Also discussed here: Understanding Road Usage Patterns in Urban Areas (6 page pdf, Pu Wang, Timothy Hunter, Alexandre M. Bayen, Katja Schechtner & Marta C. Gonzalez, Scientific Reports, Nature, Dec. 20, 2012)
And here: Phone data helps pinpoint source of traffic congestion (On Balance, Dept. Civil and Environmental Engineering, Massachusetts Institute of Technology, Jan. 2013)
And here: http://www.youtube.com/watch?v=9YDqVBUO3Ps (48 sec You-Tube, Marta Gonzalez, Dec. 8, 2013)
Today we review research from MIT aimed at diagnosing the dynamics of traffic congestion using mobile phone records and population and origin-destination statistics to identify key congested road segments that lead to major congestion across major cities such as San Francisco and Boston. These congested areas rapidly lead to high levels of pollution that affect the entire urban area which puts both drivers and others such as cyclists who use the roads at risk to their health. Better design of the road network and method to reduce traffic peaks such as congestion pricing are offered as solutions.
Key Quotes:
“In 2007 alone, congestion forced Americans living in urban areas to travel 4.2 billion hours more, purchase an additional 2.8 billion gallons of fuel, at a total cost of $87.2 billion”
“the major usage of each road segment can be traced to its own – surprisingly few - driver sources…in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network”
“For a road segment, its level of congestion can be measured by the additional travel time te, defined as the difference between the actual travel time ta and the free flow travel time tf. The drivers who travel through congested roads experience a significant amount of te.”
“the major traffic flows in congested roads are generated by very few driver sources, which enables us to target the small number of driver sources affected by this significantly larger Te.”
“Congestion hot spots can become air quality hot spots within a short amount of time…If you as an individual are stuck in a car and you’re driving in traffic, you’re spending more time being exposed to potentially higher levels of air pollution. The same thing goes for bikers and pedestrians along that roadway.”
“Ultrafine particles and combusted pollutants from gasoline and diesel fuel are the road’s most common threats to air quality... In urban areas, such as Boston, motor vehicles contribute a large percentage of both.”
“the team could model their algorithm, which aims to prevent inconveniences and environmental stressors triggered by the onset of traffic, based on human destination sites.These sites within the traffic flow prediction formula were then categorized into “absorbers” and “emitters,” with absorbers marking daily locations that draw in large numbers of people — like BU, for example — and emitters marking the places where people live”
