# Optimized tour planning for drone-based urban traffic monitoring

arXiv: https://arxiv.org/abs/2007.06911 · HTML: https://mlsanity.com/paper/2007.06911/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jul 2020.

## Built on by (most cited first, 2 of 2)

- [CAROM Air -- Vehicle Localization and Traffic Scene Reconstruction from Aerial Videos](https://mlsanity.com/paper/2306.00075/) (2023)
- [Distributed Deep Reinforcement Learning for Intelligent Traffic Monitoring with a Team of Aerial Robots](https://mlsanity.com/paper/2107.04924/) (2021)

## Abstract (arXiv)

Drones or Unmanned Aerial Vehicles (UAVs) have become a reliable and efficient tool for road traffic monitoring. Compared to loop detectors and bluetooth receivers (with high capital and operational expenditure), drones are a low-cost alternative that offers great flexibility and high quality data. In this work, we derive optimized tour plans that a fleet of drones can follow for rapid traffic monitoring across particular regions of transportation network. To derive these tours, we first identify monitoring locations over which drones should fly through and then compute minimum travel-time tours based on realistic resource constraints. Evaluation results are presented over a real road network topology to demonstrate the applicability of the proposed approach.