scholarly journals Research and Educational Programs for Connected and Autonomous Vehicles at the University of Waterloo

2017 ◽  
Vol 139 (12) ◽  
pp. S21-S23
Author(s):  
Ross Mckenzie ◽  
John Mcphee
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Engineering Students ◽  
Pattern Analysis ◽  
Autonomous Driving ◽  
Educational Programs ◽  
Transportation Systems ◽  
Systems Research ◽  
Vehicle Systems ◽  
The University

This article presents an overview of the research and educational programs for connected and autonomous vehicles at the University of Waterloo (UWaterloo). UWaterloo is Canada’s largest engineering school, with 9,500 engineering students and 309 engineering faculty. The University of Waterloo Centre for Automotive Research (WatCAR) for faculty, staff and students is contributing to the development of in-vehicle systems education programs for connected and autonomous vehicles (CAVs) at Waterloo. Over 130 Waterloo faculty, 110 from engineering, are engaged in WatCAR’s automotive and transportation systems research programs. The school’s CAV efforts leverage WatCAR research expertise from five areas: (1) Connected and Autonomous; (2) Software and Data; (3) Lightweighting and Fabrication; (4) Structure and Safety; and (5) Advanced Powertrain and Emissions. Foundational and operational artificial intelligence expertise from the University of Waterloo Artificial Intelligence Institute complements the autonomous driving efforts, in disciplines that include neural networks, pattern analysis and machine learning.

scholarly journals Introduction to the Special Issue on the Man and the Machine

2016 ◽  
Vol 7 (2) ◽  
pp. 295-296
Author(s):  
Thomas Burri ◽  
Isabelle Wildhaber
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Autonomous Robots ◽  
Autonomous Systems ◽  
Federal Aviation Administration ◽  
Legal Issues ◽  
Special Issue ◽  
The Us ◽  
Modern Business ◽  
The University

This special issue assembles five articles ensuing from a conference on “The Man and the Machine: When Systems Take Decisions Autonomously”, which took place on June 26 and 27, 2015, at the University of St. Gallen in Switzerland.The aim of the conference was to explore the broader implications of artificial intelligence, machine learning and autonomous robots and vehicles. Alphabet's Deep Mind is just one example about Whom we know, at least a little, and who, we are told, will be good. Autonomous vehicles are also about to enter the market and our phones have begun to verbalize at us. Private drones are being regulated by the US Federal Aviation Administration. The five papers in this special issue address some of the legal issues the broader development raises.The first article is on “The Implications of Modern Business-Entity Law for the Regulation of Autonomous Systems” and is written by Shawn Bayern.

scholarly journals Human factors concern on autonomous vehicles’ safety, ethics and cost saving for the ridesharing industries

2021 ◽  
Vol 11 (9) ◽  
pp. 2331-2340 ◽  
Author(s):  
Bankole K. Fasanya ◽  
Abosede O. Gbenga-Akinbiola
Keyword(s):  
Artificial Intelligence ◽  
Cost Saving ◽  
Business Model ◽  
Autonomous Vehicles ◽  
Public Perception ◽  
Autonomous Driving ◽  
Transportation Industry ◽  
Comprehensive Understanding ◽  
Technological Readiness ◽  
Autonomous Technology

Artificial Intelligence (AI) is a motivation for full usage of autonomous driving. Many have predicted that autonomous technology would significantly disrupt the transportation industry. This research examines how autonomous driving might impact and disrupt the ridesharing industry and their drivers. The hypothesis is that autonomous vehicles (AV) will negatively impact the ridesharing industry. To examine the full effects of this disruption, we researched current literature on driverless technology cars and the ridesharing industry. Factors examined include: current economics of drivers and vehicles, public perception and acceptance, technological readiness, collaborations, regulations, and liability. Key findings from a host of resources were tabulated to build a case for the proposed hypothesis. The results provide a more comprehensive timeline estimate, predicted $0.75 cost estimate per mile by 2040, and documented the collaboration figure among the players that shows the significant investments across different industries. This research shows that the ridesharing industry’s current business model is due for a significant disruption by autonomous driving capabilities. Drivers in the ridesharing industry might likely suffer the most, however not for at least another decade or so. There are many independent factors, which must be further scrutinized to develop a more comprehensive understanding as to the velocity of this disruption. Findings from this study would be applicable while evaluating the future of autonomous vehicles.

scholarly journals Autonomous Recognition Model

2021 ◽  
Vol 10 (6) ◽  
pp. 67-73
Author(s):  
Akash gupta ◽  
Rahat Ali ◽  
Abhay Pratap Singh ◽  
P.Raja Kumar
Keyword(s):  
Artificial Intelligence ◽  
Automobile Industry ◽  
Autonomous Vehicles ◽  
Future Generation ◽  
Autonomous Driving ◽  
Traffic Signs ◽  
Use Of Technology ◽  
Human Driver ◽  
New Research ◽  
Self Driving Cars

