NYUAD researchers study traffic management in 25 cities
Review aims to improve understanding of traffic patterns, relieve congestion
Abu Dhabi: Researchers at New York University Abu Dhabi (NYUAD) have created a comprehensive review of fundamental traffic models in a bid to improve understanding of traffic management systems around the globe. The researchers reviewed traffic data pertaining to 2.3 billion vehicle observations in 25 cities.
The study, which also aims to promote the creation of improved traffic modelling and relieve congestion, is a comprehensive review of 50 models of traffic flow developed over the past 85 years. It has been developed by Daniel Bramich, research scientist, and Dr Monica Menendez, professor of Civil and Urban Engineering at NYUAD, and director of the CITIES Research Centre. The project, titled ‘Fitting Empirical Fundamental Diagrams of Road Traffic: A Comprehensive Review and Comparison of Models Using an Extensive Data Set’, has been published in the ‘IEEE Transactions on Intelligent Transportation Systems’ journal.
Road type and level of congestion
The researchers found that a model with minimal assumptions outperformed the other traffic-flow models, regardless of variables such as the road type and the level of congestion. The winning model is non-parametric, meaning that its number of free parameters can vary as necessary, but without overfitting the data. This represents a departure from traditional parametric models (with fixed numbers of parameters), and opens the door to new approaches to understanding the data with the ultimate goal of improving traffic management and relieving congestion.
Larger data set
With unprecedented access to a large and well-controlled sample of traffic data from cities around the world, the review avoids the shortcomings of previous reviews, which did not have access to a data set of this scale, and did not take all of the top models for traffic flow into account. Specifically, the amount of data this study had access to is approximately 100-1,000 times larger than any of the data sets from previous studies, and the number of models studied is approximately ten times larger than previous studies.
‘Important resource for traffic engineers’
“We hope that our review will become the ‘one-stop shop’ for researchers who seek to understand the development of present-day traffic models. We believe this will serve as an important resource for traffic engineers as they design traffic infrastructure, including traffic light timing and speed limits, for cities around the world,” the researchers said.