INDUSTRIAL INTELLIGENCE FOR SMART CITIES: THE ROLE OF AI AND IOT IN TRANSFORMING URBAN MOBILITY AND INFRASTRUCTURE

Objective: The aim of this work is to review the literature and analyze trends and innovations in public transportation, as well as discuss the importance and challenges of urban mobility in the Brazilian context. Theoretical framework: Urban mobility is relevant due to the growth of cities and the need for sustainable transportation. Quality of life and economic development depend on safe and efficient transportation. Mobility also reduces social inequality by allowing access to services and opportunities for different social classes. Inclusive public policies and accessible transportation are crucial to improve people's quality of life. Method: The methodology adopted in this study was based on a literature review conducted in three distinct phases, covering the planning of the review, the effective execution of it, and the communication and presentation of the results obtained from the research. Results and conclusion: The review identified that the current scenario of urban mobility in Brazil is marked by a lack of adequate infrastructure for public transportation, cycling, and pedestrian routes, with an increase in the number of private vehicles on the streets and inequality in access to public transportation. To overcome these limitations, integrated planning, investments in quality public transportation, cycling and pedestrian infrastructure, and a cultural change in relation to urban mobility are necessary. Technological innovations, such as vehicle electrification, digitalization of transportation services, and autonomous car systems, are essential to solve the challenges of urban mobility. Research implications: In the future, integration of transportation forms and intermodal networks is expected to facilitate mobility. Advanced technologies, such as autonomous vehicles, can reduce costs and increase efficiency. Investments in infrastructure, such as cycling routes, charging stations, and renewal of public transportation, are necessary. Public policies that encourage the adoption of electric vehicles and shared mobility, such as tax and tariff reductions, can disseminate technologies. Originality/value: It is recommended to analyze the economic and social impacts of the popularization of electric vehicles in Brazil, including financial viability and charging infrastructure. It is important to research advanced technologies, such as autonomous vehicles, to improve the efficiency and safety of public transportation, as well as to examine regulatory and implementation challenges.

The growing relevance of sustainability, as well as the necessity to replace traditional forms of transportation with sustainable ones, has made sustainable urban mobility an imperative. In order to respond to the ever-increasing need to develop sustainable modes of transport, the importance of electric, autonomous, and electric autonomous vehicles is increasingly emphasized. In addition, as trends of growth and development in electric autonomous vehicle technology are increasing, one of the questions that has appeared is whether autonomous electric vehicles represent one of the mechanisms that will be used to increase the sustainability of urban mobility. With this in mind, the results of a systematic analysis of existing research in the WOS and Scopus databases using the keywords “urban mobility”, “electric vehicles”, and “autonomous vehicles” was carried out to identify research trends in the use of autonomous electric vehicles in urban areas. The research showed that authors focus on the advantages and disadvantages of autonomous electric vehicles and their usage in the urban mobility system, but an insufficient number of authors consider and define the need to plan the transition towards incorporating autonomous electric vehicles into the urban system. The results of this research also indicate an insufficient number of papers that research and describe the application of autonomous electric vehicles in distribution logistics. This paper provides an overview of existing research related to autonomous electric vehicles and the challenges of transition in the context of infrastructure and the development of a culture of sustainability among urban residents.

A systematic review of agent-based models for autonomous vehicles in urban mobility and logistics: Possibilities for integrated simulation models

