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Real-Time Traffic Monitoring using Wireless Beacons with the Cell Transmission Model

Libman, Lavy; Bastani, Saeed LU and Waller, S. Travis (2014) IEEE 17th International Conference on Intelligent Transportation Systems (ITSC) In 2014 Ieee 17th International Conference on Intelligent Transportation Systems (Itsc) p.1079-1084
Abstract
One of the exciting emerging uses of DSRC/WAVE technology is the ability to monitor real-time road traffic conditions with high resolution, using beacons transmitted by individual vehicles, and make informed traffic control decisions such as traffic light timing or route advice. However, previous studies have shown that achieving a high level of accuracy in traffic density estimation requires very frequent beacon transmissions as well as a high adoption rate of the technology, which raises a scalability problem in dense urban settings and effectively requires a dedicated radio transceiver, precluding the wireless channel from being used for any other purpose at the same time. In this paper, we propose an approach that allows the wireless... (More)
One of the exciting emerging uses of DSRC/WAVE technology is the ability to monitor real-time road traffic conditions with high resolution, using beacons transmitted by individual vehicles, and make informed traffic control decisions such as traffic light timing or route advice. However, previous studies have shown that achieving a high level of accuracy in traffic density estimation requires very frequent beacon transmissions as well as a high adoption rate of the technology, which raises a scalability problem in dense urban settings and effectively requires a dedicated radio transceiver, precluding the wireless channel from being used for any other purpose at the same time. In this paper, we propose an approach that allows the wireless channel load due to beacon transmissions to be significantly reduced while retaining very low traffic estimation error levels, by using tools from traditional traffic theory (such as the Cell Transmission Model, CTM) to analyze position and speed signals from infrequent wireless beacons and predict the dynamics of the traffic behavior in between. Our approach is evaluated in a typical urban scenario consisting of a signalized intersection of multiple-lane roads, leading to new insights about how the value of the information in vehicles' beacons depends strongly on their location with respect to the intersection. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2014 Ieee 17th International Conference on Intelligent Transportation Systems (Itsc)
pages
1079 - 1084
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)
external identifiers
  • WOS:000357868701025
  • Scopus:84937126223
DOI
10.1109/ITSC.2014.6957831
language
English
LU publication?
yes
id
a6c7ba5f-8ba7-4b97-b625-afbcef733e8d (old id 7779659)
date added to LUP
2015-09-07 13:01:05
date last changed
2016-10-13 04:42:15
@misc{a6c7ba5f-8ba7-4b97-b625-afbcef733e8d,
  abstract     = {One of the exciting emerging uses of DSRC/WAVE technology is the ability to monitor real-time road traffic conditions with high resolution, using beacons transmitted by individual vehicles, and make informed traffic control decisions such as traffic light timing or route advice. However, previous studies have shown that achieving a high level of accuracy in traffic density estimation requires very frequent beacon transmissions as well as a high adoption rate of the technology, which raises a scalability problem in dense urban settings and effectively requires a dedicated radio transceiver, precluding the wireless channel from being used for any other purpose at the same time. In this paper, we propose an approach that allows the wireless channel load due to beacon transmissions to be significantly reduced while retaining very low traffic estimation error levels, by using tools from traditional traffic theory (such as the Cell Transmission Model, CTM) to analyze position and speed signals from infrequent wireless beacons and predict the dynamics of the traffic behavior in between. Our approach is evaluated in a typical urban scenario consisting of a signalized intersection of multiple-lane roads, leading to new insights about how the value of the information in vehicles' beacons depends strongly on their location with respect to the intersection.},
  author       = {Libman, Lavy and Bastani, Saeed and Waller, S. Travis},
  language     = {eng},
  pages        = {1079--1084},
  publisher    = {ARRAY(0x7618ab8)},
  series       = {2014 Ieee 17th International Conference on Intelligent Transportation Systems (Itsc)},
  title        = {Real-Time Traffic Monitoring using Wireless Beacons with the Cell Transmission Model},
  url          = {http://dx.doi.org/10.1109/ITSC.2014.6957831},
  year         = {2014},
}