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Due to the development of the shared economy, increasingly more shared mobility providers have launched services based on the use of electric vehicles. The increasing growth of electric shared mobility services has produced various types of problems that do not occur (or occur with a limited effect) under conventional shared mobility systems. This increase in electric shared mobility problems has led to many effects, including limitations of the system zones or going out of business. To avoid difficulties in the functioning of electric shared mobility systems, various scientific studies have been undertaken to model and optimize the operation of these systems. Modeling and optimization mainly relate to one category of the system—for example, only to bike sharing. However, to understand the system of electric shared mobility holistically, there is a need to define the criteria generally as stimulants or destimulants. Based on these assumptions, we conducted research on the identification of factors influencing the development of electric shared mobility services. We conducted our own expert research based on the Social Network Analysis method. The aim of this study was to determine the factors that influence the development or recession of services in the entire electric shared mobility market in reference to selected stakeholders. The obtained results indicate a non-standard approach to the modeling and optimization of electric shared mobility services. This study could be used as support for creating electric shared mobility models and could also be helpful for service providers or local mobility managers through the developed recommendations.

Urban travel behavior in developing cities forms a complex system with nonlinear interactions among socioeconomic factors, land use patterns, and transportation infrastructure. This study examines these intricate dynamics in Rajshahi City Corporation (RCC), Bangladesh, using a multimodel approach to capture emergent properties of urban mobility. Analyzing data from 2286 households across six zones, we developed three interconnected models: Trip Production Model (TPM), Trip Attraction Model (TAM), and Household Kilometers Traveled Model (HKTM). The TPM showed that increasing household size by one unit boosts trip production by 1.537 times, while a one‐unit increase in accessibility raises it by 1.930 times. Interestingly, the TAM revealed that higher accessibility can decrease trip attractions (coefficient: −1.412), indicating emergent congestion effects. The HKTM indicated that a one‐unit improvement in road connectivity leads to an increase of 2.652 km in household travel. Our results demonstrate that socioeconomic and land use factors explain 75.1% of the variability in trip production, emphasizing the system’s complexity. The City Center, with the highest entropy index (0.80), attracted the most trips, whereas the Northern Fringe, despite a low entropy (0.52), generated the highest number of trips. These surprising findings highlight the nonlinear relationships in urban mobility and stress the importance of context‐specific solutions to address urban transportation challenges. By applying complex systems theory, including concepts of self‐organization and feedback loops, we provide a comprehensive framework for understanding and modeling urban transport dynamics in developing areas, offering valuable insights for adaptive policy‐making amid rapid urban growth.

Transportation habits have been significantly modified in the past decade by the introduction of shared mobility systems. These have emerged as a partial response to the need of resorting to green means of transportation and to the desire of being more flexible in the choice of trips, both from a spatial and a temporal point of view. On the one hand, shared mobility systems have taken advantage of the interest of riders for shared experiences. On the other hand, their success has been possible as a result of the recent advances in information and communications technology. The operational research community is already very active in this emerging field, which provides a very rich source of new and interesting challenges, covering several planning levels, from strategic to operational ones, such as station location, station sizing, rebalancing routes. A fascinating feature of this field is the variety of the methods used to deal with these questions. Our purpose is to survey the main problems and methods arising in this field.

For a significant number of people with visual impairments, public transport plays an important role in productivity, community participation, and independence, since it may be the only feasible mobility option to participate in their education, work, medical care, food, and to attend many other places in their community. To use the public bus system safely, effectively, and autonomously, these people need to collect information about their physical environment and visible information at stops and terminals, such as timetables, routes, etc. Unfortunately, most people who are blind or visually impaired experience difficulties in getting on the right bus or getting off at the right destination. These situations usually force them to depend on other people that assist them in activities close to their homes, or settle for simpler jobs, or simply stay at home. Therefore, our efforts should aim to develop a system where technology is used to empower people with visual disabilities, allowing them to navigate autonomously in the public transport system. This paper presents a system based on radio frequency (RF) communication proposed within the framework of the MOVIDIS (Mobility for Visually Disabled People) research project (funded by the National Secretariat of Science, Technology and Innovation-SENACYT, under Grants No. 109-2015-4-FID14-073 and No. 99-2018-4-FID17-031), which provides an alternative to assist people with visual disabilities with their mobility in the public transport system. The various modules of this system communicate with each other by means of radio frequency and allow users to interact with buses and their respective stops. The first experimental results show that RF communication represents a viable option to help people with visual disabilities in public transport services.

