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Báo cáo hóa học: " Research Article Traffic Data Collection for Floating Car Data Enhancement in V2I Networks"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: IResearch Article Traffic Data Collection for Floating Car Data Enhancement in V2I Networks | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 719294 13 pages doi 10.1155 2010 719294 Research Article Traffic Data Collection for Floating Car Data Enhancement in V2I Networks D. F. Llorca M. A. Sotelo S. Sanchez M. Ocana J. M. Rodriguez-Ascariz and M. A. Garcia-Garrido Department of Electronics University of Alcala Ctra. N-II Km. 33 Alcala de Henares C.P. 28871 Madrid Spain Correspondence should be addressed to D. F. Llorca Uorca@depeca.uah.es Received 19 November 2009 Accepted 5 July 2010 Academic Editor Shahrokh Valaee Copyright 2010 D. F. Llorca et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. This paper presents a complete vision-based vehicle detection system for floating car data FCD enhancement in the context of vehicular ad hoc networks VANETs . Three cameras side- forward- and rear-looking cameras are installed onboard a vehicle in a fleet of public buses. Thus a more representative local description of the traffic conditions extended FCD can be obtained. Specifically the vision modules detect the number of vehicles contained in the local area of the host vehicle traffic load and their relative velocities. Absolute velocities average road speed and global positioning are obtained after combining the outputs provided by the vision modules with the data supplied by the CAN Bus and the GPS sensor. This information is transmitted by means of a GPRS UMTS data connection to a central unit which merges the extended FCD in order to maintain an updated map of the traffic conditions traffic load and average road speed . The presented experiments are promising in terms of detection performance and computational costs. However significant effort is further necessary before deploying a system for large-scale real applications. 1. Introduction .