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The limited endurance mileage of battery electric vehicles (BEVs) affects mode choice of commuters inevitably. To help facilitate BEV charging and improve accessibility of transit stations, the park-charge-ride (PCR) services have been implemented in some cities. This study develops a deterministic continuum equilibrium model for a monocentric city to analyze the modal choice behavior of commuters in a transportation system with BEVs and PCR services. Theoretical analysis is conducted for the model and some equilibrium properties are presented. The positive influence for setting PCR facilities is confirmed from theoretical point of view. It is also found that in the transportation systems with PCR services, a location exists that commuters living closer to CBD should choose railway as their only transportation mode. By deploying the discrete approximation approach, numerical examples are given to demonstrate the model. The impact of factors including initial state of charge of the battery electric vehicles, in carriage crowding cost of the railway transit are studied via numerical analysis.

The development of efficient electric vehicle (EV) charging infrastructure requires modelling of consumer demand at an appropriate level of detail. Since only limited information about real customers is available, most simulations employ a stochastic approach by combining known or estimated business features (e.g. arrival and departure time, requested amount of energy) with random variations. However, these models in many cases do not include factors that deal with the social characteristics of EV users, while others do not emphasise on the economic elements. In this work, we introduced a more detailed demand model employing a modal choice simulation framework based on Triandis’ Theory of Interpersonal Behaviour, which can be calibrated by empirical data and is capable of combining a diverse number of determinants in human decision-making. By applying this model on Switzerland mobility domain, an analysis on three of the most popular EV incentives from both supply and demand sides is provided, which aims for a better understanding of electro-mobility systems by relating its causes and effects.

Output power and beam quality are the two main bottlenecks for semiconductor lasers—the favourite light sources in countless applications because of their compactness, high efficiency and cheapness. Both limitations are due to the fact that it becomes increasingly harder to stabilize a single-mode laser over a broader chip area without multi-mode operations. Here we address this fundamental difficulty with the Dirac-vortex topological cavity1, which offers the optimal single-mode selection in two dimensions. Our topological-cavity surface-emitting laser (TCSEL) exhibits 10 W peak power, sub-1° divergence angle and 60 dB side-mode suppression, among the best-reported performance ever at 1,550 nm—the most important telecommunication and eye-safe wavelength where high-performance surface emitters have always been difficult to make2. We also demonstrate the multi-wavelength capability of two-dimensional TCSEL arrays that are not generally available for commercial lasers2,3. TCSEL, as a new-generation high-brightness surface emitter, can be directly extended to any other wavelength range and is promising for an extremely wide variety of uses.Researchers demonstrate a topological-cavity surface-emitting laser with a 10 W peak power and sub-degree beam divergence at 1,550 nm wavelength. The system is also capable of multiple-wavelength arrays.

Shuttles that operate without an onboard driver are currently being developed and tested in various projects worldwide. However, there is a paucity of knowledge on the determinants of acceptance of driverless shuttles in large cross-national samples. In the present study, we surveyed 10,000 respondents on the acceptance of driverless vehicles and sociodemographic characteristics, using a 94-item online questionnaire. After data filtering, data of 7,755 respondents from 116 countries were retained. Respondents reported that they would enjoy taking a ride in a driverless vehicle (mean = 4.90 on a scale from 1 = disagree strongly to 6 = agree strongly). We further found that the scores on the questionnaire items were most appropriately explained through a general acceptance component, which had loadings of about 0.7 for items pertaining to the usefulness of driverless vehicles and loadings between 0.5 and 0.6 for items concerning the intention to use, ease of use, pleasure, and trust in driverless vehicles, as well as knowledge of mobility-related developments. Additional components were identified as thrill seeking, wanting to be in control manually, supporting a car-free environment, and being comfortable with technology. Correlations between sociodemographic characteristics and general acceptance scores were small (<0.20), yet interpretable (e.g., people who reported difficulty with finding a parking space were more accepting towards driverless vehicles). Finally, we found that the GDP per capita of the respondents’ country was predictive of countries’ mean general acceptance score (ρ=-0.48 across 43 countries with 25 or more respondents). In conclusion, self-reported acceptance of driverless vehicles is more strongly determined by domain-specific attitudes than by sociodemographic characteristics. We recommend further research, using objective measures, into the hypothesis that national characteristics are a predictor of the acceptance of driverless vehicles.

A discussion of the sustainability and travel behaviour impacts of ride-hailing is provided, based on an extensive literature review of studies from both developed and developing countries. The effects of ride-hailing on vehicle-kilometres travelled (VKT) and traffic externalities such as congestion, pollution and crashes are analysed. Modal substitution, user characterisation and induced travel outputs are also examined. A summary of findings follows. On the one hand, ride-hailing improves the comfort and security of riders for several types of trips and increases mobility for car-free households and for people with physical and cognitive limitations. Ride-hailing has the potential to be more efficient for rider-driver matching than street-hailing. Ride-hailing is expected to reduce parking requirements, shifting attention towards curb management. On the other hand, results on the degree of complementarity and substitution between ride-hailing and public transport and on the impact of ride-hailing on VKT are mixed; however, there is a tendency from studies with updated data to show that the ride-hailing substitution effect of public transport is stronger than the complementarity effect in several cities and that ride-hailing has incremented motorised traffic and congestion. Early evidence on the impact of ride-hailing on the environment and energy consumption is also concerning. A longer-term assessment must estimate the ride-hailing effect on car ownership. A social welfare analysis that accounts for both the benefits and costs of ride-hailing remains unexplored. The relevance of shared rides in a scenario with mobility-as-a-service subscription packages and automated vehicles is also highlighted.

