scholarly journals Developing a Simulation Model for Autonomous Driving Education in the Robobo SmartCity Framework

2021 ◽  
Vol 7 (1) ◽  
pp. 49
Author(s):  
Daniel Juanatey ◽  
Martin Naya ◽  
Tamara Baamonde ◽  
Francisco Bellas
Keyword(s):  
Artificial Intelligence ◽  
Simulation Model ◽  
Smart City ◽  
State Of The Art ◽  
Autonomous Driving ◽  
The Real ◽  
Educational Framework ◽  
Real Model ◽  
Teachers And Students

This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the smartphone-based robot Robobo and a real model of a smart city. We describe the development of a simulation model of Robobo SmartCity in the CoppeliaSim 3D simulator, implementing both the real mock-up and the model of Robobo. In addition, a set of Python libraries that allow teachers and students to use state-of-the-art algorithms in their education projects is described too.

scholarly journals Securing Semiconductor Supply Chains

2021 ◽  
Author(s):  
Saif Khan
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Supply Chain ◽  
Supply Chains ◽  
Emerging Technologies ◽  
State Of The Art ◽  
The United States ◽  
Beneficial Use ◽  
Semiconductor Chips

The countries with the greatest capacity to develop, produce and acquire state-of-the-art semiconductor chips hold key advantages in the development of emerging technologies. At present, the United States and its allies possess significant leverage over core segments of the supply chain used to produce these chips. This policy brief outlines actions the United States and its allies can take to secure that advantage in the long term and use it to promote the beneficial use of emerging technologies, such as artificial intelligence.

scholarly journals Introduction Of Energy Saving Principles: Technologies And Awareness, Latvian Experience

2018 ◽  
Vol 55 (6) ◽  
pp. 52-62 ◽  
Author(s):  
A. Mutule ◽  
J. Teremranova
Keyword(s):  
Energy Saving ◽  
Smart City ◽  
Energy Efficient ◽  
New Technologies ◽  
State Of The Art ◽  
Smart Cities ◽  
Current Situation ◽  
Wide Range ◽  
New Energy

Abstract The article presents an overview of the current situation of awareness of the Latvian citizens in the field of state-of-the-art energy-saving technologies. The authors present a wide range of data obtained as a result of a survey on the attitude of residents to new technologies and readiness to follow the development trends of a smart city. The article contains the analysis and recommendations for improving the efficiency of introducing new energy-saving and energy-efficient technologies into each household in order to create the most favourable conditions for the implementation of long-term plans for the development of smart cities in Latvia.

scholarly journals When Pedestrian Detection Meets Nighttime Surveillance: A New Benchmark

2020 ◽  
Author(s):  
Xiao Wang ◽  
Jun Chen ◽  
Zheng Wang ◽  
Wu Liu ◽  
Shin'ichi Satoh ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Critical Time ◽  
Autonomous Driving ◽  
Benchmark Dataset ◽  
Lighting Conditions ◽  
Criminal Suspects

Pedestrian detection at nighttime is a crucial and frontier problem in surveillance, but has not been well explored by the computer vision and artificial intelligence communities. Most of existing methods detect pedestrians under favorable lighting conditions (e.g. daytime) and achieve promising performances. In contrast, they often fail under unstable lighting conditions (e.g. nighttime). Night is a critical time for criminal suspects to act in the field of security. The existing nighttime pedestrian detection dataset is captured by a car camera, specially designed for autonomous driving scenarios. The dataset for nighttime surveillance scenario is still vacant. There are vast differences between autonomous driving and surveillance, including viewpoint and illumination. In this paper, we build a novel pedestrian detection dataset from the nighttime surveillance aspect: NightSurveillance1. As a benchmark dataset for pedestrian detection at nighttime, we compare the performances of state-of-the-art pedestrian detectors and the results reveal that the methods cannot solve all the challenging problems of NightSurveillance. We believe that NightSurveillance can further advance the research of pedestrian detection, especially in the field of surveillance security at nighttime.

Autonomous driving in urban environments: approaches, lessons and challenges

2010 ◽  
Vol 368 (1928) ◽  
pp. 4649-4672 ◽  
Author(s):  
Mark Campbell ◽  
Magnus Egerstedt ◽  
Jonathan P. How ◽  
Richard M. Murray
Keyword(s):  
Autonomous Vehicles ◽  
New Technologies ◽  
State Of The Art ◽  
Autonomous Driving ◽  
Urban Environments ◽  
Vehicle Safety ◽  
Paper Briefly ◽  
The Past ◽  
Current State

The development of autonomous vehicles for urban driving has seen rapid progress in the past 30 years. This paper provides a summary of the current state of the art in autonomous driving in urban environments, based primarily on the experiences of the authors in the 2007 DARPA Urban Challenge (DUC). The paper briefly summarizes the approaches that different teams used in the DUC, with the goal of describing some of the challenges that the teams faced in driving in urban environments. The paper also highlights the long-term research challenges that must be overcome in order to enable autonomous driving and points to opportunities for new technologies to be applied in improving vehicle safety, exploiting intelligent road infrastructure and enabling robotic vehicles operating in human environments.

