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The UAH-DriveSet

The UAH-DriveSet is a public collection of data captured by our driving monitoring app DriveSafe by various testers in different environments. This dataset tries to facilitate progress in the field of driving analysis by providing a large amount of variables that were captured and processed by all the sensors and capabilities of a smartphone during independent driving tests. The application was run on 6 different drivers and vehicles, performing 3 different behaviors (normal, drowsy and aggressive) on two types of roads (motorway and secondary road), resulting in more than 500 minutes of naturalistic driving with its associated raw data and additional semantic information, together with the video recordings of the trips.

 

                 

To download this database click here:

The UAH-DriveSet

 

RobeSafe Driver Monitoring Video Dataset (RS-DMV)

The RS-DMV dataset is a set of video sequences of drivers, recorded with cameras installed over the dashboard. The dataset currently contains 10 video sequences. The drivers were fully awake, talked frequently and were asked to look regularly to rear-view mirrors and operate the car sound system. Sequences contain occlusions, illumination changes and other elements that are problematic to face tracking and driver monitoring systems using computer vision.

Frames are recorded in gray-scale, at 30 frames per second, and stored as RAW video. Frame size of outdoor videos is 960x480 pixels, and 1390x480 for indoor videos. Faces in the videos have been marked with 20 points.

The RS-DMV was created by the RobeSafe Research Group of the Dpt. of Electronics of the UAH.  Videos recorded in a simulator were recorded under the CABINTEC project.

 

To download this database click here:

Datasets (uah.es)

Miguel Eduardo Ortiz Huamani

Personal Information

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Position: Master Student

gitHub: Miguel Eduardo Ortiz Huamani

 

About me

Graduated in Computer Engineering and Master Student in Cybersecurity at University of Alcalá.

 

Research Areas

Computer Vision, Machine Learning, Deep Learning, Intelligent Vehicles, Robotics

Juan Felipe Arango Vargas

Personal Information

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Position: Phd Student

LinkedIn: Juan Felipe Arango Vargas

 

About me

My name is Juan Felipe Arango Vargas, currently PhD candidate in Advanced Electronic Systems and Intelligent Systems at the RobeSafe research group (Electronics Department, University of Alcalá) under the supervision of Prof. Luis Miguel Bergasa and Prof. Pedro Revenga. I received my BSc degree in Industrial Electronics and Automation Engineering and my MSc in Industrial Engineering from the University of Alcalá.

My PhD thesis is focused on "Autonomous Navigation Techniques Validation over a Real Electric Vehicle". As member of the RobeSafe research group, I am working within Tech4AgeCar and RoboCity2030 research projects. My main role consist in the automation and preparation of an electric vehicle to carry out validation tests of the autonomous navigation systems developed within the group. More specifically, my work is the design and implementation of the Drive-By-Wire module and the Localization module based on RTK-DGNSS, IMU and odometry positions fusion, as well as designing the validation methods of the navigation techniques in real environments.

 

Research Areas

Autonomous Vehicle, Drive-By-Wire System, Global Navigation Satellite System (GNSS), Real-Time Kinematic (RTK) Positioning, MEMS-IMU, Sensor Fusion, Extended Kalman Filter (EKF), Robot Operating System (ROS), Automotive Electronics, Embedded Systems.

Santiago Montiel Marín

Personal Information

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Position: BSc in Electronics and Industrial Automation Engineering

Linkedin: Santiago Montiel

 gitHub: Santiago Montiel

About me

My name is Santiago Montiel Marín, currently studying the fourth and last year of a BSc degree in Electronics and Industrial Automation Engineering at University of Alcalá. As a research staff member of RobeSafe Research Group (Electronics Department, University of Alcalá), I am developing my Final's Degree Project "Multi Object-Tracking system based on LiDAR and RADAR for Intelligent Vehicles applications" under the supervision of Prof. Luis Miguel Bergasa and PhD student Carlos Gómez Huélamo. I would like this project to become the starting point of my research career. Main areas of interest consist of Computer Vision, Machine Learning, Deep Learning, Robotics, Embedded Systems, Perception in Intelligent Vehicles and any field related to these.

 

Research Areas

Computer Vision, Machine Learning, Deep Learning, Robotics, Embedded Systems, Perception in Intelligent Vehicles

Rodrigo Gutiérrez-Moreno

Personal Information

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Position: Phd Student

LinkedIn: Rodrigo Gutiérrez-Moreno

github: Rodrigo Gutiérrez-Moreno

 

About me

My name is Rodrigo Gutiérrez Moreno, currently PhD candidate in Artificial Intelligence and Robotics at the RobeSafe research group (Electronics Department, University of Alcalá) under the supervision of Prof. Luis Miguel Bergasa. I received my BSc degree in Industrial Electronics and Automation Engineering from the University of Alcalá (2012-2017) , in which I was granted with an Erasmus+ scholarship to study in the University of Portsmouth (UK) and my MSc in Robotics and Automation from the UPM (2017-2018). As member of the RobeSafe research group, I am working in research projects with other universities and companies to generate an important technology transfer to companies and publications. In particular, my PhD thesis is focused on "Decision making of an autonomous ground vehicle based in reinforcement learning and POMDPs".

 

Researcher Areas

Autonomous vehicle, control, decision making, reinforcement learning.

Location

Polytechnic School

University of Alcalá

Av. Jesuitas s/n.

Alcalá de Henares, 28871

Madrid, Spain

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