Autonomous Boat Control Software Design Using Model-Based Systems Engineering

While there is considerable buzz about self-driving cars, self-driving boats are actually more fully developed. The Boat Hardware Control Platform Team was tasked with developing a fleet of small autonomous boats that travel to a destination while avoiding obstacles and staying in formation. The author’s specific task was to develop software used by the boats to detect obstacles and plan a route to a destination. This was done using a method inspired by self-driving cars, which shows promise, but is still being tested at the time of writing. The entire project incorporated model-based systems engineering, which proved to be useful

Self Driving Car: Artificial Intelligence Approach

- Artificial Intelligence also known as (AI) is the capability of a machine to function as if the machine has the capability to think like a human. In automotive industry, AI plays an important role in developing vehicle technology. Vehicular automation involves the use of mechatronics and in particular, AI to assist in the control of the vehicle, thereby relieving responsibilities from the driver or making a responsibility more manageable. Autonomous vehicles sense the world with such techniques as laser, radar, lidar, Global Positioning System (GPS) and computer vision. In this paper, there are several methodologies of AI techniques such as: fuzzy logic, neural network and swam intelligence which often used by autonomous car. On the other hand, self driving cars are not in widespread use, but their introduction could produce several direct advantages: fewer crashes, reduce oil consumption and air pollution, elimination of redundant passengers, etc. So that, in future where everyone can use a car and change the way we use our highways. Key Words - artificial intelligence, self driving, vehicular automation, fuzzy logic, neural network, swam intelligence

Merging self-driving cars with the law

Self-driving cars are gradually being introduced in the United States and in several Member States of the European Union. Policymakers will thus have to make important choices regarding the application of the law. One important aspect relates to the question who should be held liable for the damage caused by such vehicles. Arguably, product liability schemes will gain importance considering that the driver's fault as a cause of damage will become less likely with the increase of autonomous systems. The application of existing product liability legislation, however, is not always straightforward. Without a proper and effective liability framework, other legal or policy initiatives concerning technical and safety matters related to self-driving cars might be in vain. The article illustrates this conclusion by analysing the limitation periods for filing a claim included in the European Union Product Liability Directive, which are inherently incompatible with the concept of autonomous vehicles. On a micro-level, we argue that every aspect of the Directive should be carefully considered in the light of the autonomisation of our society. On the macro-level, we believe that ongoing technological evolutions might be the perfect moment to bring the European Union closer to its citizens. (C) 2018 Jan De Bruyne and Jarich Werbrouck. Published by Elsevier Ltd. All rights reserved

From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation

Context: Competitions for self-driving cars facilitated the development and research in the domain of autonomous vehicles towards potential solutions for the future mobility. Objective: Miniature vehicles can bridge the gap between simulation-based evaluations of algorithms relying on simplified models, and those time-consuming vehicle tests on real-scale proving grounds. Method: This article combines findings from a systematic literature review, an in-depth analysis of results and technical concepts from contestants in a competition for self-driving miniature cars, and experiences of participating in the 2013 competition for self-driving cars. Results: A simulation-based development platform for real-scale vehicles has been adapted to support the development of a self-driving miniature car. Furthermore, a standardized platform was designed and realized to enable research and experiments in the context of future mobility solutions. Conclusion: A clear separation between algorithm conceptualization and validation in a model-based simulation environment enabled efficient and riskless experiments and validation. The design of a reusable, low-cost, and energy-efficient hardware architecture utilizing a standardized software/hardware interface enables experiments, which would otherwise require resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table

Ethical and Social Aspects of Self-Driving Cars

As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.Comment: 11 pages, 3 figures, 2 table

Too sick to drive : how motion sickness severity impacts human performance

There are multiple concerns surrounding the development and rollout of self-driving cars. One issue has largely gone unnoticed - the adverse effects of motion sickness as induced by self-driving cars. The literature suggests conditionally, highly and fully autonomous vehicles will increase the onset likelihood and severity of motion sickness. Previous research has shown motion sickness can have a significant negative impact on human performance. This paper uses a simulator study design with 51 participants to assess if the scale of motion sickness is a predictor of human performance degradation. This paper finds little proof that subjective motion sickness severity is an effective indicator of the scale of human performance degradation. The performance change of participants with lower subjective motion sickness is mostly statistically indistinguishable from those with higher subjective sickness. Conclusively, those with even acute motion sickness may be just as affected as those with higher sickness, considering human performance. Building on these results, it could indicate motion sickness should be a consideration for understanding user ability to regain control of a self-driving vehicle, even if not feeling subjectively unwell. Effectiveness of subjective scoring is discussed and future research is proposed to help ensure the successful rollout of self-driving vehicles