Pavement management with dynamic traffic and artificial neural network: a case study of Montreal
This study improves the pavement management system by developing a linear programming optimization for the road network of the City of Montreal with simulated traffic for a period of 50 years and deals with the uncertainty of pavement performance modeling. Travel demand models are applied to simulat...
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| Published in | Canadian journal of civil engineering Vol. 43; no. 3; pp. 241 - 251 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Ottawa
NRC Research Press
01.03.2016
Canadian Science Publishing NRC Research Press |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0315-1468 1208-6029 1208-6029 |
| DOI | 10.1139/cjce-2015-0299 |
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| Summary: | This study improves the pavement management system by developing a linear programming optimization for the road network of the City of Montreal with simulated traffic for a period of 50 years and deals with the uncertainty of pavement performance modeling. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. A backpropagation neural network (BPN) with a generalized delta rule learning algorithm is applied to develop pavement performance models without uncertainties. Linear programming of life-cycle optimization is applied to develop maintenance and rehabilitation strategies to ensure the achievement of good levels of pavement condition subject to a given maintenance budget. The BPN network estimated that PCI values were predominantly determined by the differences in pavement condition index, AADT, and equivalent single axle loads. Dynamic linear programming optimization estimated that CAD$150 million is the minimum annual budget required to keep most of the arterial and local roads in good condition in Montreal. |
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| Bibliography: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0315-1468 1208-6029 1208-6029 |
| DOI: | 10.1139/cjce-2015-0299 |