Rapid updating if 3D road traffic noise maps in large cities

A rapid updating system of three-dimensional road traffic noise maps is presented. The system described in this paper primarily consists of two parts. The first part is an optimized noise update algorithm, which can significantly improve the update speed for large scale noise maps by reducing the amount of calculation work. To make full use of scattered computing resources, the second part is a distributed computation system with high simplicity and extensibility and the ability of self-balance. For traffic flow data gathered in large cities, a model that uses a speed-density relationship is developed to estimate the traffic volume from the Global Positioning System (GPS) data collected by floating cars. Finally, an experiment was performed to analyze the efficiency of both the distributed computation system and the optimized algorithm. The outcomes show that the distributed computation system has a near-linear speedup and the optimized algorithm can update a noise map of a 5.25 km2 area with 446,367 noise receiver points using about 96 s. Thus, for a large city with an area of approximately 500 km2, such as the central area of Guangzhou, its noise map can be updated hourly using only 3 personal computers.