Urban transport provides access to multiple services, structures and impedes daily life of residents, and translates into wellbeing considerations, sustainability impacts, and GHG emissions. Thus motivated, multiple disciplines, ranging from psychology to urban planning, are invested in understanding the potential for transitioning to low-carbon and sustainable urban transport systems. While each discipline has carved out a growing body of knowledge, a consistent cross-disciplinary understanding of psychological, sociological, and urban form determinants of urban mobility choices is, perhaps surprisingly so, still lacking. Here, we systematically review the reviews of several strands of literature and lay out the evidence for individual, social, and infrastructure level factors pertinent to urban mode choice. Synthesizing the results from 75 review papers, we find that all three dimensions (individual, social, and infrastructure) unambiguously interfere with mode choice. Individuals are most motivated to shift modes, if they are well informed, if personal norms match low-carbon mode use, and, most importantly, if they perceive to have personal control over decisions. Perceptions about common travel behaviour (descriptive social norms), especially if supported by perceived normative beliefs of others (injunctive norms), are highly influential to support mode shift. However, the overall margin of shift as induced by individual and social settings remains limited. Instead, the infrastructure factors explain large differences in mode choice. New shared mobility modes, and teleworking and shopping, add a long tail to modes chosen, but are no game changer. We conclude that a transition to low-carbon mobility requires low-carbon infrastructure, which leverages enthusiastic individuals' concerns and empowers them for mode change, and that address safety concerns prevalent especially in cities of the Global South. The mode shift to low-carbon option can then be sustained and enhanced by social influence in the form of collective social norms.

Ride-sharing has received great attention recently and is considered to be a sustainable transportation mode. Understanding the determinants of the consumers’ intention to use ride-sharing services is critical to promote such services. In this research, an extended technology acceptance model is used as a theoretical research framework. This extension was implemented by incorporating three new constructs: personal innovativeness, environmental awareness, and perceived risk. The model was empirically tested using questionnaire survey data collected from 426 participants. The results indicate that personal innovativeness, environmental awareness, and perceived usefulness are positively associated with consumers’ intention to use ride-sharing services, while perceived risk is negatively associated with the intention and perceived usefulness. The analysis shows that, contrary to our expectations, the perceived ease of use has no significant effect on intention to use ride-sharing services. In addition, personal innovativeness is positively related to perceived usefulness and perceived ease of use but negatively related to perceived risk. Based on these results, implications for practice and suggestions for further research are discussed.

An unprecedented fiber narrow-band filter is proposed, which is composed of a phase-shifted fiber grating with an anti-symmetric refractive index distribution and a uniform fiber grating. The anti-symmetric refractive index distribution is obtained by performing a one-sided exposure on both sides of the few-mode fiber, where the two exposure positions differ by half period of the grating. By introducing an anti-symmetric refractive index distribution, coupling resonance occurs in the LP01 and LP11 modes in the two-mode fiber, and the reflected light and transmitted light are separated into LP11 mode and LP01 mode, respectively. To achieve a narrow-band reflection spectrum, the π phase is introduced into an anti-symmetric refractive index grating, and its transmitted light is reflected through a uniform grating. Single-mode fiber and taper-coupled fiber are introduced to select LP01 mode selection, and the LP11 mode is cutoff. Finally, the laser linewidth characteristics of the proposed structure are analyzed by co-simulation with semiconductor gain chips. Simulation results show that the proposed structure can improve the linewidth of single-longitudinal mode lasers, which has very important potential applications in the fields of Lidar, coherent communication and sensing.

Due to the potential of automated vehicles to offer a multitude of advantages to the travelers and therefore influence their daily routines, it is essential to monitor the public’s opinion on this particular technological development. The goal of a number of surveys in recent years was therefore not only to elicit the general acceptance of the technology but to additionally explore when, how and why respondents were inclined to make use of it. This is the first literature review on surveys regarding automated vehicles with the intention to investigate the various methods currently being applied and the conclusions they lead to. In addition to comparing the general results in terms of the distributions of the response variables, the surveyed explanatory variables are categorized and analyzed according to their influence in different experiments. Based on these investigations, this review identifies research gaps that can be addressed in future experiments.

Capacitive membrane and inductive channels enable the approach of neural activities in some equivalent neural circuits, and involvement of memristive term and magnetic flux can estimate the effect of electromagnetic induction. Based on the memristive neuron models, synaptic controllability and field coupling between neurons can be explored from physical aspect. Most of the biophysical neurons are defined in nonlinear oscillators, which can be mapped from the circuit equations under scale transformation, and the energy functions can be obtained in theoretical way. To enrich complex dynamics, specific terms are often introduced into the known models, and it requires the involvement of specific electric components for inducting special relation between the channel current and across voltage. Indeed, mathematical maps are effective to produce similar firing modes matching with neural activities in biological neurons. In this work, memristor is connected to a simple nonlinear circuit for building a memristive neuron, and its energy function is derived from two ways. Under linear transformation, the memristive neuron in oscillator form is converted into a memristive map, the energy function is confirmed, and an adaptive criterion is presented to regulate the intrinsic parameter, which the self-adaptive regulation property is released. The scheme provides clues to design discrete neuron models and understand its role of energy flow on the self-adaptive property and mode selection.