Cost Estimation Methods for Transport Infrastructure: A Systematic Literature Review

Nowadays, large amount of money is invested on infrastructure projects within transport section. This attracts policy and decision makers a lot. Especially, project cost is one of the most discussed factors. This paper aims to investigate different types of cost estimation methods used in transport projects, identify their attributes that make them unique to specific infrastructure, and finally study their applications on transport infrastructure. In addition, the research looked to see if there is trend change on using cost estimation methods over time and checked the applications of methods in each transport infrastructure. The study used a systematic literature review (date cube creation, data filtering using primary and secondary search clusters, content analysis, etc.) to include as many estimation methods as possible. To find the trend, the study carried out a quantitative data analysis to investigate the frequency of each method over time in different modes of transport infrastructure. As a result, the research identified about 12 cost estimation methods and discusses them with three major cost estimation attributes i.e. accuracy, usability/application and easiness to understand. The quantitative analysis showed that parametric, Artificial Neural Networks and unit cost methods are the most used methods across the transport infrastructure. In addition, road infrastructure projects received the highest diversity and frequency of the cost estimation methods.