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This paper presents the development of the Mobility Lab, an instrumented car that
was developed to support research on the comfort of automated driving. The Mobility Lab
was established as a platform to investigate the implications of motion sickness on
human users especially when exposed to low-frequency horizontal forces while engaging in
non-driving activities. First, the Mobility Lab's overview of interior setup and system
architecture involving data acquisition system with its sensors is described. Then, a
validation study is presented, comprising of simulations with forty-six participants by
two designated drivers. The simulations were focusing on the manipulation of lateral
acceleration based on defensive automated driving style settings. The consistency of the
manipulations in terms of accelerations, velocities, frequencies and motion sickness
dose values by both drivers was measured and compared. Subjective motion sickness
assessments, as well as user rating towards the believability of the Mobility Lab
platform, were also carried out. The results indicate good reliability in producing
consistent simulations of automated driving experience within the desired settings. In
addition, the versatility of Mobility Lab in term of flexibility on interior setup
arrangement and also its measurement system makes various automated driving related
experiments possible.

Objective: The current study investigated driver vigilance in partially automated vehicles to determine whether increased task demands reduce a driver's ability to monitor for automation failures and whether the vigilance decrement associated with hazard detections is due to driver overload. Background: Drivers of partially automated vehicles are expected to monitor for signs of automation failure. Previous research has shown that a driver's ability to perform this duty declines over time. One possible explanation for this vigilance decrement is that the extreme demands of vigilance causes overload and leads to depletion of limited attentional resources required for vigilance. Method: Participants completed a 40-min drive in a simulated partially automated vehicle and were tasked with monitoring for hazards that represented potential automation failures. Two factors were manipulated to test the impact of monitoring demands on performance: Spatial uncertainty and event rate. Results: As predicted, hazard detection performance was poorer when monitoring demands were increased, and performance declined as a function of time on task. Subjective reports also indicated high workload and task-induced stress. Conclusion: Drivers of partially automated vehicles are impaired by the vigilance decrement and elevated task demands, meaning that safe operation becomes less likely when the demands associated with monitoring automation increase and as a drive extends in duration. This study also supports the notion that vigilance performance in partially automated vehicles is likely due to driver overload. Application: Developers of automation technologies should consider countermeasures that attenuate a driver's cognitive load when tasked with monitoring automation.

Dynamic Inversion (DI) is a powerful nonlinear control technique which has been applied to several modern flight control systems. This research utilized concepts of DI in order to develop a controller to land an Unmanned Combat Aerial Vehicle (UCAV) on an aircraft carrier. The Joint Unmanned Combat Air System (J-UCAS) Equivalent Model was used as the test aircraft. An inner-loop DI controller was developed to control the pitch, roll, and yaw rate dynamics of the aircraft, while an outer-loop DI controller was developed to provide flight path commands to the inner-loop. The controller design and simulation were conducted in the MATLAB/Simulink environment. Simulations were conducted for various starting positions near the carrier and for varying wind, wind turbulence, and sea state conditions. In the absence of wind and sea state turbulence, the controller performed well. After adding wind and sea state turbulence, the controller performance was degraded. Future work in this area should include a more robust disturbance rejection technique to compensate for wind turbulence effects and a method of carrier motion prediction to compensate for sea state effects.

This article summarizes the makeup of AV legal regimes of Australia, China, France, Germany, Japan, and the United Kingdom, with a focus on law and policy relating to highly to fully automated vehicles.

Enlace de acceso: https://rdcu.be/b9awz ; How should automated vehicles (AVs) react in emergency circumstances? Most research projects and scientific literature deal with this question from a moral perspective. In particular, it is customary to treat emergencies involving AVs as instances of moral dilemmas and to use the trolley problem as a framework to address such alleged dilemmas. Some critics have pointed out some shortcomings of this strategy and have urged to focus on mundane traffic situations instead of trolley cases involving AVs. Besides, these authors rightly point out the political nature of the most interesting debates involving AVs. However, in our view, they do not offer an adequate account of the distinction between ethics and politics and still see their proposals as contributions to the ethics of AVs. We argue that many of the interesting questions about how AVs should behave, both in emergency and other situations, are of political, and not moral, nature. This view is based on a conception of politics and political normativity that we have developed elsewhere and that we call "political minimalism." Additionally, we show that this proposed perspective has significant consequences for the design, management, and regulation of transport systems.