The shared mobility services market is growing and changing very rapidly. Many novelties are introduced to the systems, ranging from improvements to the services already offered to services referred to as innovative. Since the following years are to bring significant development of mobility as a service (MaaS) systems, data sharing, and cooperation on the mobility market, the article is dedicated to check whether the current business models of the industry are ready for the open innovations implementations. The article aimed to analyze the business models of shared mobility systems along with their presentation in the form of CANVAS models and to investigate whether the models contain aspects of open innovation. Moreover, the article presents its own value-added open business model prepared for the whole shared mobility market. The paper also identifies a set of open innovations that can be implemented by all types of shared mobility operators. It proposed the basis that operators can use when developing their own open business models. The developed research is an original contribution to filling the research gap concerning the approach to open innovation by operators of all types of shared mobility services available on the market. The results show that car-sharing service providers are the biggest opponents of open innovation. On the other hand, the most ‘open’ systems are bike-sharing services. The conducted research may support operators in the process of transforming their businesses into more accessible for users. It also helps to develop the open innovation concept to create more sustainable shared mobility systems along the lines of collaborative economy assumptions.

The urban landscape of Kinshasa, Democratic Republic of Congo, faces significant mobility challenges, primarily stemming from rapid urbanization, overpopulation, and outdated infrastructure. These challenges necessitate the exploration of modern smart mobility concepts to improve traffic flow, road safety, and sustainability. This study investigates the potential of solutions such as Mobility-as-a-Service, car sharing, micro-mobility, Vehicle-as-a-Service, and electric vehicles in addressing these challenges. Through a comparative analysis of global implementations, this research identifies key success factors and barriers that inform the feasibility of integrating these solutions into Kinshasa’s unique socio-political and infrastructural context. The study presents a conceptual framework, supported by stakeholder analysis, for adapting these solutions locally. A detailed feasibility analysis considers technological, economic, social, environmental, and regulatory factors, offering a clear roadmap for implementation. Drawing on lessons from cities facing similar urban mobility challenges, the paper concludes with actionable recommendations and insights for policymakers and urban planners in Kinshasa. This research not only highlights the viability of smart mobility solutions in Kinshasa but also contributes to the broader discourse on sustainable urban development in rapidly growing cities. While smart mobility studies have largely focused on cities with developed infrastructure, there is a gap in understanding how these solutions apply to cities like Kinshasa with different infrastructural and socio-political contexts. Previous research has often overlooked the challenges of integrating smart mobility in rapidly urbanizing cities with underdeveloped transportation systems and financial constraints. This study fills that gap by offering a feasibility analysis tailored to Kinshasa, assessing smart mobility solutions for its traffic congestion and road safety issues. The smart mobility solutions studied—Mobility-as-a-Service (MaaS), car sharing, electric vehicles (EVs), and micro-mobility—were chosen for their ability to address Kinshasa’s key mobility challenges. MaaS reduces reliance on private vehicles, easing congestion and improving public transport. Car sharing offers affordable alternatives to vehicle ownership, essential in a city with income inequality. EVs align with sustainability goals by reducing emissions, while micro-mobility (bikes and e-scooters) improves last-mile connectivity, addressing public transit gaps. These solutions are adaptable to Kinshasa’s context and offer scalable, sustainable improvements for urban mobility.