Nowdays we are witnessing the technology transforming everything the way we used to do things and how the automobile industry is transforming itself with the use of technology IOT,Artificial intelligence,Machine learning.Companies shifting its products and its utilities in diferent way and they now want to acquire and introduce level-5 autonomous to future generation and big automobile companies are trying to achieve autonomous vechicles and we have researhed about the model that will help in assisting autonomous vechicles and trying to achieve that.We will develop this model with help of technologies like Artificial intelligence,Machine learning,Deep learning.Autonomous vehcicles will become a reality on our roads in the near future. However, the absence of a human driver requires technical solutions for a range of issues, and these are still being developed and optimised. It is a great contribution for the automotive industry which is going towards innovation and economic growth. If we talking about some past decade the momentum of new research and the world is now at the very advanced stage of technological revolution. “Autonomous-driving” vehicles. The term Self-driving cars, autonomous car, or the driverless cars have different name with common objective. The main focus is to keep the human being out of the vehicle control loop and to relieve them from the task of driving. Everyday automotive technology researchers solve challenges. In the future, without human assistance, robots will produce autonomous vehicles using IoT technology based on customer needs and prefer that these vehicles are more secure and comfortable in mobility systems such as the movement of people or goods. We will build a deep neural network model that can classify traffic signs present in the image into different categories. With this model, we are able to read and understand traffic signs which are a very important task for all autonomous vehicles .This model we have tested it and resulted in 95% accuracy.

scholarly journals Students Working Towards Robotic Chauffeurs: The SAE/GM Autodrive Challenge

2018 ◽  
Vol 140 (03) ◽  
pp. S6-S11
Author(s):  
Diane L. Peters
Keyword(s):  
Autonomous Vehicles ◽  
Engineering Students ◽  
Real Life ◽  
Autonomous Driving ◽  
Interdisciplinary Teams ◽  
Academic Disciplines ◽  
General Motors ◽  
Hands On ◽  
The Us ◽  
Time Domain Response

This article focuses on efforts by automotive manufacturers and engineering students towards developing autonomous vehicles. The Society of Automotive Engineers (SAE) has defined different levels of autonomy (SAE J3016 standard), to describe how automated a vehicle is, which have also been adopted by the US Department of Transportation. The purpose of SAE and General Motors (GM) in designing and implementing hands-on engineering design and conducting technology-focused collegiate competition with an emphasis on autonomous driving and the associated technologies´ is to provide a professional development and educational experience for undergraduate and graduate students enrolled at selected universities. SAE and its sponsors are supporting the competition with training and mentoring. Students are also learning how to work in interdisciplinary teams, which has its own issues. Different academic disciplines approach problems differently, use different techniques, and sometimes even seem to speak a different language. Another important thing about the Challenge is that it lets them see how their courses impact real engineering problems. Students taking a controls course see plenty of Laplace transforms and all sorts of plots—root-locus plots, perhaps Nyquist plots or Bode plots, time domain response plots—but they may not always realize how this links up to real life.

scholarly journals An Intelligent Actuator of an Indoor Logistics System Based on Multi-Sensor Fusion

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 120
Author(s):  
Pangwei Wang ◽  
Yunfeng Wang ◽  
Xu Wang ◽  
Ying Liu ◽  
Juan Zhang
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Inertial Navigation System ◽  
Route Planning ◽  
Autonomous Driving ◽  
Transportation Systems ◽  
A Algorithm ◽  
Logistics System ◽  
Planning Strategy ◽  
Logistics Distribution

Integration technologies of artificial intelligence (AI) and autonomous vehicles play important roles in intelligent transportation systems (ITS). In order to achieve better logistics distribution efficiency, this paper proposes an intelligent actuator of an indoor logistics system by fusing multiple involved sensors. Firstly, an actuator based on a four-wheel differential chassis is equipped with sensors, including an RGB camera, a lidar and an indoor inertial navigation system, by which autonomous driving can be realized. Secondly, cross-floor positioning can be realized by multi-node simultaneous localization and mappings (SLAM) based on the Cartographer algorithm Thirdly the actuator can communicate with elevators and take the elevator to the designated delivery floor. Finally, a novel indoor route planning strategy is designed based on an A* algorithm and genetic algorithm (GA) and an actual building is tested as a scenario. The experimental results have shown that the actuator can model the indoor mapping and develop the optimal route effectively. At the same time, the actuator displays its superiority in detecting the dynamic obstacles and actively avoiding the collision in the indoor scenario. Through communicating with indoor elevators, the final delivery task can be completed accurately by autonomous driving.

scholarly journals A Survey about Intelligent Solutions for Autonomous Vehicles based on FPGA

2020 ◽  
Vol 13 (2) ◽  
pp. 7-11
Author(s):  
Ashraf Kasem ◽  
Ahmad Reda ◽  
József Vásárhelyi ◽  
Ahmed Bouzid
Keyword(s):  
Artificial Intelligence ◽  
Power Consumption ◽  
Autonomous Vehicles ◽  
High Performance ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Real Problem ◽  
Safe Driving ◽  
Field Programmable ◽  
Increasing Demand

