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Automatic thermal control (ATC) was investigated for implementation into a spacesuit to provide thermal neutrality to the astronaut through a range of activity levels. Two different control concepts were evaluated and compared for their ability to maintain subject thermal comfort. Six test subjects, who were involved in a series of three tests, walked on a treadmill following specific metabolic profiles while wearing the Mark III spacesuit in ambient environmental conditions. Results show that individual subject comfort was effectively provided by both algorithms over a broad range of metabolic activity. ATC appears to be highly effective in providing efficient, “hands-off” thermal regulation requiring minimal instrumentation. Final selection of an algorithm to be implemented in an advanced spacesuit system will require testing in dynamic thermal environments and consideration of technology for advancement in instrumentation and controller performance.

In this paper, a reinforcement learning-based method is proposed to adapt autonomous vehicle passengers’ expectation of comfort through in-situ human-vehicle interaction. Ride comfort has a significant influence on the user’s experience and thus acceptance of autonomous vehicles. There is plenty of research about the motion planning and control of autonomous vehicles. However, limited studies have explicitly considered the comfort of passengers in autonomous vehicles. This paper studies the comfort of humans in autonomous vehicles longitudinal autonomous driving. The paper models and then improves passengers’ feelings about autonomous driving behaviors. This proposed approach builds a control and adaptation strategy based on reinforcement learning using human’s in-situ feedback on autonomous driving. It also proposes an adaptation of humans to autonomous vehicles to account for improper human driving expectations.

Passenger comfort is a critical factor in user acceptance of autonomous vehicles (AVs). Despite existing methods for passenger comfort assessment, new approaches to assessing passenger comfort in AVs may be valuable to the automotive industry. In this paper, continuous pressing-based and discrete smartphone-based approaches for comfort assessment were designed and implemented in a user study. Participants used the two approaches to evaluate their comfort levels in an experimental study based on a high-fidelity autonomous driving simulator. Performances of the two approaches in assessing comfort levels were analyzed and compared. In general, the discrete approach showed better measurement repeatability and lower measurement bias than the continuous approach. The performance gap of the continuous approach could be reduced with proper post-processing measures. Discussions on the potential uses of the approaches were also raised.

A transient model of the Minimum Consumables Portable Life Support System (MPLSS) Advanced Space Suit design has been developed and implemented using MAT-LAB/Simulink. The purpose of the model is to help with sizing and evaluation of the MPLSS design and aid development of an automatic thermal comfort control strategy. The MPLSS model is described, a basic thermal comfort control strategy implemented, and the thermal characteristics of the MPLSS Advanced Space Suit are investigated.

The International Space Station Waste Collector Subsystem Risk Mitigation Experiment (ISS WCS RME) was flown as the primary (Shuttle) WCS on Space Shuttle flight STS-104 (ISS-7A) in July 2001, to validate new design enhancements. In general, the WCS is utilized for collecting, storing, and compacting fecal & associated personal hygiene waste, in a zero gravity environment. In addition, the WCS collects and transfers urine to the Shuttle waste storage tank. All functions are executed while controlling odors and providing crew comfort. The ISS WCS previously flew on three Shuttle flights as the Extended Duration Orbiter (EDO) WCS, as it was originally designed to support extended duration Space Shuttle flights up to 30 days in length. Soon after its third flight, the Space Shuttle Program decided to no longer require 30 day extended mission duration capability and provided the EDO WCS to the ISS Program.

Phase II of the Lunar-Mars Life Support Test Project was conducted in June and July of 1996 at the NASA Johnson Space Center. The primary objective for Phase II was to develop and test an integrated human life support system capable of sustaining a crew of four for 30 days in a closed chamber. The crew was continuously present inside a chamber throughout the 30-day test. The objective of this paper is to describe crew interactions and human factors for the test. Crew preparations for the test included training and familiarization of chamber systems and accommodations, and medical and psychological evaluations. During the test, crew members provided metabolic loads for the life support systems, performed maintenance on chamber systems, and evaluated human factors inside the chamber. Overall, the four crew members found the chamber to be comfortable for the 30-day test.

