A Cluster-Based Method for Evaluation of Truck's Weighing Control Stations

Effective and safe road network is essential to economic growth and social welfare (Islamic Republic of Iran Majlis, 2005). More than 550 million tons of goods are transported by road network in Islamic Republic of Iran, which is a large amount of total cargo transportation's rate (RMTO, 2009). Overloading of vehicles increases safety risk and pavement damages (Planning and Management Organization, 1996), so to improve road safety and restrain pavement damages, legislation based on maximum allowable axle and total load is applied for heavy vehicles, which are passing on the roads (Mohammadi, 1999). Law enforcement control is done by weighing control equipments, which have been installed near the arterial roads, and to evaluate law enforcement, clustering method can be used as an effective technique. Clustering method is used to classify data and decision making in transportation studies. Some researchers (Ahmed and Kanhere, 2007) used clustering method for public transport modeling in order to improve situation and possibility of changing decision in public transportation. They showed that using a step forward algorithm for clustering the nodes in finding routes problems while using clustering method, improves effectiveness of algorithm. Clustering has been used to classify accident types (Depaire et al. 2008). They used a model based on clustering data, which divide accident data to 7 homogenous groups and finally analyzed injuries in each group .Comparing results based on divided groups and total data analysis showed that classifying data could be used for safety issues researchers with more accuracy. (Fielding et. al 1985) used clustering method for analyzing transit systems equipments, considering vehicle's size, average speed, urban transportation situation, and bus specified routes, and have classified transit situation to 12 categories. Difference of characteristics for all categories was identified using variance analysis, detached group and tree decisionmaking method. Grouping data were made by seven main transit efficiency factors and finally some suggestion for each group was supposed to productivity evaluation. In this paper after a brief review on methods of controlling cargo transportation and existing regulation in rural roads network, an evaluation method of trucks weighing control is presented using clustering analysis method. For evaluation and comparing results, available data on trucks weighing control, which have been collected by local authorities in all over