The COVID-19 pandemic has resulted in unprecedented measures changing travel habits in many countries. Many users have started to prefer traveling by private cars, which is against the sustainability policies of the European cities. The necessity of gaining a deeper understanding of road users’ travel habit changes, their feelings on public transport use, and their perceptions of using sustainable urban mobility modes has emerged for future transport planning. Considering these facts, the study in this paper aimed to investigate the influence of the COVID-19 pandemic on road users’ perceptions, needs, and use of sustainable travel modes (i.e., public transport, walking, and cycling). An online survey was carried out during the period from March to May 2020 in the case study area, Sicily of Southern Italy. Regarding the population of the case study, the survey was representative, with 431 individuals. The survey included variables, namely gender, age, city of residence, private car ownership, walking and cycling frequency before and during the pandemic, public transport use frequency for leisure activities before and during the pandemic, need for remote working, and the stress and anxiety perception of using public transport during the pandemic. The analysis started with descriptive statistics and it was followed by correlation analysis in order to explore the characteristics of the dataset and relationship between variables. It was found that these were not statistically significantly correlated at a 95% confidence level. An ordinal regression model was applied for determining the predictions. The results suggested that women were less likely to walk during the pandemic than men. Participants were more likely to resume remote work even after the second phase in order to reduce their daily travel needs and keep their isolation. Participants have expressed a positive opinion on the use of micromobility during pandemic situations. These results can be considered as a basis for sustainable urban planning and a guide for decision-makers who aim to encourage the use of public transport, walking, cycling, and micromobility.

Parking is becoming an expensive resource in almost any major city in the world, and its limited availability is a concurrent cause of urban traffic congestion, and air pollution. In old cities, the structure of the public parking space is rigidly organised and often in the form of on‐street public parking spots. Unfortunately, these public parking spots cannot be reserved beforehand during the pre‐trip phase, and that often lead to a detriment of the quality of urban mobility. Addressing the problem of managing public parking spots is therefore vital to obtain environmentally friendlier and healthier cities. Recent technological progresses in industrial automation, wireless network, sensor communication along with the widespread of high‐range smart devices and new rules concerning financial transactions in mobile payment allow the definition of new intelligent frameworks that enable a convenient management of public parking in urban area, which could improve sustainable urban mobility. In such a scenario, the proposed intelligent parking assistant (IPA) architecture aims at overcoming current public parking management solutions. This study discusses the conceptual architecture of IPA and the first prototype‐scale simulations of the system.

All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted all sectors. In this study, we examine the transport sector with a specific focus on the problem of commuting mode choice and propose a new decision-making approach for the alternative modes after synthesizing expert opinions. As a methodology, a customized model of the recently developed best–worst method (BWM) is used to evaluate mobility choice alternatives. The survey reflects citizens’ opinions toward mobility choices in two Italian cities, Palermo and Catania, before and during the pandemic. BWM is a useful tool for examining mobility choice in big cities. The adopted model is easy to apply and capable of providing effective solutions for sustainable mode choice. The urban context is analyzed considering the importance of transport choices, evaluating the variation of resilience to the changing opinions of users.

Interest towards urban micromobility has been growing lately, and it will now increase further due to the measures used against COVID-19. It is recommended to avoid close contact to prevent contagion. Municipalities have been called to implement wider cycling networks so that people may go to their work place by cycling rather than by using public transport. This paper focused on cycling path design using an infrastructure-building information model (I-BIM). The issue covered was how to connect cost and safety requirements in the first steps of the project. We set a methodology that gives, after identifying the intervention area and defining the available economic resources, the key elements needed to design possible cycle path solutions. It guides the designer step-by-step, starting from basic assumptions related to a cycle path’s location (urban/non-urban), budget (by range), and safety (according to Bicycle Compatibility Index BCI and Bicycle Level of Service (BLOS) index), up to the definition of preferred options in terms of materials to be selected. As a case study, we implemented this methodology in the old city center of Catania in Sicily (Italy), designing a cycle path that connects the city center with the existing cycle path on the coast, while aligning with safety requirements within budget constraints.

In the last few years, numerous research efforts have been conducted to merge the Internet of Things (IoT) with smart city environments. The goal to make a city “smart” is arising as a possible solution to lessen the issues caused by the urban population growth and fast urbanization. Attention also has focused on the pedestrian crossings because they are one of the most dangerous places in the transport field. Information and Communications Technologies (ICT) can undoubtedly be an excellent support in developing infrastructures that can best manage pedestrian crossing. For this reason, this paper introduces a fuzzy logic-based solution able to manage dynamically the traffic lights’ phases in signalized pedestrian crossings. The proposed approach provides the possibility to change the phases of the traffic light taking into account the time of the day and the number of pedestrians about to cross the road. The paper presents a thorough description of the fuzzy logic controller configuration, an in-depth analysis of the application scenario and simulative assessments obtained through Vissim simulations.

The Sustainable Urban Mobility Planning (SUMP) process deals with barriers to improve accessibility and quality of life in urban mobility. Public opinion is highly essential for this process because it presents the real needs of road users. This paper illustrates the influence of public opinion on using Private Mobility Vehicle (PMV) in urban. A survey was carried out with 400 participants in Palermo, Italy. The results suggested that there was heterogeneity in gender and age groups in subcategories which represented people who use, do not use, and completely reject, using PMVs in urban. In addition, it was explored that there was a statistically significant relationship at 95% confidence level between sociodemographic characteristics (gender and age groups) and public opinion on PMV using. Employment status was found as an important parameter in transport planning. It was also showed that there was an inconsistency between local and national results. The results suggested that sociodemographic characteristics and public opinion should be investigated in further studies. In addition, a participatory planning process should be carried out to monitor for reliable evaluation in urban transport planning.