Malaysia explores AI for faster accident detection
Malaysia considers AI for real-time road accident detection to improve emergency response times and save lives.
Malaysia is considering adopting an AI-driven system to improve road safety. The Automatic Road Incident Detection System (ARIDS), developed by a Universiti Putra Malaysia (UPM) team, uses neural networks to identify accidents and traffic anomalies in real time. Currently in pilot testing across 1,000km of expressways and roads, ARIDS has shown potential to reduce emergency response times significantly.
ARIDS, launched in February, has already been implemented in Brunei and parts of Xi’an, China. The Malaysian Highway Authority (LLM) is assessing its viability for nationwide implementation. A recent crash in Johor, detected by ARIDS 23 minutes before an official report was made, highlighted the system’s ability to enhance response efficiency. Authorities currently rely on CCTV monitoring and user reports for accident detection, which often causes delays.
The system’s mobile integration allows remote access, providing alerts through WhatsApp without human intervention. It also monitors traffic congestion and vehicle breakdowns, offering insights into road safety improvements like sturdier guardrails. Analysts believe this AI-powered solution could complement existing monitoring systems, such as the Traffic Monitoring System (TMS) and CCTVs, and boost predictive capabilities.
Broader adoption faces legal and operational hurdles. Concessionaires cannot currently enforce safety inspections on heavy vehicles without regulatory approval. However, integrating ARIDS with technologies like Weigh-In-Motion systems could streamline enforcement and reduce risks from overloaded or unsafe vehicles.