Abstract Safe driving and reducing the number of accidents victims have been the main motivations for researchers and automotive companies for decades. Today, humanity is very close to make the old dream of fully autonomous vehicles a reality, thanks to the rapid spread of AI (artificial intelligence) and the evolution of semiconductor technologies. But the real problem here is the increasing demand for computational power and that of course will increase power requirements, hence it will not be suitable for autonomous driving applications. GPU is not suitable for solving this problem due to its power consumption as well as heat generation. On the other hand, CPU also does not satisfy the performance requirements. For the above condition, FPGA (Field Programmable Gate Array) has drawn attention as a hardware accelerator since it features high performance with low power consumption. This paper reviews the common solutions involving artificial intelligence implemented on FPGA for autonomous vehicle applications. Research, development, and current trends related to the topic are emphasized.

scholarly journals Blockchain Applications to Improve Operation and Security of Transportation Systems: A Survey

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 629
Author(s):  
Navid Khoshavi ◽  
Gabrielle Tristani ◽  
Arman Sargolzaei
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Transportation Systems ◽  
Great Success ◽  
Blockchain Technology ◽  
Fields Of Study ◽  
Vehicle Systems ◽  
Potential Applications ◽  
Near Future ◽  
Broad Overview

Blockchain technology continues to grow and extend into more areas with great success, which highlights the importance of studying the fields that have been, and have yet to be, fundamentally changed by its entrance. In particular, blockchain technology has been shown to be increasingly relevant in the field of transportation systems. More studies continue to be conducted relating to both fields of study and their integration. It is anticipated that their existing relationships will be greatly improved in the near future, as more research is conducted and applications are better understood. Because blockchain technology is still relatively new as compared to older, more well-used methods, many of its future capabilities are still very much unknown. However, before they can be discovered, we need to fully understand past and current developments, as well as expert observations, in applying blockchain technology to the autonomous vehicle field. From an understanding and discussion of the current and potential future capabilities of blockchain technology, as provided through this survey, advancements can be made to create solutions to problems that are inherent in autonomous vehicle systems today. The focus of this paper is mainly on the potential applications of blockchain in the future of transportation systems to be integrated with connected and autonomous vehicles (CAVs) to provide a broad overview on the current related literature and research studies in this field.

Training managers of professional educational programs for work in the digital environment of the university

2020 ◽  
Vol 8 (2) ◽  
pp. 4 ◽  
Author(s):  
E. K. Samerhanova ◽  
M. A. Balakin
Keyword(s):  
Educational Program ◽  
Educational Programs ◽  
Educational Process ◽  
Digital Environment ◽  
Digital Competence ◽  
Education Management ◽  
Program Managers ◽  
Digital Environments ◽  
Digital Competencies ◽  
The University

Introduction. The article deals with the training of professional educational program managers for work in the digital environment of a university. The digital environment of the university is considered from the perspective of managing professional educational programs and is a complex open system that integrates system components for managing content, process, resources, contingent, finance and quality of programs that ensure the integrity and continuity of the educational process at all levels and in all respects. The implementation of a digital model for managing educational programs at a university on the basis of a single digital ring of services for an electronic platform for managing educational programs at a university dictates the need for digital competencies of managers of major professional educational programs (OPOP).By digital competence of the leaders of professional educational programs we mean the ability and willingness to perform labor functions in the design, implementation and replication of an educational program using digital technologies that ensure the effectiveness of activitiesThe way to identify professional deficiencies in the field of digital competencies of the leaders of professional educational programs was the personalized design of educational internship trajectories with tutorial support for the internship. The internship trajectory of the heads of OPOP has a modular structure and is aimed at eliminating professional deficits in the field of information, methodological, communication, technological and organizational component of digital competencies. The internship site (virtual laboratory) is a virtual educational space that provides training for educational program managers and online events: hackaths, quests, webinars, etc.Materials and methods. When writing an article, the following methods were used - theoretical and methodological analysis and synthesis of available special domestic and foreign scientific and methodological literature, conceptual analysis of scientific articles and publications on the topic; study and generalization of both domestic and foreign developments and implementation of projects to create digital environments in education management; application of generalization, comparison, forecasting methods, online surveys.Results. The structure of the digital environment for managing professional educational programs at the university is presented. Functionally described is the ring of digital services for the management of OPOP. The analysis of different approaches to assessing the digital competencies of educators is presented. The concept of digital competencies has been clarified in relation to the head of a professional educational program. The content of the components of digital competency is described: informational, methodological, communication, technological, organizational.Discussions and Conclusions. The developed modular program for eliminating professional deficits of heads of professional educational programs in the field of digital competencies, based on the personalized design of educational internship trajectories with tutorial support for internships, will allow you to effectively administer and manage BEP in the digital environment of the university.

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