Autonomous vehicles opportunities for cities air quality

Examination of the adoption intention of new energy vehicles from the perspective of functional attributes and media richness

Drawing on the theory of media richness, this paper aims to explore the impact of media richness on consumers' adoption intention through their perception of new energy vehicle (NEV) function attributes, and assess the moderation roles of brand familiarity and locus of control. A structural equation model is applied to analyze the data collected from 427 respondents. Empirical results demonstrate that consumers' perception of an electric attribute (i.e., charging efficiency) and two intelligent attributes (i.e., car networking and self-driving) are determinants of their adoption intention of NEVs. The other electric attribute (range) is trivial in consumers' perception. We also find that low, medium, and high-richness media significantly affect consumers' perception of NEVs' functional attributes. Compared to the high-richness, medium-richness correlates significantly with two types of NEV functional attributes. Regarding moderating effects, consumer familiarity with NEV's brand negatively impacts the relationship between media richness and adoption intention. Furthermore, low and medium-richness media effectively stimulate individuals with external control to adopt NEV, while high-richness media adversely influence individuals with internal control.

Homo Viator 2020s: electrified and internet-based personal mobilities

Homo Viator [traveling Man] refers in this article to the mobile individuals of the 2020s, gradually exposed to EVs (electric vehicles) and AVs (autonomous vehicles), as electricity-based and Internet-dependent personal road transport, respectively. This article examines the similarities and differences between the electrification and Internetizing of terrestrial personal mobilities and assesses the significance of these two trends for physically moving individuals, mobile society, and mobility-based urban space. EVs are already increasingly adopted, whereas AVs are still mostly being tested. Internet-based communications have already become universally adopted. Electricity and the Internet differ from each other, notably as far as the car industry is concerned, by their roles, modes of production, transmission channels, and storage. For individuals, EVs and AVs differ from each other in several ways: The degree of personal operations and the required accounting and licensing; the ability to move human-made products electronically; ergonomic aspects; travel and communications as an experience; and interactions with fellow individuals. From a societal perspective, the universal use of electricity and the Internet for road transport will require strict security assurance for their production and transmission. In addition, the importance of the relevant communications and electricity professions will grow. On yet another end, the ability to work during car riding may blur the buffer time between work and home. Spatially, EV-based cities will be quieter and cleaner ones, whereas AV-based cities will be characterized by removing traffic lights and road signs, coupled with the availability of more parking spaces.

Verification of the Perception of the Local Community concerning Air Quality Using ADMS-Roads Modeling

Road transport is one among the sources of air pollution in a city, which results in lowering the comfort of life and increases the occurrence of respiratory diseases. The level of pollutants emitted in the city is variable, and it depends on the type and nature of the source and the manner of land development. For this reason, the purpose of the article is an attempt at a spatial (inner) diversification of a city in terms of air quality, using a study of perception and semantic differentials (SD). The research, which covered the period from June to November 2021, was performed in Kielce-the Polish Smart City-among local experts, people well acquainted with the city and knowledgeable about air quality and the impact of pollution on human health. The results allowed the demarcation of areas with the best and the worst parameters in terms of air quality within the city. Verification of the survey was carried out using the ADMS-Roads (Atmospheric Dispersion Modeling System) software for modeling pollution levels and GIS software, using data on road traffic. The verification allowed checking whether the respondents participating in the research accurately evaluated the city space. The modeling proved that within the two selected areas, the pollution level is similar, and it does not exceed the permitted values. This might indicate that in society there is still low awareness of air quality, particularly in terms of knowing the sources of pollutants and their impact on human health, and perception of areas with the best and the worst air quality was the result of an analysis of the manner of land development and its morphology.

How can the built environment affect the impact of autonomous vehicles' operational behaviour on air quality?

Autonomous vehicles (AVs) are pointed out as the technology that will reshape the concept of mobility, with significant implications for the economy, the environment, and society. This fact will bring new challenge to cities urban planning. Research to anticipate the AVs impacts, maximizing their benefits and reduce trade-offs are currently crucial. This work investigates the potential challenges and benefits of gradually replace internal combustion engine human driven vehicles with different penetration rates of AVs - 10%, 30%, 50%, 70%, 90%, and 100% - in urban roads of different characteristics, either in terms of traffic singularities or volumes, and its related implications on air quality. For that purpose, two urban areas with distinct features, Porto and Aveiro, were selected as case studies, and a modelling setup composed of a traffic model, an emission model, and a local air quality model was applied. The results revealed that the AVs benefits are directly linked with the urban design and the road characteristics. In the Aveiro case study, the AVs promoted positive changes with average reductions in daily NOx emissions (compared with the baseline scenario, without AVs) ranging between -2.1% (for C10%) and -7.7% (for C100%). In line with the emissions impacts, positive effects were found on air quality, with average reductions of NO₂ concentrations up to -4% (for C100%). In Porto urban area, slight differences in NOx emissions were obtained (<2%), which implied no changes in the air quality levels. The distinct impact of AVs in the study areas is mostly explained by the traffic light coordination system and directional split distributions in the main roads. These results provide valuable insights to support decision-makers in the definition of strategies that allow the integration of these new emerging technologies in the road infrastructure, considering the features of the urban design, traffic profile and road characteristics.

Environmental impacts of autonomous vehicles: A review of the scientific literature

Autonomous vehicles (AVs) may have significant environmental impacts although there are still few studies focusing solely on these effects. A vast majority of articles address environmental issues as a secondary outcome and, above all, emissions are the main topic. As the notion of environmental impacts concerns many aspects than just air pollution, this paper aims to explore and show the findings and flaws of current research with a wider vision. For that purpose, a systematic review of the scientific literature was carried out broadening the scope to land, water, noise, and light pollution in addition to air. The results reveal potential benefits of AVs due to technical improvements, new possibilities in design and traffic flow enhancement, but the benefits depend on penetration levels, shared mobility acceptance and the interaction with other modes of transport. On the other hand, negative effects are also identified related to the decrease in the value of trip time and user tendencies. Among other potential impacts, changes in land use are increasingly being studied. These changes can lead to significative impacts on emissions as well as on soil and water although the latter have not yet been considered. Lastly, the likely improvements in noise and light pollution are scarcely explored. Given the lack of study of some of the environmental outcomes of AVs, it is not possible to draw a precise conclusion on their overall impact, calling for more comprehensive studies that enable to identify all the measures to be taken to achieve a sustainable future.

Impact of the Light-Duty Vehicles’ Storage and Travel Demand on the Sustainable Exploitation of Available Resources and Air Pollution Abatement

Light-duty vehicles are the predominant means of road transport. As the world population is expected to increase significantly in the following decades, so too will the car fleet. Due to the rising population, and the implicitly higher travel demand, the energy demand of cars will increase too, and this will put a strain on current resources, with negative effects on the supply chain, possibly leading to more pollution. Many of the current sustainable transport models and frameworks attempt to predict the vehicle market share for different powertrains and the resulting impact based on scenarios that cater to the automotive market and industry demands. At the same time, most neglect aspects regarding resources’ depletion and storage demand. In this sense, this study proposes a coherent testing methodology based on the ratio between demand and supply in order to address the limitations of these studies, mainly related to the sustainable exploitation of available resources, which are analyzed herein in correlation with the current predictions. A sensitivity analysis is provided in order to evaluate the uncertainty of utilized predictions. As a result of this analysis, two novel scenarios for assessing the evolution of the vehicle market share are proposed by the authors. When compared to similar scenarios, it was shown that the proposed scenarios lead to noticeable benefits in reducing dependency on the resources associated with a demand of energy and raw materials and in mitigating air pollution, including related costs.

Impact of Autonomous Vehicles on Roundabout Capacity

Studying the impact of AVs on our road infrastructure offers a lot of potential in the transportation domain; one of these issues is how capacity will be affected. This paper presents a contribution to this research area by investigating the impact of AVs on the capacity of single-lane roundabouts using a microsimulation model. For the development of the model, a roundabout situated in Győr (Hungary) was selected and field data on the roundabout geometric characteristics as well as traffic volumes were used. Simulations using Vissim were run for various scenarios based on varying input traffic volumes and market penetration rates of AVs to assess queue lengths. The highway capacity manual (HCM) roundabout model was used to estimate the capacity of the existing roundabout. Values of follow-up times and critical gaps were set to decreasing as the penetration rate of AVs increases. The results demonstrated that 20% and 40% AVs in the flow would increase leg capacities by about 10% and 20%, respectively. Furthermore, a reduction in excessive queue lengths was estimated and capacities and queue lengths were calculated by legs. It was found that these are highly influenced by the distribution of flows among legs, and the share of flows in various directions.

Assessing air pollution in European cities to support a citizen centered approach to air quality management

European cities have made significant progress over the last decades towards clean air. Despite this progress, several cities are still facing acute air pollution episodes, with various urban areas frequently exceeding air quality levels allowed by the European legal standards and WHO guidelines. In this paper, six European cities/ regions (Bristol, UK; Amsterdam, NL; Sosnowiec, PL; Ljubljana, SI; Aveiro, PT; Liguria, IT) are studied in terms of air quality, namely particulate matter, nitrogen dioxide and ozone. The concentrations trends from 2008 to 2017 in the different typology of monitoring stations are addressed, together with the knowledge of daily, weekly and seasonal pollution patterns to better understand the city specific profiles and to characterize pollutant dynamics and variations in multiple locations. Additionally, an analysis of the duration and severity of air pollution episodes is also discussed, followed by an analysis of the fulfillment of the legislated limit values. Each of our 6 case study locations face different air pollution problems, but all these case studies have made some progress in reducing ambient concentrations. In Bristol, there have been strong downward trends in many air pollutants, but the levels of NO₂ remain persistently high and of concern. In recent years, decreasing concentration levels point to some success of Amsterdam air quality policies. PM₁₀ exceedances are a seasonal pollution problem in Ljubljana, Sosnowiec and Aveiro region (even if with different levels of severity). While, exceedances of NO₂ and O₃ concentrations are still problematic in Liguria region. The main findings of this paper are particular relevant to define and compare future citizen-led strategies and policy initiatives that may be implemented to improve and fulfill the EU legislation and the WHO guidelines.

Three Decades of Research on Smart Cities: Mapping Knowledge Structure and Trends

The concept of smart cities has gained significant momentum in science and policy circles over the past decade. This study aims to provide an overview of the structure and trends in the literature on smart cities. Bibliometric analysis and science mapping techniques using VOSviewer and CiteSpace are used to identify the thematic focus of over 5000 articles indexed in the Web of Science since 1991. In addition to providing insights into the thematic evolution of the field, the three-decade study period is divided into two sub-periods (1991–2015 and 2016–2021). While splitting the dataset into more sub-periods would have been desirable, we decided to only examine two sub-periods as only very few papers have been published until 2010. The annual number of publications has progressively increased since then, with a surge in the annual number of publications observable from 2015 onwards. The thematic analysis showed that the intellectual base of the field has been very limited during the first period, but has expanded significantly since 2015. Over time, some thematic evolutions, such as further attention to linkages to climate change and resilience, and more emphasis on security and privacy issues, have been made. The thematic analysis shows that existing research on smart cities is dominated by either conceptual issues or underlying technical aspects. It is, therefore, essential to do more research on the implementation of smart cities and actual and/or potential contributions of smart cities to solving societal issues. In addition to elaborating on thematic focus, the study also highlights major authors, journals, references, countries, and institutions that have contributed to the development of the smart cities literature.

A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems

Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report the findings of an online horizon scan involving 170 expert participants from 35 countries. We conclude that RAS are likely to transform land use, transport systems and human-nature interactions. The prioritized opportunities were primarily centred on the deployment of RAS for the monitoring and management of biodiversity and ecosystems. Fewer challenges were prioritized. Those that were emphasized concerns surrounding waste from unrecovered RAS, and the quality and interpretation of RAS-collected data. Although the future impacts of RAS for urban ecosystems are difficult to predict, examining potentially important developments early is essential if we are to avoid detrimental consequences but fully realize the benefits.

Mapping Carbon Monoxide Pollution of Residential Areas in a Polish City

Road traffic is among the main sources of atmospheric pollution in cities. Maps of pollutants are based on geostatistical models using a digital model of the city along with traffic parameters allowing for ongoing analyses and prediction of the condition of the environment. The aim of the work was to determine the size of areas at risk of carbon monoxide pollution derived from road traffic along with determining the number of inhabitants exposed to excessive CO levels using geostatistical modeling on the example of the city of Bydgoszcz, a city in the northern part of Poland. The COPERT STREET LEVEL program was used to calculate CO emissions. Next, based on geostatistical modelling, a prediction map of CO pollution (kg/year) was generated, along with determining the level of CO concentration (mg/m3/year). The studies accounted for the variability of road sources as well as the spatial structure of the terrain. The results are presented for the city as well as divided into individual housing estates. The level of total carbon monoxide concentration for the city was 5.18 mg/m3/year, indicating good air quality. Detailed calculation analyses showed that the level of air pollution with CO varies in the individual housing estates, ranging from 0.08 to 35.70 mg/m3/year. Out of the 51 studied residential estates, the limit value was exceeded in 10, with 45% of the population at risk of poor air quality. The obtained results indicate that only detailed monitoring of the level of pollution can provide us with reliable information on air quality. The results also show in what way geostatistical tools can be used to map the spatial variability of air pollution in a city. The obtained spatial details can be used to improve estimated concentration based on interpolation between direct observation and prediction models.