Abstract
Y This paper presents a method to clean and analyze big data compiled from raw and processed road-sensor measurements, thereby making a vital contribution toward traffic planning. A significant volume of sensor data could be used to monitor the count, speed, size, and type of vehicles to calculate accurate indicators. These indicators facilitate decision-making and deployment of subsequent measures to address traffic problems. The proposed method cleans and analyzes the data extracted from highway sensors during the third quarter of 2019. It employs the Bayesian recursive estimator (BRE) and other statistical formulae to generate clean data with fewer missing values. This facilitates the generation of appropriate data for calculating statistical indicators. The paper presents the indicators calculated using BRE-based traffic monitoring in the Kingdom of Saudi Arabia. The findings of this study reveal that big data extracted from highway sensors and cleansed using our proposed algorithm can be considered as a new source for producing official statistics that support the administration in the planning of transportation strategies and policies.