Assisted Driving Systems (ADS) are becoming more and more prevalent in our day to day lives. Today, almost all cars have integrated some form of ADS, whether it is a parking sensor or a full collision alert system in the likes of Mobileye. The goal of this project is to create an ADS that resembles Mobileye, using a drone that hovers above the car as the only sensor.
In addition, we offer a mobile application as an interface between the driver and the ADS that presents to the drive an aerial view of his vehicle in real time and alerts him when a potential collision hazard is detected – both visually and audibly.
Using a Drone as a sensor has many potential advantages: A drone is mobile, and so it offers a dynamic and virtually unlimited field of view. Using a drone the ADS can detect traffic jams or collisions ahead in real time without relying on potentially distorted user data. In addition, a drone requires no specific set-up for a car, and thus the ADS can be added or removed from the vehicle instantaneously.
Our ADS uses state-of-the-art Deep Learning algorithms to classify and detect the objects in the drone’s view. These algorithms are lightweight enough to run in real-time on an ordinary laptop.
Project’s book: project_book Link the project’s github repository: FlyEye’s Github Repo Future work: This project focuses on the collision detection part of the ADS and does not include a system for making the drone hover above the car. In future versions, GPS coordinates of the vehicle sent by the mobile app can be used by a more advanced drone model to track the car’s position.
Contact information: Itamar Shenhar: firstname.lastname@example.org Omer Licht: https://github.com/olicht Yuval Salant: email@example.com