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Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of the problem. An approach being experimented by some terminals to reduce truck queuing at the terminal is to provide live views of their gates via webcams. An assumption made by the terminals in this method is that truck dispatchers and drivers will make rational decisions regarding their departure times such that there will be less fluctuations in truck arrivals at the terminal based on the live information. However, it is clear that if dispatchers send trucks to the terminal whenever the truck queues are short and not send trucks when the truck queues are long, it could lead to a perpetual whip lash effect. This study explores the predictive strategies that need to be made by the various dispatchers to achieve the desired effects (i.e. steady arrival of trucks and hence less queuing at the seaport terminal gates). This problem is studied with the use of an agent-based simulation model and the solution to the well known El Farol Bar problem. Results demonstrate that truck depots can manage (without any collaboration with one another) to minimize congestion at seaport terminal gates by using the provided real-time gate congestion information and some simple logics for estimating the expected truck wait time. 相似文献
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Introduction The scarcity of available radio spectrum limits theextension of the modern wireless communication. Oneapproach to alleviate this limitation is the dynamicspectrum allocation (DSA) at network level, which isable to adapt to the spatial and temporal variation intraffic load[1]. The concept of DSA was first presentedin the DARPA (Defense Advanced Research ProjectsAgency) XG Program[2], with the aim to increase thespectral efficiency by spectrum sharing among radios.Due to the… 相似文献
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