WSDC 4 – Zarządzanie ruchem i zbiory danych

Czwarte spotkanie grupy WSDC. Tym razem dwie prezentacje – wykorzystanie sztucznej inteligencji w zarządzaniu ruchem i zbiory danych.

Agenda:

  • 18:00 AI-based traffic management system for connected self-driving cars, Paweł Gora
  • 19:00 Datasets and how to create one?, Karol Majek, Deep Drive PL

Poniżej filmy. Całość była po angielsku:


Pierwsza prezentacja:

AI-based traffic management system for connected self-driving cars

Paweł Gora: In this talk, I will present the idea for a traffic management system, which uses traffic simulations to evaluate the qualities of the traffic signal settings, machine learning algorithms to approximate outcomes of simulations and evolutionary algorithms or reinforcement learning to find best traffic control strategies. The idea is under development within the TensorCell project, which I lead, and has been already presented in a few scientific papers and on the best conferences dedicated to transportation and artificial intelligence. The solution may be applied for traffic including only conventional cars, but I will explain why it may be especially powerful and beneficial in the era of connected and autonomous vehicles.

BIO: Paweł Gora is a researcher and Ph.D. candidate at the Faculty of Mathematics, Informatics, and Mechanics of the University of Warsaw. His research concerns mostly modeling and optimization of complex processes, such as vehicular traffic in cities. He developed software for realistic, large-scale traffic simulations, Traffic Simulation Framework, and is leading a research group TensorCell working on approximating outcomes of traffic simulations using machine learning algorithms (e.g., neural networks, LigthGBM), which may find applications in transport planning and real-time traffic management systems. He received the „LIDER ITS” award in 2015 and 2017 for the best R&D work in the intelligent transportation systems domain in Poland. He is also working on traffic models including connected and autonomous vehicles and is a representative of Poland in the COST Action „Wider Impacts and Scenario Evaluation of Connected and Autonomous Transport”. As an AI and quantum computing enthusiast, he is one of the co-organizers of Warsaw.ai meetup addressed to AI experts and „Quantum AI” Facebook group, as well as „Warsaw Quantum Computing Group”. In 2017, he was recognized by MIT Technology Review as 1 of 10 „Top Polish Talents Under 35”, and placed on a „New Europe 2017” list of 100 emerging technology stars in Eastern Europe. In the past, he worked as a software engineer and research intern at Microsoft, Google, CERN, and IBM Research.

I druga prezentacja:

Datasets and how to create one?

Karol Majek: In this talk, you will learn about currently available datasets which can be used to train neural networks or benchmark your solutions. You will learn what you can expect from public datasets and in the second part of this talk, you will learn what you need to know before you create your own dataset. You can expect knowledge and best practices on how to work with sensors and data.
Bonus – release of new dataset!

BIO: Karol Majek is working on Deep Drive PL, a blog related to Self-Driving, Deep Learning, but during the day he is working at NASK in mobile robotics department. He wants to share his knowledge and help people learn, so he created the Warsaw Self-Driving Cars Meetup, a place to meet people interested in Self-Driving Cars, exchange experience, learn, find a new job or people who want to work in the field.
Previously working as a Mentor at Udacity in Self-Driving Car Engineer Nanodegree.

Linki:

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