Container terminals are constantly being challenged to adjust their throughput capacity to match fluctuating demand. Examining the optimization problems encountered in today's container terminals, Port Automation and Vehicle Scheduling: Advanced Algorithms for Scheduling Problems of AGVs, Third Edition provides advanced algorithms for handling the scheduling of Automated Guided Vehicles (AGVs) in ports. Building on the earlier editions, previously titled Vehicle Scheduling in Port Automation: Advanced Algorithms for Minimum Cost Flow Problems, this book has undergone extensive revisions and includes two new chapters. New material addresses the solutions to the modeling of decisions in Chapter 3, while in Chapter 11 the authors address an emerging challenge in automated container terminals with integrated management. Key Features: Classifies the optimization problems of the ports into five scheduling decisions. For each decision, it supplies an overview, formulates each of the decisions as constraint satisfaction and optimization problems, and then covers possible solutions, implementation, and performance. Explores in Part One of the book the various optimization problems in modern container terminals, while details in Part Two advanced algorithms for the minimum cost flow (MCF) problem and for the scheduling problem of AGVs in ports. Offers complete package that can help readers address the scheduling problems of AGVs in ports. This is a valuable reference for port authorities and researchers, including specialists and graduate students in operation research. For specialists, it provides novel and efficient algorithms for network flow problems. For students, it supplies the most comprehensive survey of the field along with a rigorous formulation of the problems in port automation.

Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgements -- Editors -- Contributors -- Abbreviations -- Part I: Modelling -- Chapter 1 UCEID - The Best of Both Worlds: Combining Ecological Interface Design with User-Centred Design in a Novel Human Factors Method Applied to Automated Driving -- 1.1 Introduction -- 1.1.1 Why Use UCEID? -- 1.2 The UCEID Method -- 1.2.1 Literature Review -- 1.2.2 Data Collection -- 1.2.3 Thematic Analysis -- 1.2.4 Cognitive Work Analysis -- 1.2.5 Consolidation and Ideas Generation -- 1.2.6 Filtering and Checking -- 1.3 Methodological Considerations -- 1.3.1 Advantages -- 1.3.2 Disadvantages -- 1.3.3 Training and Application Time -- 1.3.4 Tools -- 1.4 Summary -- Acknowledgements -- References -- Chapter 2 Using UCEID to Include the Excluded: An Autonomous Vehicle HMI Inclusive Design Case Study -- 2.1 Introduction -- 2.1.1 This Case Study: Designing an HMI for Level 3/ 4 Autonomous Car Takeover -- 2.1.1.1 Ageing Population -- 2.1.1.2 Ageing and Capability Impairment -- 2.1.1.3 Ageing and Digital Technological Interface Capability -- 2.1.1.4 Inclusive Design -- 2.2 Approach and Activities -- 2.2.1 Overview of Explore and Evaluate Stage -- 2.2.2 Evaluate Activity: Generation and Processing of Requirements - Method -- 2.2.3 Evaluate Activity: Generation and Processing of Needs Lists - Results -- 2.2.4 Create Activity: Design Workshop 1 -- 2.2.4.1 Input -- 2.2.4.2 Activity -- 2.2.4.3 Results -- 2.2.5 Create Activity: Iterative Design Development -- 2.2.6 Evaluate Activity: Testing with Experts and Users - Overview -- 2.2.7 Create Activity: Design Workshop 2 -- 2.2.7.1 Input -- 2.2.7.2 Outputs -- 2.2.8 Create Activity: Final Concepts and Refinement -- 2.3 Discussion and Conclusions -- Acknowledgements -- References.