Prelims

In the study, the connectivity of the ontological and epistemological knowledge of the space in intervening in urban transportation and mobility problems is questioned through the sample area. The purpose of the questioning; is to understand whether potential urban mobility analysis and original application principles can be obtained by trying to reflect the epistemological knowledge of the space to the ontological knowledge. Urban mobility studies; it is seen as sustainable and up-to-date approaches that are handled with original preparation, plan, implementation and monitoring processes, that bring together land use regulations, development plans and transportation plans in the solution of urban transportation problems, and combine spatial and other relational dimensions that develop accordingly. As a result of the inquiry, it was determined that the connectivity between epistemological and ontological knowledge of the space effectively solved urban transportation and mobility problems. It has been seen that it is effective in directing planning and design, especially in urban mobility planning, at the lower scale, during plan implementations, or before plan making. The first stage of the study consists of understanding the ontological and epistemological layers of urban space. In the second stage, the connectivities of these layers in intervening in urban transportation and mobility problems are examined. In the study, while producing urban mobility resolutions, improvements were made to the ontological and epistemological layers of the space (topographic, typological, topological, and hodological), and these were tested on the sample area. Thus, it will be understood whether the method to be followed will be valid in other cities.

Over the last century, urban transport studies have traditionally focused on private cars, public transport, and their infrastructures. In the past few decades, there has been a paradigm shift and the concept of mobility has come to the forefront. This approach is more comprehensive, as it includes walking, cycling, new paratransit modes such as e-scooters and, again, their infrastructures. On the other hand, as in other urban infrastructures and services, there is a pervasive digitalization in urban mobility. Electric and urban air mobility, autonomous vehicles, shared services, and platformization are some of the popular topics that are now addressed widely in related literature. In this chapter, we focus on these new technologies and developments in urban mobility and analyze their implications for efficiency, sustainability, and resilience, making use of the IGLUS conceptualization, which is based on a systems approach. Therefore, the interdependence between new mobility and other urban infrastructures and potential scenarios for overall future urban context is also studied. Without a specific country, city, or context, there is a global angle and findings from related literature are synthesized to conduct an analysis.

Aims: Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Background: Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. Objective: To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. Methods: An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. Results: The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Conclusion: Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.

This paper explores how technologies such as the Internet of Things (IoT), autonomous vehicles (AVs), artificial intelligence (AI), and blockchain are revolutionizing urban mobility. The IoT facilitates real-time data collection and analysis, enhancing operational efficiency and reducing emissions through optimized routes and predictive maintenance. AVs, particularly when combined with electric vehicles (EVs), offer significant reductions in fuel consumption and urban air pollution. Smart mobility solutions, including Mobility-as-a-Service (MaaS) platforms and big data analytics, further support efficient and environmentally friendly transportation networks. Blockchain technology enhances data security and transparency, crucial for the development of reliable and safe transportation networks. This paper concludes that the fusion of these technologies is not merely an enhancement but a necessary evolution to meet the growing demands for sustainable urban mobility and contribute to global sustainability efforts.

The advent of autonomous vehicles powered by artificial intelligence (AI) has revolutionized the automotive industry, paving the way for safer, more efficient, and convenient transportation solutions. This research paper delves into the intricate fusion of AI technologies within Google's driverless car project, showcasing the synergy between machine learning algorithms, advanced sensor technologies, and robust autonomous driving software. Through a deep analysis of the machine learning algorithms employed, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), this paper elucidates how Google's autonomous vehicles perceive, interpret, and navigate complex real-world environments. The role of sensor technologies such as LiDAR, radar, cameras, and ultrasonic sensors is explored in detail, emphasizing their pivotal role in data collection, processing, and fusion for comprehensive situational awareness. Furthermore, the paper delves into the software architecture and algorithms responsible for decision-making, planning driving maneuvers, and ensuring passenger safety. Safety measures, redundancy systems, and regulatory considerations are also addressed, highlighting the challenges and opportunities presented by autonomous driving technologies. By synthesizing insights from AI research, sensor technologies, and autonomous vehicle development, this paper provides a holistic view of Google's driverless car project and its implications for the future of transportation. The research not only contributes to the understanding of cutting-edge AI applications in the automotive sector but also opens avenues for further advancements in autonomous vehicle technology, paving the way for a transformative shift in urban mobility and transportation infrastructure. The advent of autonomous vehicles powered by artificial intelligence (AI) has revolutionized the automotive industry, paving the way for safer, more efficient, and convenient transportation solutions. This research paper delves into the intricate fusion of AI technologies within Google's driverless car project, showcasing the synergy between machine learning algorithms, advanced sensor technologies, and robust autonomous driving software. Through a deep analysis of the machine learning algorithms employed, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), this paper elucidates how Google's autonomous vehicles perceive, interpret, and navigate complex real-world environments. The role of sensor technologies such as LiDAR, radar, cameras, and ultrasonic sensors is explored in detail, emphasizing their pivotal role in data collection, processing, and fusion for comprehensive situational awareness. Furthermore, the paper delves into the software architecture and algorithms responsible for decision-making, planning driving maneuvers, and ensuring passenger safety. Safety measures, redundancy systems, and regulatory considerations are also addressed, highlighting the challenges and opportunities presented by autonomous driving technologies. By synthesizing insights from AI research, sensor technologies, and autonomous vehicle development, this paper provides a holistic view of Google's driverless car project and its implications for the future of transportation. The research not only contributes to the understanding of cutting-edge AI applications in the automotive sector but also opens avenues for further advancements in autonomous vehicle technology, paving the way for a transformative shift in urban mobility and transportation infrastructure.

Urban aerial mobility: Reshaping the future of urban transportation

Singapore enjoys a world-class urban transportation system today, benefitting from a combination of long-term planning, continued investment in infrastructure, and readiness in adopting new technologies. However, planners will always need to prepare for uncertain futures, and understand driving forces and global trends that affect future urban mobility. In this paper, we present an ongoing foresight study on Singapore’s urban transport and mobility up to 2030. Our objectives are to develop a shared understanding of the current state of the transportation system, highlight long-term challenges and opportunities, and establish networks between stakeholders. Through environmental scanning and expert interviews, our preliminary findings indicate that mobility-on-demand services, multi-modal transport, and e-commerce are the dominant future drivers of change in the urban mobility landscape. In addition, ageing population, growing population and travel demand, inefficiencies in urban freight, shortage in skilled manpower, and a general resistance to big policy changes are the key challenges facing Singapore urban mobility in future. Finally, in terms of technology, autonomous vehicles, real-time traveller information, and shared mobility are seen as potential game-changers for the future.

There is no formalised theory of sustainable urban mobility systems. Observed patterns of urban mobility are often considered unsustainable. But we don’t know what a city with sustainable mobility should look like. It is nevertheless increasingly apparent that the urban mobility system plays an important role in the achievement of the city’s wider sustainability objectives.In this paper we explore the characteristics of sustainable urban mobility systems through the technique of Bayesian networks. At the frontier between multivariate statistics and artificial intelligence, Bayesian networks provide powerful models of causal knowledge in an uncertain context. Using data on urban structure, transportation offer, mobility demand, resource consumption and environmental externalities from seventy-five world cities, we developed a systemic model of the city-transportation-environment interaction in the form of a Bayesian network. The network could then be used to infer the features of the city with sustainable mobility.The Bayesian model indicates that the city with sustainable mobility is most probably a dense city with highly efficient transit and multimodal mobility. It produces high levels of accessibility without relying on a fast road network. The achievement of sustainability objectives for urban mobility is probably compatible with all socioeconomic contexts.By measuring the distance of world cities from the inferred sustainability profile, we finally derive a geography of sustainability for mobility systems. The cities closest to the sustainability profile are in Central Europe as well as in affluent countries of the Far East. Car-dependent American cities are the farthest from the desired sustainability profile.

