Estimating Construction Duration for Public Roads During the Preplanning Phase

Abstract

Estimates of the construction time are of key importance in the early phases of the projectthey serve as a basis for the decision whether to commence with planning or not, and are used as input for budgets and programmes. Usually, such estimates base on experience with similar projects completed in the past. This experience may be recorded in the form of mathematical models that relate project characteristics to construction time. The aim of the research was, basing on real-life cases, to develop a model of public road building projects duration. The research comprised collection of input for the analyses, preselection of project features correlated with duration, and construction of three models: a simple statistical regression, a multifactor regression and a regression tree. The models were then compared to each other and to the models presented in the literature with respect to their predictive ability. With the assumed set of potential predictors of construction duration, the regression models were found statistically correct, though not precise enough be used as decision-support tools.

Estimating approximate construction duration of CFRD in the planning stage

“…Lee et al (2015) of normal project duration for a water resource project using linear regression by analyzing the correlation among the project scale, cost and actual duration. Czarnigowska et al (2014) developed a model estimating duration of public road construction projects based on real-life cases and presented three models: a simple statistical regression, a multifactor regression and a regression tree. Seo (2014) presented an approximate construction period prediction model for office building in the planning stage using multiple linear regression.…”

Method for Base Estimation of Construction Time for Linear Projects in Front-end Project Phases

“…For European Union (EU)-funded projects, not meeting construction deadline invites very high penalties, up to 25% of the contract value (Ministarstvo regionalnoga razvoja i fondova Europske unije [MRRFEU], 2019), and still, reports of time overruns are frequent. The estimation of project time and cost for large construction projects is a characteristically complex exercise (Singh, 2010;Czarnigowska and Sobotka, 2014).…”

“…There are only few models of time estimation, and they are mostly based on project cost (Bromilow et al, 1980;Chan and Kumaraswamy, 1995;Car-Pusic and Radujkovic, 2006;Žujo et al, 2017). Most of these models are used to record what is likely to be achievable (i.e., duration) based on experience with past projects (Czarnigowska and Sobotka, 2014). The existing time predictive models are based on regression between cost and other project variables and duration (Bromilow et al, 1980;Kaka andPrice, 1991 Chan andKumaraswamy, 1995;Chan, 2001;Petruseva et al, 2019).…”

“…Hofmann (2007) provided an MLR model based on six parameters (i.e., project delivery method, work type, and so on). Czarnigowska and Sobotka (2014) used 25 parameters in their MLR, and Chan and Kumaraswamy (1999) also used >10 parameters to provide best-fit estimation. In addition to simple linear regression and MLR, there are other methods for time estimations based on construction project parameters, i.e., artificial neural network (ANN) model (Bhokha and Ogunlana, 1999), neurofuzzy model for time and cost estimation (Boussabaine, 2001) using both fuzzy concept and neural networks, time prediction model based on locally linear neurofuzzy (LLNF) model, being trained by a locally linear model tree (Vahdani et al, 2016.).…”

“…Žujo et al (2017) developed five hybrid models, and the most accurate one was the BTC-general regression neural network (GRNN) model, which uses the BTC model as a process-based model and the GRNN as a data-driven model. Time-cost regression parametric models have some advantage over other (alternative) models, such as "black box" expert systems or neural networks, because regression models are expressed as equations, and to use them, one does not need to dispose of the whole database or software (Czarnigowska and Sobotka, 2014). On the contrary, one of the significant limitations of the "time-cost" model is also that it can be applied only in the area or country of its origin because of specific economic characteristics, which are reflected on the value of model constants (Žujo et al, 2017).…”