1,720,979 research outputs found
Going to the Zoo: A comparison of travel time ratios in 21 European cities
No full textEfficient public transport is an essential component of a sustainable transport system. The travel time ratio, i.e. the public transport journey duration divided by the car journey duration of the same trip, can be used to compare the public transport system with the road transport system within and across cities. However, few studies have used the travel time ratio to analyse the efficiency of the public transport system across European cities. The aim of this study was to compare travel time ratios of a typical leisure trip across 21 European capital cities and to examine the association of journey time and travel time ratio with socio-demographic characteristics of cities. For the purpose of this study trips to the local zoo were selected as a leisure time activity that is comparable across cities in Europe. Within 21 European capital cities random start points were selected based on an 8 km service facilities analysis from the zoo. For each start point to zoo trip the duration and distance of the public transport and car journeys was calculated using the Google Maps Directions API. Our analysis showed that in all cities public transport journeys take longer than car journeys, with a mean travel time ratio of 2.61 (range 0.98–5.82). No correlation was found between public transport and car journey duration, suggesting that they are influenced by different factors. However, mixed model analyses found no association between socio-demographic characteristics of the cities and public transport journey times. In contrast, mixed models showed that a decrease in the travel time ratio was associated with a larger population size, higher population density, higher percentage of working population, more urbanized land area and more registered cars. To encourage a modal shift towards sustainable urban transport, we recommend that travel time ratio should be considered in the design of public transport and car infrastructure in cities
Feasibility of a simplified index to improve active mobility infrastructure based on digital survey: the case of Dublin
No full textThe advantages associated with active mobility, i.e. walking and cycling, include not only the possibility of moving in an environmentally friendly way, but also health and economic benefits. Abessing the quality of infrastructures for active mobility should consider aspects related to geometric features, traffic volume and human perception; this can be a time and resources consuming procedure for administrations to be performed on the entire urban area, mostly due to the need to carry out on-site surveys. Based on this premise, the aim of this study is to abess the feasibility of a simplified index for the evaluation of the quality of pedestrian/cycling infrastructure fed by digital survey procedures. The results can be used to provide a first ranking of the roads under study, in order to identify the main criticalities to be analysed through on-site auditing
A multi-objective model to design shared e-kick scooters parking spaces in large urban areas
Full text linkIn recent years, the micromobility and the usage of shared electric kick scooters (e-kscooters) have been constantly growing, especially for systematic and recreational trips in large urban areas. Micromobility might be seen as a well-suited last-mile solution by providing a flexible travel service connection with public transport and MaaS (Mobility as a Service), in general. However, there is a need for implementing adequate regulations regarding safety aspects and shared e-kscooter parking locations, but also for meeting the user requirements. The choice of optimal shared e-kscooter parking locations could help decision-makers to regulate unmanaged dock-less shared e-kscooter parking spots that could generate issues for other road users. To this end, in this paper, a novel multi-objective Micromobility Maximal Coverage Parking Location model (M-MCPL) is developed. The model has been solved by applying an elitist Genetic Algorithm that returns the optimal shared e-kscooter parking locations based on the following objective functions: i) the maximization of the population coverage; ii) the maximization of multimodal accessibility coverage (i.e., bus, railway, and metro modes); iii) the maximization of the attraction coverage considering the most relevant points of interest for each corresponding zone in large urban areas. The proposed M-MCPL model has been applied to the case of Rome (Italy) and results suggest priorities for the shared e-kscooter parking locations design. Furthermore, the proposed model is flexible and can be considered as a decision support tool for decision-makers when planning dedicated services in different large urban areas. For that purpose, we conducted the sensitivity analysis by focusing on the single-objective model in which decision-makers might be interested in providing only high accessibility to transport services or maximizing potential demand
Addressing the public transport ridership/coverage dilemma in small cities: A spatial approach
No full textThis paper presents a spatial approach to support the design of new on-demand flexible transport services in urban areas, characterized by inefficient public transport and modal imbalance in favour of private cars. These services, enabled by new technologies and inspired by the shared mobility paradigm, can complement and improve conventional public transport and reduce car use. The methodology was applied to Acireale, a small town in Southern Italy. A redesign of the existing bus network and its integration with a flexible service was formulated. A scenario analysis was carried out by the evaluation of a simple accessibility measure; the computation of the Gini coefficient was performed to measure the social equity of different scenarios. Results show an increase in equity with a lower coverage of traditional lines and the introduction of the on-demand service. This approach based on easy-to-understand indicators can help the strategic planning of such services, which have the potential to find a trade-off between ridership and coverage as both desirable and conflicting goals in public transport planning
Exploring hybrid models for identifying locations for active mobility pathways using real-time spatial Delphi and GANs
