Macroscopic Optimum System for Management of Pavement Rehabilitation

Abaza, Khaled A.; Ashur, Suleiman; Abu-Eisheh, Sameer; Rabay'a, A

doi:10.1061/(asce)0733-947x(2001)127:6(493)

Cited by 31 publications

(10 citation statements)

References 3 publications

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“…American Association of State Highway and Transportation Officials (AASHTO) developed the present serviceability index (PSI) for the flexible pavement (AASHTO 1985). The PSI and 18 kip ESALs are the main factors of pavement performance along with other factors such as materials properties, drainage and environmental conditions, and performance reliability (Abaza et al 2001;Amin 2015). Abaza et al (2001) developed pavement performance curve plotting PSI versus time or ESALs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The PSI and 18 kip ESALs are the main factors of pavement performance along with other factors such as materials properties, drainage and environmental conditions, and performance reliability (Abaza et al 2001;Amin 2015). Abaza et al (2001) developed pavement performance curve plotting PSI versus time or ESALs. Several studies also D r a f t estimated PSI and pavement condition index (PCI) based on the AASHO Road Test (Santos and Ferreira 2013; Lee et al 1993;Li et al 1997).…”

Section: Literature Reviewmentioning

confidence: 99%

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Travel demand modeling to simulate traffic loads for pavement deterioration curves: dealing with aggregate data at urban and regional scales

Amin¹,

Amador-Jiménez²

2015

Can. J. Civ. Eng.

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https://mc06.manuscriptcentral.com/cjce-pubs Canadian Journal of Civil Engineering D r a f t 2Travel demand modeling to simulate traffic loads for pavement deterioration curves: dealing with aggregate data at urban and regional scales Abstract: Traditional pavement management system uses historical data on traffic volume or traffic growth rate to develop the pavement deterioration curves. This study simulates the traffic loads on regional and urban road networks to estimate the pavement deterioration curves applying travel demand models at urban and regional scales during the period of 2013-2062. Highways 1, 2, 7, 15, 16, 102 and 104 connecting the Atlantic Provinces of Canada are considered as the case study at regional scale. Arterial and local roads of both rigid and flexible pavement types in Montreal city are considered as the case study at urban scale. The TRANUS integrates spatial input-output and transportation models to simulate interprovincial freight movement on the regional road network. Urban transportation planning system (UTPS) simulates the urban traffic on the road network of Montreal city. The accumulated traffic loads (ESALs) are calculated based on the predicted AADT and locally observed truck distributions combined with truck factors. Roughness progression on regional highways and urban roads is estimated by applying regression model of international roughness index (IRI). The IRI will be 35.71, 43.33, 31.62 and 30.67 for flexible-arterial, rigid-arterial, flexible-local and rigid-local roads during the period of 2013-2062, respectively. Comparative evaluation of with and without simulated traffic reveals that the impact of simulated traffic is highest on the pavement structure of highway 2 and 1 at regional level and rigid-arterial and flexible roads of Montreal city. This study improves the traditional method of estimating pavement deterioration by incorporating the simulated traffic and traffic loads into the pavement performance function. Page 2 of 45 https://mc06.manuscriptcentral.com/cjce-pubs Canadian Journal of Civil Engineering D r a f t 3

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Travel demand modeling to simulate traffic loads for pavement deterioration curves: dealing with aggregate data at urban and regional scales

Amin¹,

Amador-Jiménez²

2015

Can. J. Civ. Eng.