To date, there is no developed and validated way to assess urban smartness. When evaluating smart city mobility systems, different authors distinguish different indicators. After analysing the evaluation indicators of the transport system presented in the scientific articles, the most relevant and influential indicators were selected. This article develops a hierarchical evaluation model for evaluating a smart city transportation system. The indicators are divided into five groups called “factors”. Several indicators are assigned to each of the listed groups. A hybrid multi-criteria decision-making (MCDM) method was used to calculate the significance of the selected indicators and to compare urban mobility systems. The applied multi-criteria evaluation methods were simple additive weighting (SAW), complex proportional assessment (COPRAS), and technique for order preference by similiarity to ideal solution (TOPSIS). The significance of factors and indicators was determined by expert evaluation methods: the analytic hierarchy process (AHP), direct, when experts evaluate the criteria as a percentage (sum of evaluations of all criteria 100%) and ranking (prioritisation). The evaluation and comparison of mobility systems were performed in two stages: when the multi-criteria evaluation is performed according to the indicators of each factor separately and when performing a comprehensive assessment of the smart mobility system according to the integrated significance of the indicators. A leading city is identified and ranked according to the smartness level. The aim of this article is to create a hierarchical evaluation model of the smart mobility systems, to compare the smartness level of Vilnius, Montreal, and Weimar mobility systems, and to create a ranking.

In recent years, the widespread introduction of bike-sharing systems in China has had a profound impact on the daily lives of Chinese citizens and the development of the urban transport system. This article attempts to analyse the impact of this phenomenon on sustainability. The gradual improvement of related monitoring measures has facilitated the maturation of the bike-sharing industry from the initial stage of uncontrolled growth to the current stage of standardised management. By tracing the global development of bike-sharing systems with a special focus on China, this study sheds light on the platformisation of bicycles and their multiple impacts on technical, environmental, cultural, economic and social sustainability. Furthermore, this study provides a comprehensive analysis of the transformation of bicycles in China and highlights the diverse impacts of platform-based bike sharing on various facets of Chinese society. The development of different bike-sharing systems in China is a unique and crucial case to interpret the current situation of bike sharing and imagine future scenarios. In contrast to the prevailing and uniform approach derived from the experiences of Northern European countries, the massive and widespread experimentation with different bike-sharing schemes in China reveals not only potentials and aspects of sustainability, innovation, and urban and social regeneration, but also some hidden shadows similar to those in small-scale contexts such as Northern Europe. Furthermore, this study emphasises the crucial role of sustainable development principles in addressing the urban challenges specific to China.

The arrangement of last-mile services is playing an increasingly important role in making public transport more accessible. We study the use of ridesharing in satisfying last-mile demands with the assumption that demands are uncertain and come in batches. The most important contribution of our paper is a two-level Markov decision process framework that is capable of generating a vehicle-dispatching policy for the aforementioned service. We introduce state summarization, representative states, and sample-based cost estimation as major approximation techniques in making our approach scalable. We show that our approach converges and solution quality improves as sample size increases. We also apply our approach to a series of case studies derived from a real-world public transport data set in Singapore. By examining three distinctive demand profiles, we show that our approach performs best when the distribution is less uniform and the planning area is large. We also demonstrate that a parallel implementation can further improve the performance of our solution approach. The online appendix is available at https://doi.org/10.1287/trsc.2018.0840 .

UAVs will present significant air traffic in the urban airspace in the future, which brings new challenges to urban air traffic management and control. This paper presents an air route design scheme for multi-rotor UAVs in urban airspace to enable UAV operations at orderly levels. The air routes include legs and intersections, which are the three-dimensional channels of UAV flight. Based on the concept of structured and layered urban airspace, the cylindrical pipeline flight leg is designed, and the operation concept, characteristic parameters and flight procedures of along-road and roundabout intersections are proposed. By defining UAV conflict risk and intersection service level metrics, the operation situation of UAVs is quantitatively evaluated. Taking an urban transportation scenario as a case, the proposed route design scheme is simulated in different scale UAV operating scenarios. The results show that the number of UAVs at the intersection is positively correlated with the conflict probability, the number of crossing routes is negatively correlated with the intersection passing rate, and the UAV arrival rate is positively correlated with the intersection average passing time. The along-road type intersection is suitable for the area with fewer crossing routes and sparse UAVs, while the roundabout type intersection is adapted for the area with more crossing routes and dense UAVs. This research provides a new idea for urban UAV air route design, which is helpful in promoting the standardized management of UAVs and accelerating the integration of UAVs into urban airspace.