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| Author | : Siobhán E Merriman |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2024-04-30 |
| Genre | : Business & Economics |
| ISBN | : 9781032510903 |
Driver Training for Automated Vehicles identifies the training requirements for drivers of AVs and takes a systematic approach to design, develop, implement and evaluate a comprehensive training package to address these requirements.
| Author | : Siobhán E. Merriman |
| Publisher | : CRC Press |
| Total Pages | : 278 |
| Release | : 2024-04-30 |
| Genre | : Technology & Engineering |
| ISBN | : 104001481X |
Since the introduction of Automated Vehicles (AVs) on roads, there have been a number of high-profile collisions, which have highlighted significant driver challenges. These include challenges associated with drivers’ trust in the automation, their knowledge and awareness of the AV’s capabilities and limitations and their reduced situation awareness of the road environment and the vehicle. Solutions are needed to overcome these challenges, so that the expected benefits of AVs can be realised. Driver Training for Automated Vehicles: A Systems Approach identifies the training requirements for drivers of AVs and takes a systematic approach to design, develop, implement and evaluate a comprehensive training package to address these requirements. This book explores how training can overcome the driver challenges associated with AVs by improving drivers’ mental models, trust in automation, decisions and behaviour when activating a Level 4 AV. It presents a systematic approach to the training lifecycle, by first presenting the current state of research into AVs, identifying the challenges and training requirements for drivers of AVs, and then developing and evaluating a training programme to achieve these requirements. This fascinating title highlights the need for drivers to undergo training for AVs, and takes us a step closer to this need. It walks readers through a systematic, four-step process and provides practical guidance to develop and evaluate an effective training programme. The reader will develop a thorough understanding of the current driver challenges with AVs and the methods and systems to mitigate them through current knowledge and research. This book is an ideal read for practitioners, designers and academics with a professional or research interest in AVs. Its appeal extends to those in the fields of automotive design, Systems Engineering, Human Factors and education and training.
| Author | : Daniel Watzenig |
| Publisher | : Springer |
| Total Pages | : 619 |
| Release | : 2016-09-23 |
| Genre | : Technology & Engineering |
| ISBN | : 3319318950 |
The main topics of this book include advanced control, cognitive data processing, high performance computing, functional safety, and comprehensive validation. These topics are seen as technological bricks to drive forward automated driving. The current state of the art of automated vehicle research, development and innovation is given. The book also addresses industry-driven roadmaps for major new technology advances as well as collaborative European initiatives supporting the evolvement of automated driving. Various examples highlight the state of development of automated driving as well as the way forward. The book will be of interest to academics and researchers within engineering, graduate students, automotive engineers at OEMs and suppliers, ICT and software engineers, managers, and other decision-makers.
| Author | : Michael P. Manser |
| Publisher | : |
| Total Pages | : 37 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
| Author | : David Michael Stavens |
| Publisher | : Stanford University |
| Total Pages | : 104 |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
Every year, 1.2 million people die in automobile accidents and up to 50 million are injured. Many of these deaths are due to driver error and other preventable causes. Autonomous or highly aware cars have the potential to positively impact tens of millions of people. Building an autonomous car is not easy. Although the absolute number of traffic fatalities is tragically large, the failure rate of human driving is actually very small. A human driver makes a fatal mistake once in about 88 million miles. As a co-founding member of the Stanford Racing Team, we have built several relevant prototypes of autonomous cars. These include Stanley, the winner of the 2005 DARPA Grand Challenge and Junior, the car that took second place in the 2007 Urban Challenge. These prototypes demonstrate that autonomous vehicles can be successful in challenging environments. Nevertheless, reliable, cost-effective perception under uncertainty is a major challenge to the deployment of robotic cars in practice. This dissertation presents selected perception technologies for autonomous driving in the context of Stanford's autonomous cars. We consider speed selection in response to terrain conditions, smooth road finding, improved visual feature optimization, and cost effective car detection. Our work does not rely on manual engineering or even supervised machine learning. Rather, the car learns on its own, training itself without human teaching or labeling. We show this "self-supervised" learning often meets or exceeds traditional methods. Furthermore, we feel self-supervised learning is the only approach with the potential to provide the very low failure rates necessary to improve on human driving performance.
