Latest revision as of 16:26, 21 January 2021

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.

Original document

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

• 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://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,

https://link.springer.com/chapter/10.1007%2F978-3-642-25044-6_16,

https://www.scipedia.com/public/Smith_Mailler_2011a,

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://academic.microsoft.com/#/detail/2151241884