The Influence of Sociodemographic and Technology-Associated Factors on Stress from Human Interaction with Electric Vehicle Information Systems

The purpose of this study is to examine the influence of technology-associated and sociodemographic factors on perceived stress resulting from human interaction with electric vehicle information systems. Referring to the transactional stress model of Lazarus and Folkman (1984), we propose a research model to determine the impact of technical affinity, familiarity with electric vehicles, experience with electric vehicle information systems, age, gender, and education on perceived electric vehicle information systems-related stress. We tested our conceptual model using data from a web-based questionnaire, incorporating responses from 225 participants. Using partial least squares structural equation modeling (PLS-SEM), our results demonstrate that the associations between perceived electric vehicle information systems-related stress and affinity for technology, experience with electric vehicle information systems, and education are negative and significant, while that with age is positive and significant

Towards an electric bike level of service

The fast-growing market of electric bikes (e-bikes) has introduced a paradigm shift in mobility with a promise to enhance the sustainability agenda. An in-depth understanding of transport quality of service (QOS) from the e-bike rider’s perspective is a promising approach to sustain the role of the e-bike in mobility. Level of service (LOS) is a method by which to quantify QOS for different transport modes. However, to date, the knowledge on e-bike LOS (ELOS) lags far behind that on other transport modes. Therefore, the central aim of this thesis is to provide fundamental knowledge related to the development of ELOS. To address the main aim of the thesis, the travel behaviour and riding characteristics associated with e-bikes were scrutinised. Both qualitative and quantitative methods were employed to provide knowledge on the travel behaviour (strategical level) and riding characteristics (tactical level) related to e-bikes. From a strategic perspective, an extensive review of the literature was conducted to explore which transport mode LOS is applicable for developing ELOS. Based on the findings from the state of the art and the reviewed literature, bike LOS (BLOS) was deemed substantial for the development of ELOS. Thus, to move towards the development of ELOS, a set of studies was conducted to understand the comfort concerns of e-bike riders via the literature review, interviews and a field experiment. Based on the reviewed literature, it appears evident that research related to the travel behaviour of e-bike users is sparse and that the scale of e-bike substitution for other modes of transport is unclear. The findings of the aforementioned study led to the proposition of a preliminary theoretical framework for the development of ELOS and served as a roadmap for conducting the studies that followed. To provide a deeper understanding of the travel behaviour related to e-bikes, a qualitative study was conducted to explore e-bike users’ (riders) and nonusers’ comfort concerns. This study was extended to include the comfort and health concerns of e-bike users and nonusers in the unprecedented COVID-19 pandemic situation. The findings of this study provided a set of e-bike riding comfort variables, such as infrastructure facilities and e-bike performance in both pre- and peri-pandemic situations. This study also documented the potential effect of e-bike substitution for other transport modes such as public transport and cars. From a tactical level of analysis, there was a lack of studies to facilitate understanding the riding characteristics associated with e-bikes, specifically where vulnerable road users are involved. To address this knowledge gap, the interaction between e-bike users and pedestrians was studied in an off-road facility experiment. The study was designed to evaluate whether the traffic characteristics of passing (same-direction) and meeting (opposite-direction) encounters impose different difficulties for the navigation of the e-bike rider in pedestrian crowds. The results suggested that passing events cause the e-bike rider more hindrance compared to meeting events. This study was further extended to investigate the sociodemographic characteristics of e-bike riders along with their characteristics of riding in traffic and eventually model e-bike riders’ comfort in pedestrian crowds. In sum, this thesis addresses the knowledge gaps related to e-bike comfort concerns based on different study setups, which can be used substantially for developing ELOS. Along with exploring e-bike riders’ comfort concerns, the thesis puts forward information related to e-bike nonusers in both pre- and peri-pandemic situations. The findings of the thesis are applicable for planners and policy-makers when integrating the role of e-bikes in mobility policies. At a general level, the findings of the studies presented in this thesis pave the way for developing future ELOS and highlight the dire need to develop the concept of ELOS based on different contexts. All in all, the thesis opens new avenues into the field of e-bike comfort modelling by rendering the importance of the subject as an independent mode of transport

Less is Sometimes More – The Impact of In-Vehicle Information Systems on Perceived Range Stress

Recent research has emphasized a new dimension of driver stress, the concern of getting stranded with an electric vehicle due to a depleted battery, referred to as range stress. One promising solution is seen in the appropriate provision of relevant information through in-vehicle information systems. We aim to investigate how individuals perceive the interaction of these systems with a particular focus on range stress. Thus, we employed an experimental research design in real traffic situations consisting of 70 participants. We put participants in a critical range situation and showed that the provision of volatile and too much range-related information leads to increased range stress perception, and hence, negatively affects the willingness to use electric vehicles. This research contributes to the existing body of knowledge, as it points to the importance of accounting for potential dysfunctional consequences of increased use of information systems

Too Much of a Good Thing? An Experimental Investigation of the Impact of Digital Technology-enabled Business Models on Individual Stress and Future Adoption of Sustainable Services

