Evaluation of the Effects of Maintenance and Rehabilitation Projects on Road User Costs via HDM-4 Software

Rapid growth in a number of vehicles on roadways accelerates pavement deterioration trends. Pavement inefficiency in carrying the applied load from passing vehicles results in spending significant costs on continues Maintenance and Rehabilitation (M&R) treatments. Lane closure owing to the implementation of M&R operations incurs enormous costs on road users. The research aimed to calculate, and compare Road Agency Costs (RACs) with Road User Costs (RUCs) resulted from certain types of M&R interventions on a selected roads network located in eastern part of Iran. RUCs are divided into two main categories; namely, Vehicles Operational Cost (VOC) and Travel Time Cost (TTC). The main contribution of the paper was to demonstrate the importance of RUCs in long-term economic analysis and planning of future M&R activities. A number of complicated parameters are involved in RUC estimation. The latter is the primary reason for excluding RUCs in the economic analysis. Towards this end, the HDM-4 Software was employed to calculate costs using localized data. Calibrating the HDM-4 as well as collecting the required information, the long-term effects of preservation alternatives associated with their costs were evaluated and compared. Results showed that RUCs were approximately 10 times higher than RACs on each route of the selected roads network. This revealed the importance of RUC in the Life Cycle Cost Analysis (LLCA) of different M&R actions tale place on highways. Hence, taking into account RUCs within analysis approaches would yield propose the most appropriate and cost-effective M&R alternative. Also, it was concluded that traffic composition and the number of Equivalent Single Axle Loads (ESALs) in the analysis period were contributing factors to RUCs calculation. In addition, owing to the long queue formation because of road obstruction, VOCs were always higher than increased TTCs, illustrating the importance of traffic volume and composition.