News

In recent years, the deployment of the autonomous car has been gradual, constant and has become normal. News of vehicles driving themselves through a neighborhood or testing on the highways has ceased to amaze. From wonder to curiosity. The prodigy has become an encompassing phenomenon, not always understood, but less arcane and rather technical.

In the middle of 2020 there are already many trials in real scenarios. It has even been tried to create commercial services - with a touch of experimentation but with all the guarantees - based on the transport of people in autonomous vehicles. At this point, the data collection is already large, the technology has been perfected, both the sensors and the artificial vision, the information processing or the algorithm training. Apparently the machines are practically ready. But at the technological level - the legal and social levels follow their own times, more slowly - there remains a detail.

There are many voices that point to the need to have 5G for the autonomous car to reach the highest level. This is what is known as level 5, which allows full autonomy. Here the driver's attention, even his presence, is no longer necessary. And is that the vehicles of this category can be manufactured even without steering wheel or brake or accelerator pedals.

In this article we can find some important points such as:

  • Real-time decision making: the importance of latency

    • What is necessary for a level 5 autonomous car

  • Large volumes of data

    • Information management in the autonomous car

  • V2X: Vehicle to everything

    • The problem of obsolete car fleets

    • Smart cities, autonomous car umbrella

    • First experiences with the autonomous car

  • Remote drivers

    • The debate on the regulation of the autonomous car

If you want to read the news, click on the following link: https://blogthinkbig.com/coche-autonomo-nivel-5-5g

During the month of November 2020, our colleague Eduardo Romera obtained the First Prize 🏆 in the "2020 Awards - Campus of International Excellence: Bioenergy & Smart Cites" in the Doctoral Thesis category, funded by the University of Universidad de Alcalá and Universidad Rey Juan Carlos.

The project, entitled "Semantic understanding of 3D scenes for autonomous vehicles through deep learning", was developed at the  Escuela Politécnica Superior UAH under the outstanding supervision of Prof. Luis Miguel Bergasa.

 

In September 2019 Luis Miguel Bergasa gave a lecture at the AI and Robotics Workshop organized by RoboCity2030 in Madrid titled "Robocity2030: Madrid Robotics Digital Innovation Hub".

In this WS the poster presented by our group entitled "Designing a Drive-by-Wire System for an Autonomous Electric Car" was awarded the prize for the best WS poster.

 

During the month of November 2020 our colleague Carlos Huélamo win the First Prize 🏆 in the "2020 Awards - Campus of International Excellence: Bioenergy & Smart Cites" in the Master's thesis category, funded by the Universidad de Alcalá and Universidad Rey Juan Carlos.

The project, titled "Predictive Techniques for Scene Understanding by using Deep Learning", was developed in the RobeSafe research group (Department of Electronics, Escuela Politécnica Superior UAH) under the outstanding supervision of Prof. Luis Miguel Bergasa.

The scope of the project is to propose an accurate and Real-Time Multi-Object Tracking (MOT) software architecture in the context of Intelligent Transportation Systems (ITS) by means of sensor fusion between LiDAR and Deep Learning based Visual Object Tracking. Additional tools involved in the project were ROS (Robot Operating System), Docker, Inc, the CARLA (CAR Learning to Act) autonomous driving simulator and our real-world autonomous electric vehicle.

 

To finish we leave you a phrase that Carlos cited regarding the award:
"Going together is starting, staying together is progress, working together is success"

On March 10,  Carlos Gómez Huélamo was recipient of an Honorable Mention in the XVI Edition of the contest "Premio a la Innovación Tecnológica 2019", sponsored by the Fundación Rodolfo Benito Samaniego (FRBS) and COIIM Colegio Oficial de Ingenieros Industriales de Madrid associations, representing one of the three best Master's Degree Final Project in Industrial Engineering among the regions of Madrid, Castilla y León, Castilla-La Mancha and País Vasco, including both the public and private universities. The project, titled "Técnicas Predictivas para el Entendimiento de Escenas usando Deep Learning", was supervised by Prof. Luis Miguel Bergasa.

In summary, the scope of the project, developed in the RobeSafe research group (Department of Electronics, Universidad de Alcalá), is to propose an accurate and real-time Deep Learning based Multi-Object Tracking (MOT) software architecture in the context of Intelligent Transportation Systems (ITS). Additional tools involved in the project were ROS (Robot Operating System), Docker, the CARLA autonomous driving simulator and our real world autonomous electric vehicle.

Thanks to my colleagues and professors of the UAH, specially those teammates of the RobeSafe research group, without which this award would have been unattainable.

And to finish he had some nice words of thanks: "Thanks to my colleagues and professors at UAH, especially colleagues from the RobeSafe research group, without whom this award would have been unattainable."