The pervasive diffusion of digital technologies affords the development of innovative and sustainable business models. With increased connectivity, options arise for enabling sharing-based services with pay-per-use pricing. Besides the merits that these services gather, e.g., concerning sustainability, flexibility and economics, less is known about the potential adverse impacts on individuals. Thus, we employed an experimental research design to examine how digital technology-enabled business models affect individual stress and perception concerning the future usage of these services. Specifically, we investigated the context of car sharing, a service that has recently been advanced by the use of digital technologies and received increasing adoption rates. The empirical results indicate that digital technology-enabled business model designs significantly influence psychological stress in an unfavorable manner, and hence, negatively affect the willingness to use car sharing. Thus, our investigation points to the importance of accounting for potential dysfunctional societal effects of information systems in sustainability transformation

The impact of tecnhology in distribution

Nowadays we are facing a digital era submerse in technology. Information technology is embracing every industry, causing significant impacts and leading to considerable adaptations. The distribution industry is no exception. This study aims to collect evidence supporting that distribution channels are still not benefiting from information technologies full potential. Furthermore, this investigation proposed to understand and analyse the factors that can influence customer mind-set towards technology, either positively or negatively, helping to predict technology acceptance and use more accurately. Moreover, in order to contextualize the impact of technology in distribution, this investigation approached a specific technological innovation, the autonomous vehicles, who promise to revolutionise distribution, particularly in terms of mobility. This dissertation intends to analyse autonomous vehicles growth and predict their impact in a global perspective and objectively in the distribution industry. In this regard, an online survey was conducted, allowing the collection of most up-to-date information about distribution channels, in terms of efficiency and potentialities, in addition to collecting updated data regarding autonomous vehicles beneficial value, as well as, the drawbacks and concerns influencing the acceptance and use of this innovative technology. Thus, it is conclusive that there is clearly a room for improving the current distribution channels, concretely in terms of technological improvements. Autonomous vehicles promise to be a key disruptive technology, however, they will take time to be implemented, as this technology is still being developed. Although, as soon as it reaches its full potential, it is expected that autonomous vehicles face a sudden massive adoption.Atualmente, estamos a enfrentar uma era digital submersa em tecnologia. A tecnologia da informação está inserida em várias indústrias, causando impactos significativos e levando a adaptações consideráveis. O setor da distribuição não é exceção. Este estudo tem como objetivo recolher evidências que sustentem que os canais de distribuição ainda não estão a beneficiar o potencial das tecnologias da informação. Esta investigação pretende analisar os fatores que podem influenciar a mentalidade do cliente em relação à tecnologia, positiva ou negativamente, ajudando a prever a aceitação e utilização da tecnologia com mais precisão. De forma a contextualizar o impacto da tecnologia na distribuição, esta investigação abordou uma inovação tecnológica específica, os veículos autónomos, que prometem revolucionar a distribuição, principalmente em termos de mobilidade. Esta dissertação pretende analisar o crescimento dos veículos autónomos e prever o impacto dos mesmos, numa perspetiva global e especificamente no setor da distribuição. Nesse sentido, foi realizada um inquérito on-line, permitindo recolher informações atualizadas sobre os atuais canais de distribuição, em termos de eficiência e potencialidades, recolhendo ainda dados sobre os benefícios trazidos pelos veículos autónomos, bem como as desvantagens e preocupações que influenciam a aceitação e o uso desta tecnologia inovadora. Assim, é conclusivo que existe um espaço para melhorar os atuais canais de distribuição, concretamente em termos de melhorias tecnológicas. Os veículos autónomos prometem ser uma tecnologia disruptiva, no entanto necessitam de tempo para serem implementados, uma vez que a tecnologia ainda está em desenvolvimento. Assim que atinjam todo o seu potencial, é esperado que os veículos autónomos enfrentem uma adoção repentina e massificada

The Effects of Active Luminous Road Markings Solutions on Simulated Driving Performance: an Experimental Study

openDriving at night or in hazardous weather could be risky if artificial lighting is inadequate or insufficient, especially when engaging curves. Innovative solutions, like Active Luminous Road Markings (ALRMs), might assist drivers and improve road safety. However, international road regulations lack consistent guidelines for ALRMs’ lighting colors and designs. We assessed different ALRMs solutions on 27 young adult drivers negotiating curves in simulated scenarios. We manipulated ALRMs appearance (color: green, red, and unlit), size (width: conventional and wide), and road geometry (curve direction: left and right and radius: 120m and 440m). After the driving simulation, participants completed a video-based perception task rating their perceived levels of risk, speed estimation, valence and arousal. The lateral position was significantly affected by ALRMs features, resulting in changes in the driving trajectory toward the right side of the vehicle’s lane in response to color, width, and curve radius. Green ALRMs showed higher variability for vehicle position, indicating reduced vehicle control. Curve radii also affected driving behavior, with narrower curves leading to reduced speeds. Subjective measures revealed that green ALRMs were perceived as brighter but less comfortable. Furthermore, curve radius significantly influenced arousal and speed estimates, with narrower curves eliciting lower activation and slower speed perception. Our study might offer valuable information that transportation engineers, road designers, and transportation psychologists can use to implement smart road technologies and improve road safety when designing new traffic lighting solutions

