REAL-TIME ANALYTICS FOR INTELLIGENT TRANSPORTATION

摘要

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