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Pavement Management Systems: Integration of Transportation Modeling, Land Use, Economy and Indicators of Development

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Pavement Management Systems: Integration of Transportation Modeling, Land Use, Economy and Indicators of Development

Amin, Md Shohel Reza (2015) Pavement Management Systems: Integration of Transportation Modeling, Land Use, Economy and Indicators of Development. PhD thesis, Concordia University.

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Abstract

The physical condition of road infrastructure in Canada is not good and roads are in critically condition in many regions. Canadian transportation agencies still require a comprehensive pavement management system (PMS) to guide and recommend the best practices for their appropriate application and communication. The general objective of this research is to extend PMS by incorporating dynamic states of land use, regional economics, travel modeling, and socio-economic development criteria. The specific objectives at regional scale is to integrate regional economy, transport modeling and community development criteria to simulate freight-traffic distribution between Atlantic Provinces of Canada to improve pavement-deterioration modeling and overall province-wide PMS. The specific objective at urban scale is to develop PMS for the road network of Montreal city incorporating simulated traffic and measurement errors free pavement performance curves. Comparison of current practices and proposed PMS based on simulated truck traffic reveals that incorporation of simulated truck traffic into PMS resulted in a more accurate estimation of required levels of funding for maintenance and rehabilitation (M&R). Socio-economic factors of the communities of Atlantic Provinces of Canada are integrated with regional economy and transportation modeling to support multi-criteria based PMS considering that policy makers are not only guided by the engineering characteristics but also by socio-economic benefits of the communities to allocate M&R budget. With and without scenarios of community development criteria into PMS have different implications on M&R budgets. The Backpropagation Neural Network (BPN) method with Generalized Delta Rule (GDR) learning algorithm is applied to develop pavement performance curves for Montreal road network reducing the measurement errors. Finally, a linear programming of PMS is developed for Montreal city incorporating the simulated traffic and pavement performance curves developed by BPN networks. Lifecycle optimization of PMS estimates that CAD 150 million is the minimum annual budget to achieve most of arterial and local roads are at least in good condition (PCI>70) in Montreal city. This research will provide the transportation agencies with an improved decision-making framework capable of delivering a more balanced M&R budget for the achievement of global objectives, such as cost, condition, service, accessibility, and community benefits.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (PhD)
Authors:Amin, Md Shohel Reza
Institution:Concordia University
Degree Name:Ph. D.
Program:Civil Engineering
Date:21 October 2015
Thesis Supervisor(s):Amador, Luis
ID Code:980669
Deposited By: MD SHOHEL REZA AMIN
Deposited On:16 Jun 2016 15:16
Last Modified:18 Jan 2018 17:51
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