Answers are grounded in this paper and cite their sources.
This study overviews the scientific and practical results obtained within the advanced traffic monitoring (ATMO) project (www.atmo.tudelft.nl) from its inception in 2004 until its final year 2009. ATMO is a 2.5 million Euros research project in which universities, public bodies and the industry collaboratively addressed the question how to translate large amounts of raw traffic data from all sorts of sensors and systems into useable and meaningful information for traffic information, and sustainable traffic management and control. In the context of sustainability, traffic monitoring entails not just observing or estimating ‘classic’ traffic data and information, such as average speed, volume or delay and travel time, but also more diffuse concepts such as travel time reliability, traffic safety and environmentally related quantities. In five PhD tracks many scientific contributions were made such as new hybrid methods and models for traffic and travel time prediction, online traffic simulation models and new travel time reliability measures, to name a few. ATMO also demonstrated that bridging the gap between science and practice in the field of traffic monitoring requires entrepreneurial academics, sharing of data and results and tailor-made post-academic courses and education.
No takes yet. Share an insight, caveat, or question.
Lint et al. (2010) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: