Jyh-Hone Wang’s research while affiliated with University of Rhode Island and other places

While energy consumption in the United States residential sector has a complex relationship with users’ physical, demographic, and behavioral characteristics, academic research has recognized the role of social acceptance in the immediate and long-term use of renewable energy. This study sought to understand how users’ physical, demographic, socioeconomic, and behavioral characteristics impact their acceptance of renewable energy in the residential sector in the U.S. Specifically, this study tested the theory of planned behavior (TPB) research model and included the “willingness to pay” construct to predict consumers’ intentions to use renewable energy. Twenty-two states, which are responsible for over 20% of the total energy produced from renewable sources, were included in the study. The findings showed that the average household income in the residential sector has an important effect on consumers’ intentions to use renewable energy. Furthermore, the study’s results are consistent with the TPB structural equation model. In this case, the subjective norm (perceived behavioral control) and the willingness to pay construct significantly affected consumers’ intentions to use renewable energy, while attitudes toward the behavior did not. Limitations of the study and suggestions for future research are also discussed.

The increase in the number of older adult drivers in developed countries has raised safety concerns due to the decline in their sensory, motor, perceptual, and cognitive abilities which can limit their driving capabilities. Their driving safety could be enhanced by the use of modern Automated Driver Assistance Systems (ADASs) and might totally resolved by full driving automation. However, the acceptance of these technologies by older adult drivers is not yet well understood. Thus, this study investigated older adult drivers’ intention to use six ADASs and full driving automation through two questionnaires with 115 and 132 participants respectively in Rhode Island, USA. A four-dimensional model referred to as the USEA model was used for exploring older adult drivers’ technology acceptance. The USEA model included perceived usefulness, perceived safety, perceived ease of use, and perceived anxiety. Path Analysis was applied to evaluate the proposed model. The results of this study identified the important factors in older adult drivers’ intention to use ADASs and full driving automation, which could assist stakeholders in improving technologies for use by older drivers.

Driving is an essential activity in living a fulfilling lifestyle. Older adults, like the rest of the population, require a means of transportation to participate in important lifestyle choices; however, declines in their sensory, motor, perceptual, and cognitive abilities limit their driving capabilities. These limitations motivated this study to investigate older adult drivers' driving challenges by conducting a questionnaire. The in-vehicle technologies which mitigate these challenges were identified. In this study, the acceptance of the identified technologies is explored by conducting a second questionnaire. A four dimensional model which included perceived usefulness, perceived ease of use, perceived safety, and perceived anxiety is considered in the second questionnaire. In total, 250 older adult drivers participated in these questionnaires. The responses obtained from both questionnaires identified potential challenges that they were facing and whether they intend to use the identified in-vehicle technologies. Having more information about the acceptance of these technologies can help engineers better understand the factors that make technologies useful to older adult drivers, and thus improve their driving safety.

In an increasingly mobile era, the wide availability of technology for texting and the prevalence of hands-free form have introduced a new safety concern for drivers. To assess this concern, a questionnaire was first deployed online to gain an understanding of drivers’ text driving experiences as well as their demographic information. The results from 232 people revealed that the majority of drivers are aware of the associated risks with texting while driving. However, more than one-fourth of them still frequently send or read text messages while driving. In addition to the questionnaire, through the use of a virtual-reality driving simulator, this study examined drivers’ driving performance while they were engaged in some forms of text driving under different challenging traffic conditions. Through a blocked factorial experiment, drivers would either read a text message or respond to it with two levels of text complexity while using either hand-held or hands-free texting method. Their driving performance was assessed based on the number of driving violations observed in each scenario. Conclusions regarding the impacts of different forms of texting, text complexity, and response mode on drivers driving performance were drawn.

As a critical component in Intelligent Transportation Systems (ITS) of modern traffic management, dynamic message signs (DMS) are widely used in many countries as an effective means to provide motorists with up-to-date information regarding accidents, congestion, road conditions and travel time, etc. However, it was observed in traffic data that motorists tended to slow down when approaching active DMSs and speed up after passing these signs. The speed variations could pose safety hazards to other motorists on highways. To gain insights into this issue and understand associated causes and risks, a human factors study was conducted to help ease the speed variation when approaching DMSs. The effect of DMS messages on traffic approaching and passing the signs were assessed by analyzing highway traffic data near DMSs. A questionnaire survey was conducted to identify associated causes and risks. Participants were further surveyed about their preferences on DMS characteristics such as message category, message type, number of frames, message details, and the use of graphics. Individual drivers' responses to various DMS designs were evaluated through a simulation test. This study has provided updated knowledge regarding the effects of DMSs on highway traffic and has identified measures to improve the design and display of DMS messages to help ease the speed variation of approaching traffic.

A human factors study consisting of a vehicle headway analysis and a questionnaire survey was conducted in Rhode Island (RI) to investigate tailgating issues and possible means for tailgating treatment. Vehicle headways were collected from highway surveillance videos and serious tailgating issues were identified on RI highways. The results of the questionnaire survey further confirmed the observations made in the vehicle headway analysis that most RI drivers maintained insufficient vehicle headways on highways. Among a few tailgating treatments presented in the survey, most subjects preferred a system consisting of equally spaced, white horizontal bars marked on pavement and overhead graphic-aided dynamic message signs.

A human factors study was carried out to assess drivers' tailgating behavior and the effect of advisory signs in mitigating tailgating. Tailgating is a dangerous driving behavior and a leading cause of most rear-end crashes. Through a prior study, serious tailgating was identified on urban Rhode Island highways. It is critical to many urban traffic management authorities to understand tailgating and to explore means to mitigate drivers' tailgating behavior, especially on urban highways with high-speed and high-volume traffic. Properly designed advisory signs could reduce tailgating and related motor crashes. To assess drivers' behavior with regards to tailgating, a questionnaire survey was developed and given to a number of subjects with daily highway driving experience. The survey is designed to identify causes of tailgating and drivers' perceptions and engagements on tailgating behavior. Drivers' driving behaviors were further assessed through driving simulation under different traffic conditions. To help mitigate tailgating behavior, advisory signs and an educational video were developed. The effectiveness of these proposed counter-tailgating measures was assessed in the driving simulation. Subjects' real driving behaviors were further studied in a follow-up field study. Study results found that the majority had an incorrect sense regarding safe following distance and were tailgating while driving on highways. Heavy traffic was identified as the top tailgating cause. The simulation results confirmed the tailgating phenomenon observed on urban Rhode Island highways. The proposed advisory signs were found effective in mitigating tailgating behavior.

This paper addresses the variation problem in design for assembly (DFA) benefits in different products. It investigated 12 product cases that employed DFA methodology in their redesign and found that DFA benefits correlate with certain product assembly properties. It explored the correlation relationships using assembly factors consisting of clustered manual handling and insertion assembly elements. Two sets of correlation models for estimating potential DFA benefits were developed. An example is provided to illustrate the estimation procedure and its result.