Objective: The aim of this study was to review existing research into driver control transitions and to determine the time it takes drivers to resume control from a highly automated vehicle in noncritical scenarios. Background: Contemporary research has moved from an inclusive design approach to adhering only to mean/median values when designing control transitions in automated driving. Research into control transitions in highly automated driving has focused on urgent scenarios where drivers are given a relatively short time span to respond to a request to resume manual control. We found a paucity in research into more frequent scenarios for control transitions, such as planned exits from highway systems. Method: Twenty-six drivers drove two scenarios with an automated driving feature activated. Drivers were asked to read a newspaper, or to monitor the system, and to relinquish, or resume, control from the automation when prompted by vehicle systems. Results: Significantly longer control transition times were found between driving with and without secondary tasks. Control transition times were substantially longer than those reported in the peer-reviewed literature. Conclusion: We found that drivers take longer to resume control when under no time pressure compared with that reported in the literature. Moreover, we found that drivers occupied by a secondary task exhibit larger variance and slower responses to requests to resume control. Workload scores implied optimal workload. Application: Intra- and interindividual differences need to be accommodated by vehicle manufacturers and policy makers alike to ensure inclusive design of contemporary systems and safety during control transitions.

Objective This paper investigates driver engagement with vehicle automation and the transition to manual control in the context of a phenomenon that we have termed vicarious steering—drivers steering when the vehicle is under automated control. Background Automated vehicles introduce many challenges, including disengagement from the driving task and out-of-the-loop performance decrement. We examine drivers' steering behavior when the automation is engaged, and steering input has no effect on the vehicle state. Such vicarious steering is a potential indicator of engagement for evaluating automated vehicles. Method A total of 32 female and 32 male drivers between 25 and 55 years of age participated in this experiment. A 2 × 2 between-subject design combined control algorithms and instructed responsibility. The control algorithms (lane centering and adaptive) were intended to convey the capability of the automation. The adaptive algorithm drifted across the lane center when latent hazards were present. The instructed levels of responsibility (driver primarily responsible and automation primarily responsible) were intended to replicate the admonitions of owners' manuals. Results The adaptive algorithm increased vicarious steering ( p < .001), but instructed responsibility did not ( p = .67), and there was no interaction between the algorithm and the responsibility ( p = .75). Vicarious steering was associated with an increase in transitions to manual control and glances to the road but was negatively associated with driving performance immediately after the transition to manual control. Conclusion Vicarious steering is a promising indicator of driver engagement when the vehicle is under automated control and automation algorithms can promote engagement.

Objective: The primary aim of the current study was to determine whether monitoring the roadway for hazards during automated driving results in a vigilance decrement. Background: Although automated vehicles are relatively novel, the nature of human-automation interaction within them has the classic hallmarks of a vigilance task. Drivers must maintain attention for prolonged periods of time to detect and respond to rare and unpredictable events, for example, roadway hazards that automation may be ill equipped to detect. Given the similarity with traditional vigilance tasks, we predicted that drivers of a simulated automated vehicle would demonstrate a vigilance decrement in hazard detection performance. Method: Participants "drove" a simulated automated vehicle for 40 minutes. During that time, their task was to monitor the roadway for roadway hazards. Results: As predicted, hazard detection rate declined precipitously, and reaction times slowed as the drive progressed. Further, subjective ratings of workload and task-related stress indicated that sustained monitoring is demanding and distressing and it is a challenge to maintain task engagement. Conclusion: Monitoring the roadway for potential hazards during automated driving results in workload, stress, and performance decrements similar to those observed in traditional vigilance tasks. Application: To the degree that vigilance is required of automated vehicle drivers, performance errors and associated safety risks are likely to occur as a function of time on task. Vigilance should be a focal safety concern in the development of vehicle automation.