Real-Time Traffic Information Management using Stream Computing

With the widespread adoption of location tracking technologies like GPS, the domain of transportation information management has seen growing interest in the last few years. In this paper, we describe a stream processing infrastructure for processing large volumes of sensor data in real time to derive useful traffic and travel planning information. We have used this infrastructure to process floating car data for the city of Stockholm in real-time. Our findings show that there is a great need for real-time traffic information management because of the tremendous variability in traffic conditions in a city like Stockholm. Also, our stream processing infrastructure can help meet this need by supporting the development of applications that can process large volumes of GPS and other data on a distributed cluster of machines.

• Type: Journal
• Year: 2010
• Where: DEBU
• Authors: Alain Biem, Eric Bouillet, Hanhua Feng, Anand Ranganathan, Anton Riabov, Olivier Verscheure, Haris N. Koutsopoulos, Mahmood Rahmani, Baris Güç
• Keywords: DEBU 2010, Floating Car Data, Large Volumes, Travel Planning Information