Work zones are an essential part of roads maintenance. Despite all the efforts addressed to reduce work zone’s negative impacts on the road traffic performance and improve the road safety, there still exist work zone related congestions and traffic problems. This thesis aims to study and analyze highway reconstruction/maintenance activities, their impacts and existing ways of reducing these negative effects and investigating the role of Intelligent Transport Systems in improvement of the difficulties caused by work zones. The research of the factors influencing capacity resulted in three factors presented in each considered study. The factors are heavy vehicle percentage, weather conditions and police presence. An unusual approach presented by Weng & Meng (2011) distinguishes among the examined analytical models. Their Decision-Tree model, based on training a large data set, showed significantly lower values of errors of prediction of level-of-service. Three different dynamic late merge systems (DLMS) have been simulated and analyzed using the AIMSUN micro-simulation software. The simulation outcome shows promising results favoring the use of DLMS. Among the simulated systems is extra focus put on the ALINEA algorithm that shows potential to improve traffic flow in work zones. Conducted sensitivity analysis shows different behaving of the ALINEA algorithm due to change of regulator parameter and critical occupancy. In order to investigate performance of the ALINEA algorithm, an extensive research has to be conducted. The research should include various work zone configurations as well as different values of heavy vehicle percentage and the parameters within the algorithms code should be subjects to optimization.