Gold Rush for Transportation Data

Massive amounts of traffic- related information are being generated every second by road operators and users alike. The term “big data” derives from the sheer amount and complexity of available raw data, and its potential value is emerging throughout the intelligent transportation system community. Data mining, a process that identifies useful patterns in the data is at the forefront of capturing this value. It is also about gaining efficiencies in planning by pointing to patterns of recurring congestion on a level that may not have been discovered otherwise. From that point, predictive analytics can support improved, proactive traffic operations. But for data mining to be useful, highway authorities must tap into new and unconventional data sources such as vehicle probe and telemetry data, as well as other ‘user generated’ data needs to be collected and mined. The article discusses data warehouses, where standardized raw data amalgamated from multiple information sources, must be used to resolve any semantic discrepancies in data collected to preserve, annotate, and archive historical data.