Cluster use for logistics operations and wireless vehicular networks in urban port areas : Urban freight. / Coronado Mondragon, Adrian E; Coronado Mondragon, Etienne S.; Coronado Mondragon, Christian E.

2011. Paper presented at 8th Intelligent Transport System European Congress, Lyon, France.

Research output: Contribution to conferencePaperpeer-review

Published

Abstract

Around the world important sea port facilities running complex multimodal operations happen to be in close proximity to major urban areas. This kind of sea port facilities face several challenges such as increase in competition with other regions, the reduction of costs, space constraints limiting expansion, the optimization of logistics operations and the reduction of any possible negative impact on the environment among others. The need to create logistics clusters that can be used to address the challenges facing port facilities necessarily require the support of Intelligent Transport Systems (ITS) and more specifically next generation wireless vehicle network technology such as Dedicated Short Range Communication (DSRC) @ 5.9 GHz given the dependence of multimodal operations on road haulage vehicles. The work presented here is a feasibility study that investigates the formation of logistics clusters comprising companies with interests in the port and which can be supported by the deployment of DSRC-based wireless networks which enhance track and trace, security, information sharing and visibility. Logistics operations analysis mapping and network modelling and simulation are tools considered to test the feasibility of the logistics cluster approach for meeting port terminal operators’ and urban requirements.
Original languageEnglish
Number of pages9
Publication statusPublished - Jun 2011
Event8th Intelligent Transport System European Congress - Lyon, France
Duration: 6 Jun 20119 Jun 2011

Conference

Conference8th Intelligent Transport System European Congress
CountryFrance
CityLyon
Period6/06/119/06/11
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 2252648