management

Guo, Hanxiang and Leong, Wa Yie (2025) Singapore's Land Transport Authority (LTA): A Case Study of Predictive AI and Centralized Coordination in Urban Traffic Management. Journal of Innovation and Technology, 2025 (12). pp. 1-7. ISSN 2805-5179

	Text joit2025_12.pdf - Published Version Available under License Creative Commons Attribution. Download (144kB)
	Text 737 - Published Version Available under License Creative Commons Attribution. Download (22kB)

Abstract

This study examines Singapore’s Smart Mobility strategy through the predictive and centralized system operated by the Land Transport Authority (LTA). Using the four-dimensional ITS framework including data acquisition, network connectivity, analytical intelligence, and operational responsiveness, the paper evaluates how predictive artificial intelligence and integrated control systems contribute to urban traffic management. The study finds that Singapore’s centralized, predictive governance model has led to notable improvements in average expressway speed, bus punctuality, and incident clearance times. However, limitations remain in areas such as system adaptability and data transparency. Comparative discussion with international cities offers insight into the scalability and constraints of such predictive transport systems.

Item Type:	Article
Uncontrolled Keywords:	Singapore, Land Transport Authority, Smart Mobility 2030, Predictive AI, Intelligent Transport Systems, Urban Traffic Governance
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > TE Highway engineering. Roads and pavements
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	01 Oct 2025 01:46
Last Modified:	01 Oct 2025 01:46
URI:	http://eprints.intimal.edu.my/id/eprint/2187

Actions (login required)

View Item