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http://hdl.handle.net/1942/24256
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DC Field | Value | Language |
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dc.contributor.author | Syed, Wasim Sohail Hashmi | - |
dc.contributor.author | Jabbar, Ambreen | - |
dc.contributor.author | Shaikh, Maqbool Uddin | - |
dc.contributor.author | YASAR, Ansar | - |
dc.contributor.author | JANSSENS, Davy | - |
dc.contributor.author | Galland, Stephane | - |
dc.date.accessioned | 2017-08-17T14:00:14Z | - |
dc.date.available | 2017-08-17T14:00:14Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 8(3), p. 395-404 | - |
dc.identifier.issn | 1868-5137 | - |
dc.identifier.uri | http://hdl.handle.net/1942/24256 | - |
dc.description.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. | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER HEIDELBERG | - |
dc.rights | © Springer-Verlag Berlin Heidelberg 2017 | - |
dc.subject.other | evolutionary algorithm; neural network; nodes; routes; traffic flow; telemetry | - |
dc.subject.other | Evolutionary algorithm; Neural network; Nodes; Routes; Traffic flow; Telemetry | - |
dc.title | A new traffic route analyzer for commuter's guidance in developing countries: application study in Islamabad, Pakistan | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 404 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 395 | - |
dc.identifier.volume | 8 | - |
local.format.pages | 10 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.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. | - |
local.publisher.place | HEIDELBERG | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1007/s12652-017-0453-0 | - |
dc.identifier.isi | 000402072700008 | - |
item.fulltext | With Fulltext | - |
item.validation | ecoom 2018 | - |
item.accessRights | Restricted Access | - |
item.fullcitation | Syed, Wasim Sohail Hashmi; Jabbar, Ambreen; Shaikh, Maqbool Uddin; YASAR, Ansar; JANSSENS, Davy & Galland, Stephane (2017) A new traffic route analyzer for commuter's guidance in developing countries: application study in Islamabad, Pakistan. In: JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 8(3), p. 395-404. | - |
item.contributor | Syed, Wasim Sohail Hashmi | - |
item.contributor | Jabbar, Ambreen | - |
item.contributor | Shaikh, Maqbool Uddin | - |
item.contributor | YASAR, Ansar | - |
item.contributor | JANSSENS, Davy | - |
item.contributor | Galland, Stephane | - |
crisitem.journal.issn | 1868-5137 | - |
crisitem.journal.eissn | 1868-5145 | - |
Appears in Collections: | Research publications |
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8888.pdf Restricted Access | Published version | 1.79 MB | Adobe PDF | View/Open Request a copy |
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