Simplified user delay cost model for pavement and bridge life cycle analysis.

This paper was presented at the session titled `Assessment of user costs in pavement infrastructure life-cycle costing'. In maintenance or rehabilitation of roadways, the road user cost can contribute significantly to the total life cycle cost. Road user costs have two major components: a) vehicle operating costs (VOC), which vary with surface roughness, vehicle type and other factors, and b) user delay costs, which vary with the length of work zone, duration of delay time, traffic volume, traffic handling strategy during rehabilitation, etc. This paper focuses of the delay cost component. A simplified model for estimating delay costs is presented. While a number of models have been developed for calculating user costs they require a large amount of input data. Moreover, they are cumbersome and time consuming to use with life cycle cost analysis (LCCA) spreadsheets. There are many situations where an approximate estimate of user delay costs is satisfactory. This estimate can be based on simplifying a more complex model. The complex model used herein was developed for the Ontario Pavement Analysis of Costs (OPAC) 2000 design methodology. This program is a comprehensive design package which includes life cycle cost calculations for different design alternatives including vehicle operating costs, user delay costs, etc. User delay occurs both during traffic slowing in approaching and/or proceeding through the work zone as well as due to queuing. The simplified model described in the paper is based on a large number of runs for OPAC 2000 for a representative set of conditions and various traffic handling strategies. These strategies range from a two-lane undivided facility with a flag-person to a multi-lane divided facility with different lane closure alternatives. The result is a series of simple look-up tables for each traffic handling strategy. Clearly illustrated is the exponential increase in delay cost, which occurs when traffic volumes are high enough to cause queuing delay. Finally the paper presents life cycle analysis examples which illustrate the use of the simplified estimate of user delay costs. (A)