City-scale traffic estimation from a roving sensor network


== Abstract ==

Traffic congestion, volumes, origins, destinations, routes, and other road-network performance metrics are typically collected through survey data or via static sensors such as traffic cameras and loop detectors. This information is often out-of-date, difficult to collect and aggregate, difficult to analyze and quantify, or all of the above. In this paper we conduct a case study that demonstrates that it is possible to accurately infer traffic volume through data collected from a roving sensor network of taxi probes that log their locations and speeds at regular intervals. Our model and inference procedures can be used to analyze traffic patterns and conditions from historical data, as well as to infer current patterns and conditions from data collected in real-time. As such, our techniques provide a powerful new sensor network approach for traffic visualization, analysis, and urban planning.

National Science Foundation (U.S.) (Grant CPS-0931550)

National Science Foundation (U.S.) (Grant 0735953)

United States. Office of Naval Research (Grant N00014-09-1-105)

United States. Office of Naval Research (Grant N00014-09-1-1031)

Document type: Conference object

== Full document ==
<pdf>Media:Draft_Content_715220423-beopen1899-5313-document.pdf</pdf>


== Original document ==

The different versions of the original document can be found in:

* [https://dspace.mit.edu/bitstream/1721.1/90617/1/Rus_City-scale%20traffic.pdf https://dspace.mit.edu/bitstream/1721.1/90617/1/Rus_City-scale%20traffic.pdf] under the license https://creativecommons.org/licenses/by-nc-sa

* [http://hdl.handle.net/1721.1/90617 http://hdl.handle.net/1721.1/90617],
: [https://orcid.org/0000-0001-5473-3566 https://orcid.org/0000-0001-5473-3566] under the license cc-by-nc-sa

* [https://dspace.mit.edu/handle/1721.1/90617 https://dspace.mit.edu/handle/1721.1/90617],
: [https://core.ac.uk/display/78055879 https://core.ac.uk/display/78055879],
: [https://dblp.uni-trier.de/db/conf/sensys/sensys2012.html#AslamLPR12 https://dblp.uni-trier.de/db/conf/sensys/sensys2012.html#AslamLPR12],
: [https://dl.acm.org/citation.cfm?id=2426671 https://dl.acm.org/citation.cfm?id=2426671],
: [https://doi.org/10.1145/2426656.2426671 https://doi.org/10.1145/2426656.2426671],
: [https://academic.microsoft.com/#/detail/2050134713 https://academic.microsoft.com/#/detail/2050134713] under the license http://creativecommons.org/licenses/by-nc-sa/4.0/

* [http://dl.acm.org/ft_gateway.cfm?id=2426671&amp;ftid=1332975&amp;dwn=1 http://dl.acm.org/ft_gateway.cfm?id=2426671&amp;ftid=1332975&amp;dwn=1],
: [http://dx.doi.org/10.1145/2426656.2426671 http://dx.doi.org/10.1145/2426656.2426671]