Ethics of Artificial Intelligence

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Moral Status ◽  
Technology Development ◽  
State Of The Art ◽  
Critical Time ◽  
Human Intervention ◽  
Weapon Systems ◽  
Original Essays ◽  
Near Future

Featuring seventeen original essays on the ethics of artificial intelligence (AI) by today’s most prominent AI scientists and academic philosophers, this volume represents state-of-the-art thinking in this fast-growing field. It highlights central themes in AI and morality such as how to build ethics into AI, how to address mass unemployment caused by automation, how to avoid designing AI systems that perpetuate existing biases, and how to determine whether an AI is conscious. As AI technologies progress, questions about the ethics of AI, in both the near future and the long term, become more pressing than ever. Should a self-driving car prioritize the lives of the passengers over those of pedestrians? Should we as a society develop autonomous weapon systems capable of identifying and attacking a target without human intervention? What happens when AIs become smarter and more capable than us? Could they have greater than human-level moral status? Can we prevent superintelligent AIs from harming us or causing our extinction? At a critical time in this fast-moving debate, thirty leading academics and researchers at the forefront of AI technology development have come together to explore these existential questions.

scholarly journals Reference Pose Generation for Long-term Visual Localization via Learned Features and View Synthesis

2020 ◽  
Author(s):  
Zichao Zhang ◽  
Torsten Sattler ◽  
Davide Scaramuzza
Keyword(s):  
3D Model ◽  
Feature Matching ◽  
State Of The Art ◽  
Autonomous Driving ◽  
Visual Localization ◽  
Uncertainty Estimates ◽  
Feature Correspondences ◽  
Key Enabling Technologies ◽  
Learned Features

AbstractVisual Localization is one of the key enabling technologies for autonomous driving and augmented reality. High quality datasets with accurate 6 Degree-of-Freedom (DoF) reference poses are the foundation for benchmarking and improving existing methods. Traditionally, reference poses have been obtained via Structure-from-Motion (SfM). However, SfM itself relies on local features which are prone to fail when images were taken under different conditions, e.g., day/night changes. At the same time, manually annotating feature correspondences is not scalable and potentially inaccurate. In this work, we propose a semi-automated approach to generate reference poses based on feature matching between renderings of a 3D model and real images via learned features. Given an initial pose estimate, our approach iteratively refines the pose based on feature matches against a rendering of the model from the current pose estimate. We significantly improve the nighttime reference poses of the popular Aachen Day–Night dataset, showing that state-of-the-art visual localization methods perform better (up to 47%) than predicted by the original reference poses. We extend the dataset with new nighttime test images, provide uncertainty estimates for our new reference poses, and introduce a new evaluation criterion. We will make our reference poses and our framework publicly available upon publication.

Hidden “holes” in the capital of banks and the supply of credit to the real sector of economy

2018 ◽  
pp. 49-68 ◽  
Author(s):  
M. E. Mamonov
Keyword(s):  
Credit Risk ◽  
The Other ◽  
Real Sector ◽  
Capital Management ◽  
Loan Loss ◽  
Short Term ◽  
The Real ◽  
Ex Post ◽  
The One

Our analysis documents that the existence of hidden “holes” in the capital of not yet failed banks - while creating intertemporal pressure on the actual level of capital - leads to changing of maturity of loans supplied rather than to contracting of their volume. Long-term loans decrease, whereas short-term loans rise - and, what is most remarkably, by approximately the same amounts. Standardly, the higher the maturity of loans the higher the credit risk and, thus, the more loan loss reserves (LLP) banks are forced to create, increasing the pressure on capital. Banks that already hide “holes” in the capital, but have not yet faced with license withdrawal, must possess strong incentives to shorten the maturity of supplied loans. On the one hand, it raises the turnovers of LLP and facilitates the flexibility of capital management; on the other hand, it allows increasing the speed of shifting of attracted deposits to loans to related parties in domestic or foreign jurisdictions. This enlarges the potential size of ex post revealed “hole” in the capital and, therefore, allows us to assume that not every loan might be viewed as a good for the economy: excessive short-term and insufficient long-term loans can produce the source for future losses.

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