REAL-TIME ANALYTICS FOR INTELLIGENT TRANSPORTATION

摘要

Managing congestion and improving personal mobility is an obvious concern for the transportation industry. Adoption of new technology is helping, for example, by providing more frequent and detailed data using cheaper GPS devices and networks of wireless sensors. However, with approximately 800 million vehicles on the world's roads today, estimated to increase to four billion vehicles by 2050, reducing congestion will require operational systems to process a vast volume of data, but also to automate responses to changing conditions in real-time.This paper presents the requirements for low latency intelligent transportation systems, and uses a case study to illustrate how these requirements can be addressed to deliver real-time analytics for Travel Time and congestion detection applications.