Traffic Management in Smart Cities Using the Weighted Least Squares Method

TL;DR

This paper applies the weighted least squares method to optimize drone station placement in smart cities, aiming to reduce traffic congestion and improve emergency response capabilities.

Contribution

It introduces a novel application of the least squares method for optimal drone station placement in urban traffic management.

Findings

Optimal drone station locations identified near traffic hotspots

Reduction in traffic congestion through strategic drone deployment

Enhanced emergency response efficiency in smart city environments

Abstract

In this paper we demonstrate how one of the most powerful methods in mathematics and statistics can be used to optimally control and reduce traffics in smart cities. The main goal of the present work is to use the least squares method [5] to identify the best location of a portable drone station in a metropolitan city. By the best location we mean a location that is closest to traffic congestions and accidents that may occur on a daily basis. It is generally accepted that drones will play a key role in smart city environments in the near future. Drones will provide different types of public service, such as emergency response, disaster relief, and traffic control