| Author | : Laura Fraade-Blanar |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2018 |
| Genre | : Technology & Engineering |
| ISBN | : 9781977401649 |
This report presents a framework for measuring safety in automated vehicles (AVs): how to define safety for AVs, how to measure safety for AVs, and how to communicate what is learned or understood about AVs.
| Author | : Alexander Eriksson |
| Publisher | : CRC Press |
| Total Pages | : 158 |
| Release | : 2018-07-04 |
| Genre | : Computers |
| ISBN | : 1351207504 |
Driver Reactions to Automated Vehicles focuses on the design and evaluation of the handover to and from driver and the automobile. The authors present evidence from studies in driving simulators and on the open roads to show that handover times are much longer than anticipated by previous research. In the course of the studies, Eriksson and Stanton develop compelling evidence to support the use of driving simulators for the study of handovers. They also develop guidelines for the design of handover strategies and show how this improves driver takeover of vehicle control. Features Provides a history of automobile automation Offers a contemporary analysis of the state of automobile automation Includes novel approaches in examining driver-automation interaction Presents studies of automation in driving simulators Includes on-road studies of driver automation Covers guidelines for design of vehicle automation
| Author | : Srinath Sibi |
| Publisher | : |
| Total Pages | : |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
While human drivers are currently responsible for almost all of the transport of goods and people, autonomous vehicles are near-at-hand and are expected to replace human drivers in the next few decades. Several vehicle manufacturing and tech companies have begun testing their autonomous vehicles on public roads. During this period of testing, human drivers are employed to ensure the safety of the passengers and those in the immediate vicinity in the event of a failure of automation. Moreover, lower levels of automation, that are currently available to the general public, also require constant human supervision to ensure safety. This makes the study of the cognitive, behavioral and psycho-physiological state of drivers of automation crucial. In this thesis, I review existing literature on the study of driver state and behavior and on the methodologies employed by researchers to study them. I present a series of studies that investigate the changes in driver state while using automated vehicles. To this end, I employed various physio- logical sensors such as near-infrared spectroscopy, galvanic skin response, and electrocardiography. I argue the case for driver state monitoring in automated vehicles to ensure vigilance and driver availability for a take over of control. The first study I present investigates the reasons for the presence of sleepy and drowsy behavior in drivers of automated vehicles. I found that the reason for drowsy behavior was prolonged intervals of low cortical activity. The second and third study investigate the changes in cortical activity across different levels of automation and over time. These studies showed that drivers who used partially automated vehicles had the highest levels of cognitive activity and drivers of partial and fully automated vehicles showing significant decreases in cortical activity over time. In the last study, I employ a panel design to investigate the impact of prior and knowledge and training on driver preparedness and behavior. I found that drivers are prepared when they are trained on the possible failure modes of automation. However, this preparedness decreases over time in both drivers with and without any training. These studies add to the existing knowledge of driver state investigations while providing much needed insight into the longitudinal changes in driver state. It is my hope that this thesis provides the foundation for future investigations into training programs for safety drivers in autonomous vehicles and serve as guidance for developers of automated driving technology.
| Author | : Donald L. Fisher |
| Publisher | : CRC Press |
| Total Pages | : 548 |
| Release | : 2020-05-31 |
| Genre | : Computers |
| ISBN | : 1351979809 |
Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles Subject Guide: Ergonomics & Human Factors Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. It provides information about the human driver, other road users, and human–automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential. Features Addresses four major transportation challenges—crashes, congestion, carbon emissions, and accessibility—from a human factors perspective Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles Leverages lessons from other domains in understanding human interactions with automation Sets the stage for future research by defining the space of unexplored questions
| Author | : James M. Anderson |
| Publisher | : Rand Corporation |
| Total Pages | : 215 |
| Release | : 2014-01-10 |
| Genre | : Transportation |
| ISBN | : 0833084372 |
The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.