Objective: This article aims to analyze the challenges and solutions of integrating urban logistics and urban mobility, providing insights and a framework for the development of public policies, business strategies, and future research. Theoretical Framework: The harmony between logistics and urban mobility is essential for the efficient management of cities, given its direct influence on the movement of people and goods. This integration enhances infrastructure, accessibility, social inclusion, and competitiveness while reducing operational costs. With the growth of online commerce and urbanization, it is urgent to seek a fairer and more sustainable mobility model, demanding strategic and collaborative urban planning to ensure smart and efficient cities in the future. Method: The research employed a systematic literature review (SLR) with a predefined search strategy in the Scopus and Transport Research International Documentation (TRID) databases, using specific terms related to urban logistics and mobility. This resulted in the selection of 129 studies from the period 2019-2024. The framework's development involved organizing and categorizing the extracted information. Results and Discussion: The SLR revealed the need for more comprehensive technical studies to improve urban mobility, considering geographical and cultural specificities and the local impact of infrastructure works. The high population density in metropolitan areas has increased traffic and hindered goods deliveries, emphasizing the importance of urban logistics in mitigating congestion and finding sustainable solutions. The integration of urban logistics with cities' development strategies and territorial policies is essential, requiring technological innovations and integrated public policies. Research Implications: The study proposes an integrated framework for urban logistics and mobility management, which includes components of urban planning, technology and information, incentives and public policies, as well as community engagement. It also highlights the need for future research on the impacts of emerging technologies like autonomous vehicles and delivery systems on urban logistics operations. Originality/Value: The article offers a unique perspective on the interdependence between urban logistics and urban mobility, providing a comprehensive analysis and proposing integrated strategies to enhance efficiency, sustainability, and quality of life in modern cities.

Nowadays cities are subjected to an urbanization increase, such phenomena has several consequences that affect different topics but especially regard urban mobility, because of this increase the number of people using cars rises consequently congestion and CO2 emissions increase. The rise of private vehicles circulating creates a decrease of average speed travel that affect the entire city context so its liveability, then when a high number of vehicles moves into infrastructure that was not designed for that capacity probability of collision will increase due to the elevated interaction compromising people safety. For this reasons public transport systems represents a key role in the liveability of a city because most of them operates in reserved areas and moreover decrease the number of private vehicles moving in cities. The progress that automotive was subjected to affected also urban mobility, first of all the innovation that mainly involved public transport regarded the use of electric vehicles instead of fossil fuels ones, that had a significant environmental impact on bus public transport systems that used fossil fuels vehicles. Anyway the most important innovation that in the last decade is involving automotive regards autonomous vehicles (AVs), these new technologies represent an important change for public transport efficiency due to the elevated performance so the relevant reduction of human mistakes, then because of the high precision of headways would provide a high quality service. Taking into account that each public transport systems has its own characteristics in relation to vehicles type and configuration, the introduction of autonomous vehicles requires specific adjustments and changes.

The development of urban land passenger transport in Kyiv from its inception to the present is studied. The key stages of the evolution of the transport system in Kyiv, from the horse-drawn railway to the introduction of electric trams, buses and electric buses, are considered. The impact of socio-economic and technological changes on the development of transport, in particular urban passenger transport, as well as the current challenges facing urban transport are analyzed. Attention is paid to the Kyiv City Development Strategy until 2025, in particular to the Transport and Urban Mobility sector. The development of land-based urban transport in Kyiv has gone through several important stages of modernization and development over the years, starting with the horse-drawn railway and ending with the implementation of environmental solutions today and in the future. The current development plan focuses on environmental and technological innovations that improve the quality of life of city residents and meet the challenges of urbanization. Taking into account historical experience and current trends, the future development of surface transportation in Kyiv will focus on the introduction of the latest technologies, including autonomous and electric vehicles, which will help improve the environmental situation and quality of life of the residents of the modern city. In the future, the development of surface transportation in Kyiv will be closely linked to the integration of modern technologies, such as intelligent and automatic traffic management systems, electric and autonomous vehicles. In particular, the development of public and passenger transport is envisaged, taking into account its environmental friendliness, safety, accessibility for people with disabilities and other low-mobility groups, and ensuring a high-quality and competitive transport offer.