Automatic thermal comfort control for the minimum consumables PLSS is undertaken using several control approaches. Accuracy and performance of the strategies using feedforward, feedback, and gain scheduling are evaluated through simulation, highlighting their advantages and limitations. Implementation issues, consumable usage, and the provision for the extension of these control strategies to the cryogenic PLSS are addressed.

The subjective aspects of comfort in three different cooling garments, the MACS-Delphi, Russian Orlan, and LCVG were evaluated. Six subjects (4 males and 2 females) were tested in separate sessions in each garment and in one of two environmental chamber conditions: 24°C and 35°C. Subjects followed a staged exercise/rest protocol with different levels of physical exertion at different stages. Thermal comfort and heat perception were assessed by ratings on visual analog scales. Ratings of physical comfort of the garment and also garment flexibility in positions simulating movements during planetary exploration were also obtained. The findings indicated that both overall thermal comfort and head thermal comfort were rated highest in the MACS-Delphi at 24°C. The Orlan was rated lowest on physical comfort and less flexible in different body positions.

Autonomous driving technologies can provide better safety, comfort and efficiency for future transportation systems. Most research in this area has mainly been focused on developing sensing and control approaches to achieve various autonomous driving functions. Very little of this research, however, has studied how to efficiently handle sensing exceptions. A simple exception measured by any of the sensors may lead to failures in autonomous driving functions. The autonomous vehicles are then supposed to be sent back to manufacturers for repair, which takes both time and money. This paper introduces an efficient approach to make human drivers able to online teach autonomous vehicles to drive under sensing exceptions. A human-vehicle teaching-and-learning framework for autonomous driving is proposed and the human teaching and vehicle learning processes for handling sensing exceptions in autonomous vehicles are designed in detail.

The most recent goal of our research program was to identify the optimal features of each of three garments to maintain core temperature and comfort under intensive physical exertion. Four males and 2 females between the ages of 22 and 46 participated in this study. The garments evaluated were the MACS-Delphi, Russian Orlan, and NASA LCVG. Subjects were tested on different days in 2 different environmental chamber temperature/humidity conditions (24°C/H∼28%; 35°C/H∼20%). Each session consisted of stages of treadmill walking/running (250W to 700W at different stages) and rest. In general, the findings showed few consistent differences among the garments. The MACS-Delphi was better able to maintain subjects within a skin and core temperature comfort zone than was evident in the other garments as indicated by a lesser fluctuation in temperatures across physical exertion levels.

An Advanced Automotive Manikin (ADAM), is used to evaluate liquid cooling garments (LCG) for advanced space suits for extravehicular applications and launch and entry suits. The manikin is controlled by a finite-element physiological model of the human thermoregulatory system. ADAM's thermal response to a baseline LCG was measured.The local effectiveness of the LCG was determined. These new thermal comfort tools permit detailed, repeatable measurements and evaluation of LCGs. Results can extend to other personal protective clothing including HAZMAT suits, nuclear/biological/ chemical protective suits, fire protection suits, etc.

Autonomous vehicles have the potential to transform lives by providing transportation to a wider range of users. However, with this new method of transportation, user acceptance and comfort are critical for widespread adoption. This exploratory study aims to investigate what makes passengers uncomfortable in existing vehicles to inform the design of future autonomous vehicles. In order to predict what may impact user acceptance for a diverse rider population for future autonomous vehicles, it is important to understand what makes a broad range of passengers uncomfortable today. In this study, interviews were conducted for a total of 75 participants from three diverse groups, including 20 automotive engineering graduate students who are building an autonomous concept vehicle, 21 non-technical adults, and 34 senior citizens. The results revealed both topics which made different groups of passengers uncomfortable as well as how these varied between the groups.