Evaluating Impacts of Shared E-scooters from the Lens of Sustainable Transportation

As the popularity of shared micromobility is increasing worldwide, city governments are struggling to regulate and manage these innovative travel technologies that have several benefits, including increasing accessibility, reducing emissions, and providing affordable travel options. This dissertation evaluates the impacts of shared micromobility from the perspective of sustainable transportation to provide recommendations to decision-makers, planners, and engineers for improving these emerging travel technologies. The dissertation focuses on four core aspects of shared micromobility as follows: 1) Safety: I evaluated police crash reports of motor vehicle involving e-scooter and bicycle crashes using the most recent PBCAT crash typology to provide a comprehensive picture of demographics of riders crashing and crash characteristics, as well as mechanism of crash and crash risk, 2) Economics: I estimated the demand elasticity of e-scooters deployed, segmented by weekday type, land use, category of service providers based on fleet size using negative binomial fixed effect regression model and K-means clustering, 3) Expanding micromobility to emerging economies: Using dynamic stated preference pivoting survey and panel data mixed logit model, I assessed the intentions to adopt shared micromobility in mid-sized cities of developing countries, where these innovative technology could be the first wave of decarbonizing transportation sector, and 4) Micromobility data application: I identified five usage-clusters of shared e-scooter trips using combination of Principal Component Analysis (PCA) and K-means clustering to propose a novel framework for using micromobility data to inform data-driven decision on broader policy goals. Based on the key findings of the research, I provide five recommendations as follows: 1) decision-makers should be proactive in incorporating new travel technologies like shared micromobility, 2) city governments should leverage shared micromobility usage and operation data to empower the decision-making process, 3) each shared micromobility vehicles should be approached uniquely for improving road safety, 4) city governments should consider regulating the number of service providers and their fleet sizes, and 5) decision-makers should prioritize expanding shared micromobility in emerging economies as one of the first efforts to the decarbonizing transportation sector

Assessing the Effect of Drivers' Gender on Their Intention to Use Fully Automated Vehicles

Although fully automated vehicles (SAE level 5) are expected to acquire a major relevance for transportation dynamics by the next few years, the number of studies addressing their perceived benefits from the perspective of human factors remains substantially limited. This study aimed, firstly, to assess the relationships among drivers' demographic factors, their assessment of five key features of automated vehicles (i.e., increased connectivity, reduced driving demands, fuel and trip-related efficiency, and safety improvements), and their intention to use them, and secondly, to test the predictive role of the feature' valuations over usage intention, focusing on gender as a key differentiating factor. For this cross-sectional research, the data gathered from a sample of 856 licensed drivers (49.4% females, 50.6% males; M = 40.05 years), responding to an electronic survey, was analyzed. Demographic, driving-related data, and attitudinal factors were comparatively analyzed through robust tests and a bias-corrected Multi-Group Structural Equation Modeling (MGSEM) approach. Findings from this work suggest that drivers' assessment of these AV features keep a significant set of multivariate relationships to their usage intention in the future. Additionally, and even though there are some few structural similarities, drivers' intention to use an AV can be differentially explained according to their gender. So far, this research constitutes a first approximation to the intention of using AVs from a MGSEM gender-based approach, being these results of potential interest for researchers and practitioners from different fields, including automotive design, transport planning and road safety

Using body sensors for evaluating the impact of smart cycling technologies on cycling experiences:a systematic literature review and conceptual framework

Digital technologies in, on, and around bicycles and cyclists are gaining ground. Collectively called Smart Cycling Technologies (SCTs), it is important to evaluate their impact on subjective cycling experiences. Future evaluations can inform the design of SCTs, which in turn can help to realize the abundant benefits of cycling. Wearable body sensors and advanced driver assistance systems are increasingly studied in other domains, however evaluation methods integrating such sensors and systems in the field of cycling research were under-reviewed and under-conceptualized. This paper therefore presents a systematic literature review and conceptual framework to support the use of body sensors in evaluations of the impact of SCTs on perceptions, emotions, feelings, affect, and more, during outdoor bicycle rides. The literature review (n = 40) showed that there is scarce research on this specific use of body sensors. Moreover, existing research designs are typically not tailored to determine impact of SCTs on cycling experience at large scale. Most studies had small sample sizes and explored limited sensors in chest belts and wristbands for evaluating stress response. The evaluation framework helps to overcome these limitations, by synthesizing crucial factors and methods for future evaluations in four categories: (1) experiences with SCTs, (2) experience measurements, (3) causal analysis, (4) confounding variables. The framework also identifies which types of sensors fit well to which types of experiences and SCTs. The seven directions for future research include, for example, experiences of psychological flow, sensors in e-textiles, and cycling with biofeedback. Future interactions between cyclists and SCTs will likely resemble a collaboration between humans and artificial intelligence. Altogether, this paper helps to understand if future support systems for cyclists truly make cycling safer and more attractive