“Real-time Traffic Incident Detection and Monitoring Using Social Media.”
Social networks have become a valuable source of real-time information. Transport Management Centre (TMC) in Australian state of New South Wales has collaborated with Data61 to develop TrafficWatch, a system that leverages Twitter as a channel for transport network monitoring, incident and event management. This system utilises advanced web technologies and state-of-the-art machine learning (ML) algorithms. The live web interface is based on Data61 Subspace and 3D Cesium Bing map to provide a spatial and temporal display of tweets that are potentially related to transport issues. The crawled tweets are first filtered to show incidents in Australia, and then divided into different groups by online clustering and classification algorithms.
One of the issues identified was that only 3% of tweets contained geo-locations, making it difficult to interpret the locations of reported issues. TrafficWatch was able to geo-locate an additional 20% of tweets by analysing locations extracted from its text analysis module.
Findings from the use of TrafficWatch at TMC demonstrated that it has potential to report incidents earlier than other data sources, as well as identifying unreported incidents. The concept of monitoring social media also shows promise in improving TMC’s network monitoring capabilities to assess network impacts of incidents and events.
People: Fang Chen (technical contact), Hoang Nguyen, Chen Cai, Ronnie Taib, Paul Rivera, Kin-Hon Chan.