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“…The data required for a MS are produced by monitoring and inventory activities, while modelling provides the tools for planning, trade-off analysis, ranking, and optimisation (Li et al, 1997). For PMS, pavement performance models adopt either deterministic (Abaza, 2004;Abaza et al, 2001;Wong et al, 2003) or probabilistic Golabi et al, 1982;Li et al, 1997) AM, the requirements for an AM system and the guidelines for the application of ISO 55001. The ISO is a high-level strategic guide that introduces systems thinking and AM organisational precursors in a business-oriented manifesto that aims to standardise AM.…”

Section: Defining Maintenance and Maintenance Strategiesmentioning

confidence: 99%

Highway filter drains: precursors for maintenance management

Stylianides¹,

Frost²,

Fleming³

et al. 2015

Infrastructure Asset Management

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This paper conceptualises and presents a number of asset management building blocks required to establish holistic management for highway filter drains in the UK roads network. This is accomplished by evaluating current maintenance and management thinking and by identifying how existing strategies are lacking and potentially unsustainable. A condition assessment regime is hence described, tied to a measure of filter drain level of service (drainability) and an asset-specific ageing/renewal model that adopts six discreet condition bands is proposed. For this model to hold true, the Markov process is assumed to represent cumulative damage in a network. Drawing from relevant asset management concepts, a decision support tool to inform and optimise managerial decisions in respect to maintenance planning and resources allocation is also described.

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“…In optimization models, the goal of the analysis can be the minimization of any combination between agency costs, user costs and residual value of pavements over a selected planning time-span subject to minimum quality level constraints (Abaza 2006;Abaza et al 2004;Ferreira et al 2002a;Ferreira et al 2002b;Ferreira et al 2009a;Golabi et al 1982;Madanat et al 2006;Nunoo and Mrawira 2004;Picado-Santos et al 2004) or the maximization of the whole network quality or performance subject to annual budget constraints (Abaza 2006;Abaza et al 2004;Abaza et al 2001;Ferreira et al 2009b;Nunoo and Mrawira 2004). In these models, pavement condition data are used as model inputs, pavement performance models are used to predict future quality of pavements and annual budgets and minimum quality levels are constraints that must be assured.…”

Section: Introductionmentioning

confidence: 99%

“…over a selected planning time-span subject to minimum quality level constraints (Golabi et al 1982, Ferreira et al 2002a, Ferreira et al 2002b, Picado-Santos et al 2004, Abaza et al 2004, Abaza 2006, Madanat et al 2006, Abaza 2007, Madanat et al 2006, Durango-Cohen and Tadepalli 2006, Ferreira et al 2009a, Jorge and Ferreira 2012, the maximization of the whole network quality or performance subject to annual budget constraints (Abaza et al 2001, Nunoo and Mrawira 2004, Abaza 2006, Abaza 2007, Yoo and Garcia-Diaz 2008, Ferreira et al 2009b, Li and Sinha 2009, Li 2009), or considering both at the same time , Wang et al 2003. In these models, pavement condition data are used as model inputs, pavement performance models are used to predict future quality of pavements and annual budgets and minimum quality levels are constraints that must be assured.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective decision-aid tool for pavement management

Meneses¹,

Ferreira²,

Collop³

2013

Proceedings of the Institution of Civil Engineers - Transport

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This paper presents the development and implementation of a multi-objective decision-aid tool tested with data from Oliveira do Hospital's pavement management system. The pavement management system includes the following components: a road network database; a quality evaluation tool; a cost model; a pavement performance model; and a decision-aid tool. Nowadays, the pavement management system decision-aid tool uses a deterministic section-linked optimisation model with the objective of minimising the total expected discounted costs over the planning time-span while keeping the road pavements within given quality standards. The multi-objective decision-aid tool uses a multi-objective deterministic section-linked optimisation model with three different possible goals: minimisation of agency costs (maintenance and rehabilitation costs); minimisation of user costs; and maximisation of the residual value of pavements. This new approach allows pavement management systems to become interactive decision-aid tools capable of providing road administrators with answers to ‘what-if' questions in short times.

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Macroscopic Optimum System for Management of Pavement Rehabilitation

Cited by 31 publications

References 3 publications

Travel demand modeling to simulate traffic loads for pavement deterioration curves: dealing with aggregate data at urban and regional scales

Travel demand modeling to simulate traffic loads for pavement deterioration curves: dealing with aggregate data at urban and regional scales

Highway filter drains: precursors for maintenance management

Multi-objective decision-aid tool for pavement management

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