01090262

Component

In many cases agencies that are embarking on implementing transportation asset management systems are faced with the challenge of lack of good time-series data for performance modeling. This paper presents one approach towards the formulation of performance prediction models that are required to support trade-off and optimization analyzes in a comprehensive transportation asset management system. The paper demonstrates that starting performance models can be formulated based on as little as two years’ network-level data on condition and traffic, for example. The paper builds a locally calibrated pavement condition index from the available falling weight deflectometer and pavement roughness (IRI) data, and subsequently uses it for network-level modeling. Optimal operational windows for preservation and rehabilitation activities can also derived from the condition data. The case study is based on Costa Rica national road network of more than 4000 km of paved roads. Further, the paper applies advanced analytical software capable of both simulating the agency’s current works programming practice and conducting comprehensive optimization. Several investment scenarios were tested to investigate the sustainability of the network asset value over time. The results demonstrate that the worst-first ranking approach leads to loss of network-level asset value (deterioration of asset conditions) while full optimization of preservation/rehab decisions at the same budget level, would result in improved asset conditions.

01084478

08-1616

English

17p

2008

Transportation Research Board 87th Annual Meeting

DVD

Figures (7) ; References (13) ; Tables (2)

Asset management; Pavement management systems; Pavement performance; Roughness; Time series

International Roughness Index

Performance modeling (pavements)

Costa Rica

Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways

Transportation Research Board Annual Meeting 2008 Paper #08-1616

TRIS, TRB

Jan 29 2008 3:57PM