Smith Mailler 2011a - Revision history

Scipediacontent at 14:26, 21 January 2021

2021-01-21T14:26:19Z

Scipediacontent: Scipediacontent moved page Draft Content 809514098 to Smith Mailler 2011a

2020-10-14T14:15:39Z

Scipediacontent moved page Draft Content 809514098 to Smith Mailler 2011a

Scipediacontent: Created page with " == Abstract == Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of c..."

2020-10-14T14:15:36Z

Created page with " == Abstract == Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of c..."

New page

== Abstract ==

Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of congestion, can turn even the biggest highways into a parking lot. Several congestion mitigation strategies are being studied, many focusing on micro-simulation of traffic to determine how modifying road structures will affect the flow of traffic and the networking perspective of vehicle-to-vehicle communication. Vehicle routing on a network of roads and intersections can be modeled as a distributed constraint optimization problem and solved using a range of centralized to decentralized techniques. In this paper, we present a constraint optimization model of a traffic routing problem. We produce congestion data using a sinusoidal wave pattern and vary its amplitude (saturation) and frequency (vehicle waves through a given intersection). Through empirical evaluation, we show how a centralized and decentralized solution each react to unknown congestion information that occurs after the initial route planning period.

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_809514098-beopen969-1613-document.pdf</pdf>

== Original document ==

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

* [http://www.personal.utulsa.edu/%7Eroger-mailler/publications/prima2011.pdf http://www.personal.utulsa.edu/%7Eroger-mailler/publications/prima2011.pdf]

← Older revision		Revision as of 14:26, 21 January 2021
Line 3:		Line 3:

	Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of congestion, can turn even the biggest highways into a parking lot. Several congestion mitigation strategies are being studied, many focusing on micro-simulation of traffic to determine how modifying road structures will affect the flow of traffic and the networking perspective of vehicle-to-vehicle communication. Vehicle routing on a network of roads and intersections can be modeled as a distributed constraint optimization problem and solved using a range of centralized to decentralized techniques. In this paper, we present a constraint optimization model of a traffic routing problem. We produce congestion data using a sinusoidal wave pattern and vary its amplitude (saturation) and frequency (vehicle waves through a given intersection). Through empirical evaluation, we show how a centralized and decentralized solution each react to unknown congestion information that occurs after the initial route planning period.		Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of congestion, can turn even the biggest highways into a parking lot. Several congestion mitigation strategies are being studied, many focusing on micro-simulation of traffic to determine how modifying road structures will affect the flow of traffic and the networking perspective of vehicle-to-vehicle communication. Vehicle routing on a network of roads and intersections can be modeled as a distributed constraint optimization problem and solved using a range of centralized to decentralized techniques. In this paper, we present a constraint optimization model of a traffic routing problem. We produce congestion data using a sinusoidal wave pattern and vary its amplitude (saturation) and frequency (vehicle waves through a given intersection). Through empirical evaluation, we show how a centralized and decentralized solution each react to unknown congestion information that occurs after the initial route planning period.
−
−	~~Document type: Part of book or chapter of book~~
−
−	~~== Full document ==~~
−	~~<pdf>Media:Draft_Content_809514098-beopen969-1613-document.pdf</pdf>~~


Line 15:		Line 10:

	* [http://www.personal.utulsa.edu/%7Eroger-mailler/publications/prima2011.pdf http://www.personal.utulsa.edu/%7Eroger-mailler/publications/prima2011.pdf]		* [http://www.personal.utulsa.edu/%7Eroger-mailler/publications/prima2011.pdf http://www.personal.utulsa.edu/%7Eroger-mailler/publications/prima2011.pdf]
		+
		+	* [http://link.springer.com/content/pdf/10.1007/978-3-642-25044-6_16 http://link.springer.com/content/pdf/10.1007/978-3-642-25044-6_16],
		+	: [http://dx.doi.org/10.1007/978-3-642-25044-6_16 http://dx.doi.org/10.1007/978-3-642-25044-6_16] under the license http://www.springer.com/tdm
		+
		+	* [http://personal.utulsa.edu/~roger-mailler/publications/prima2011.pdf http://personal.utulsa.edu/~roger-mailler/publications/prima2011.pdf],
		+	: [https://link.springer.com/chapter/10.1007%2F978-3-642-25044-6_16 https://link.springer.com/chapter/10.1007%2F978-3-642-25044-6_16],
		+	: [https://www.scipedia.com/public/Smith_Mailler_2011a https://www.scipedia.com/public/Smith_Mailler_2011a],
		+	: [https://dblp.uni-trier.de/db/conf/prima/prima2011.html#SmithM11 https://dblp.uni-trier.de/db/conf/prima/prima2011.html#SmithM11],
		+	: [https://rd.springer.com/chapter/10.1007/978-3-642-25044-6_16 https://rd.springer.com/chapter/10.1007/978-3-642-25044-6_16],
		+	: [https://academic.microsoft.com/#/detail/2151241884 https://academic.microsoft.com/#/detail/2151241884]

← Older revision	Revision as of 14:15, 14 October 2020
(No difference)