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Tuktuk, as a generalized connotation, serves as a widely used vehicle for urban transportation, adapted from Thailand by the Philippines. The creation of the electric-typed public vehicle has now been recognized as one of the modalities of public transportations, the etuktuk. This study investigated the factors influencing passengers' intention to use etuktuks as a mode of transportation in the Philippines by integrating the Theory of Planned Behavior with higher-order SERVQUAL dimensions. The objective was to understand how service qualities, attitudes, subjective norms, and perceived behavioral control impact passenger satisfaction and intention to use etuktuks. Data were collected from 501 respondents who had used etuktuks and were analyzed using partial least square structural equation modeling. The findings revealed that assurance, empathy, reliability, tangibility, and responsiveness significantly affected passenger satisfaction and intentions, with assurance being the most influential factor. Conversely, tangibles, such as the physical attributes of the etuktuk, were the least significant in shaping passenger preferences. Notably, a negative significant effect was observed between service quality and behavioral intention, indicating that while passengers are generally satisfied with etuktuk services, they may opt for alternative transportation options when available. These results highlight the need for improvements in etuktuk services, particularly in enhancing comfort, safety, and accessibility. Such improvements are crucial for encouraging wider adoption of etuktuks and fostering cleaner, more sustainable urban environments. By addressing the identified service quality issues and leveraging the research findings, stakeholders can better support the transition to more environmentally friendly and efficient transportation options. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to develop a readiness index model that can serve as an analytical tool for exploring the achievements of the electrification of transportation systems. We have applied this readiness index model to evaluate the readiness positioning of China, Norway, and Sweden towards transportation electrification. We have chosen these three countries as they represent diversity among countries adopting electric transportation system solutions. Our developed readiness index model has four key dimensions: technological readiness, political readiness, societal readiness, and economic readiness. The embeddedness of all four dimensions in one model provides a multi-perspective way of analyzing and evaluating the readiness levels of countries moving towards transforming their transportation system. Therefore, we named the model a "multidimensional readiness index". Our main conclusions are that political processes and decisiveness are the most important factors, followed by societal needs and economic ability, with the current technology as the fourth. Without the participation of dedicated and determined political decision makers, the other three factors are challenging to obtain. Political decision makers need to facilitate economic means to support the transformation in society and affected industries to balance the economic disadvantages of the electrically powered vehicle systems until they pass the cost disadvantage turning point. The development of relevant technology is no longer the significant barrier it was at the beginning of this transformation about 20 years ago. The technology for electrically powered transportation systems and devices is widely available now, although it is continuously evolving and being improved. Associated industries cannot be expected to initiate, finance, take risks, and take the lead in this global societal transformation without clear and strong political support. [ABSTRACT FROM AUTHOR]

Battery health assessments are essential for roadside energy storage systems that facilitate electric transportation. This paper uses the samples from the charging and discharging data of the base station and the power station under different working conditions at different working hours and at different temperatures to demonstrate the decay of the battery health of a roadside energy storage system under different cycles. In this paper, for the first time, the predicted state-of-health values are obtained by extracting the characteristic quantities affecting the battery health based on three indicators: the internal resistance, the rate of change of voltage, and the change of temperature. Data on state of health are clustered by K-Means, GMM, K-Means++ and divided into high, medium, and low levels. Using a comparison of the three methods, GMM clustering appears to be the best at reflecting the charging and discharging capacity of the battery. [ABSTRACT FROM AUTHOR]

Improving air quality, reducing greenhouse gas emissions, and achieving independence from fossil fuels have led most countries towards deploying solar photovoltaics (PV) in the power distribution grid and electrifying the transportation fleet. Internal combustion engine (ICE) vehicles are, in particular, one of the main culprits of injecting greenhouse gas emissions into the atmosphere, making electric vehicles (EVs) an important tool in combating climate change. Despite their considerable environmental and economic benefits, the integration of PVs and EVs can introduce unique operational challenges for the power distribution grid. If not coordinated, high penetration of PVs and EVs can result in variety of power quality issues, such as instances of overvoltage and undervoltage, frequency fluctuations, and/or increased losses. This paper proposes a mixed-integer multi-objective nonlinear optimization model for optimal energy dispatch in a power distribution grid with high penetration of PV and EV resources. The model proposed here is an extension of the traditional voltage and var optimization (VVO) into a comprehensive and coordinated control of voltage, active power, and reactive power. A modified version of the IEEE 123-bus test distribution system is used to demonstrate the effectiveness of the proposed solution. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the environmental impacts of different types of passenger transportation means (i.e., bicycles, motorcycles, cars, buses, trains, and airplanes). The method has been applied to the European scenario. The study was performed by using life cycle assessment in accordance with international standard ISO 14040/44 for assessing the CO2 eq., SO2, and PM10 of the transportation means by exploiting data (i.e., vehicles features and environmental impacts) from 24 scientific papers from the literature that have been manually analyzed. The functional unit is defined as the impact per 1 passenger over 1 km. The study identified that planes are the most impacting for CO2 eq. with up to 380 g/pkm, while cars are the most impacting for SO2 with up to 1.78 g/pkm and PM10 with 0.98 g/pkm. Electric and hybrid models proved to be significantly better than others, while buses are the most sustainable in general. Referring to the overall European scenario, cars constitute up to 95% of the overall impacts. By comparing some improvements for reducing the impacts, it emerged that the limitation of diesel cars along with the increase of buses and trains are the most effective. The provided outcomes may be useful for legislators, manufacturers, and users for favoring the choice of the transportation means in a more environmentally conscious way. [ABSTRACT FROM AUTHOR]