Paper Title :Truck Routing Prediction and Optimal Overloaded Vehicle Checkpoint Location Selection Service Plan using Big Data

Author :Tae-Hak Kim, Hyun Ok, Seong-Jin Kim

Article Citation :Tae-Hak Kim ,Hyun Ok ,Seong-Jin Kim , (2017 ) " Truck Routing Prediction and Optimal Overloaded Vehicle Checkpoint Location Selection Service Plan using Big Data " , International Journal of Advances in Mechanical and Civil Engineering (IJAMCE) , pp. 5-8, Volume-4,Issue-6

Abstract : The recent expansion of road facilities and the activation of vehicle-based logistics have led to an increase of overloaded vehicles. Overloaded vehicles accelerate the failure of road pavement, reducing the service life of roads and consuming a considerable national budget in performing repair and maintenance work for facilities. The government checks overloaded vehicles through overloaded vehicle control works, but the existing check pattern is well known to drivers who can easily circumvent such a control scheme. Therefore, the present study aimed to develop a plan to predict truck routes and select optimal locations for overloaded vehicle checkpoints by analyzing truck driving patterns by the day of the week and time of the day, using various analysis techniques on overloading-related data, such as truck driving records, inspection and control information, and traffic information among others. Keywords - Overload, Big-Data, Cargo Vehicle Traffic, Patterns, DTG

Type : Research paper

Published : Volume-4,Issue-6

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