Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24256
Title: A new traffic route analyzer for commuter's guidance in developing countries: application study in Islamabad, Pakistan
Authors: Syed, Wasim Sohail Hashmi
Jabbar, Ambreen
Shaikh, Maqbool Uddin
YASAR, Ansar 
JANSSENS, Davy 
Galland, Stephane
Issue Date: 2017
Publisher: SPRINGER HEIDELBERG
Source: JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 8(3), p. 395-404
Abstract: Growth of population in the capital city of Pakistan-Islamabad-is too high. This growth rate has caused a negative impact on the smooth flow of traffic system. The aim of this paper is to provide a solution to facilitate the car-based commuters to pick the route with minimal bottlenecks and to minimize the distance to reach the destination. The proposed solution is to manage and control the traffic system in the city of Islamabad. The current traffic data collection system in Islamabad and other urban areas does not provide timely and reliable data that can be useful to the Regional Transportation Authority for planning activities. To overcome this problem, our approach is based on collecting the missing data using a custom-built mobile app. Our system analyses and manipulates the collected information based on artificial neural network scheme that can indicate the bottlenecks for each route and predicts the shortest route based on the user's severity levels. To validate our proposed approach, we tested six different randomly selected routes in Islamabad with different bottlenecks.
Notes: [Syed, Wasim Sohail Hashmi; Jabbar, Ambreen] HEC, Islamabad, Pakistan. [Shaikh, Maqbool Uddin] COMSATS Inst Informat Technol, Islamabad, Pakistan. [Yasar, Ansar-Ul-Haque; Janssens, Davy] Hasselt Univ, Transportat Res Inst, Hasselt, Belgium. [Galland, Stephane] Univ Technol Belfort Montbeliard, Belfort, France.
Keywords: evolutionary algorithm; neural network; nodes; routes; traffic flow; telemetry;Evolutionary algorithm; Neural network; Nodes; Routes; Traffic flow; Telemetry
Document URI: http://hdl.handle.net/1942/24256
ISSN: 1868-5137
e-ISSN: 1868-5145
DOI: 10.1007/s12652-017-0453-0
ISI #: 000402072700008
Rights: © Springer-Verlag Berlin Heidelberg 2017
Category: A1
Type: Journal Contribution
Validations: ecoom 2018
Appears in Collections:Research publications

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