Full text linkAbstract The spatial planning process is considered an extremely complex system, as it comprises different variables that interrelate and interact with each other. Effectively addressing this spatial complexity necessitates a multidisciplinary approach, as unified methodologies may prove insufficient. Specifically, in urban planning, it is increasingly crucial to prioritize bike lanes, bike stations, and pedestrian zones, for functional transportation infrastructures. This approach can enhance cities by improving air quality, reducing emissions, and boosting public health and safety through physical activity and accident prevention. However, implementing these changes requires careful planning, community engagement, and stakeholder collaboration. This paper proposes a hybrid model for identifying optimal locations for bike lanes, bike stations, and pedestrian zones adopting Real-Time Spatial Delphi and Generative Adversarial Networks (GANs). The Real-Time Spatial Delphi is a modified version of the traditional Delphi method that incorporates real-time feedback and visualization of group response in real-time, aiming to achieve a convergence of opinions among experts on the territory. Nevertheless, these judgments are a spatial representation not visible in reality, and with the spread of artificial intelligence models, different implementations can support the planning process, such as the use of GANs. In this case, GANs can be exploited by adopting pre-existing location images resulting from experts’ judgments to illustrate the proposed intervention’s visual impact. To demonstrate the effectiveness of our hybrid model, we apply it to the city of Dublin. The results showcased how the method helps stakeholders, policymakers, and citizens in visualizing the proposed changes and gauging their potential impact with greater precision
On the equity of the x-minute city from the perspective of walkability
Full text linkWalkability and equity in transport are crucial aspects of sustainable mobility and social well-being. The x-minute city concept emphasizes the importance of walkability, by fostering the design of a city where people can easily access their daily needs aiming to reduce reliance on private cars. However, such approaches, which generally rely on the idea of an “average resident” can ignore inequalities amongst people and fail to achieve the goal of building urban environments where everyone can participate in city life regardless of their socio-economic characteristics and vulnerability. In this study we propose an approach to assess the equity of the x-minute city, highlighting the limitations of the current application of the concept. The approach includes the computation of x-minute thresholds based on the walkability of pedestrian paths and considering different users’ needs. Home to school trips and social trips are taken as a reference; equity metrics such as the Lorenz Curve and Gini Index are used to assess how the x-minute city concurs with the transport equity of a city. The results of the assessment can help identify potential disparities in access to key destinations among different user groups, and support evidence-based policy recommendations to promote equitable transportation options. The case study of Bari, Italy, is used to illustrate the application of the method; however, the proposed approach can be replicated in different contexts, contributing to the ongoing discourse on walkability and equity in transport
Exploring the impact of mobility restrictions on the COVID-19 spreading through an agent-based approach
Full text linkBackground: The recent health emergency caused by the COVID-19 pandemic forced people to change their mobility habits, with the reduction of non-essential travels and the promotion online activities. During the first phase of the emergency in 2020, governments considered several mobility restrictions to avoid the pandemic diffusion. However, it is difficult to quantify the actual effects of these restrictions on the virus spreading, especially due to the biased data available. Notwithstanding the big role of data analysis to understand the pandemic phenomenon, it is also important to have more general models capable of predicting the impact of different policy scenarios, including territorial parameters, independently from the available infection data. In this respect, this paper proposes an agent-based model to simulate the impact of mobility restrictions on the spreading of the COVID-19 at a large scale level, by considering different factors that can be attributed to the diffusion and lethality of the virus and population mobility patterns. Methods: The first step of the method includes a zonation of the study area, according to administrative boundaries. A risk index is calculated for each zone considering indicators which can influence the virus spreading and people lethality: mean winter temperature, housing concentration, healthcare density, population mobility, air pollution and the percentage of population over 60 years old. The agent-based model associates the risk index to the agents and determines their “status” (“susceptible”, “infected”, “isolated”, “recovered” or “dead”) by combining the risk index with the mean infection duration, using a SIR-based approach (i.e. susceptible–infective-removed). Results: The study is applied to Italy. Several scenarios based on different mobility restrictions have been simulated, including the one based on the official data (status quo). The main results show that characterizing zones with a risk index allows to adopt local policies with almost the same effectiveness as in the case of restrictions extended to the full study area; scenario simulations return an increase in terms of infected (+20%) and deaths (+25%) with respect to the status quo. These results underline the importance of finding a trade-off between socio-economic benefits and health impact. Conclusions: The reproducibility of the proposed methodology and its scalability allow to apply it to different contexts and at a different administrative level, from the urban scale to a national one. Moreover, the model is able to provide a decision-support tool for the design of strategic plans to contrast pandemics based on respiratory diseases
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