Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model

Modeling the resilience of urban mobility when exposed to the COVID-19 pandemic: A qualitative system dynamics approach

In December 2019, coronavirus disease (COVID-19) was detected in Wuhan, China. Due to the rapid spread of the disease, containment measures were adopted, which caused unprecedent shifts in individual mobility. Although some studies explored the impacts of the COVID-19 pandemic on travel patterns and resilience of transport systems based on different analysis techniques, there is a lack of studies addressing the impacts of the pandemic on the sustainability and resilience of urban mobility systems using in-depth and holistic methods, such as system dynamics. This research aims to characterize the dynamics present in urban mobility systems when exposed to pandemics and analyze the changes needed for systems to increase their resilience to pandemics using qualitative system dynamics modeling. The framework comprises the characterization of cause-and-effect relationships and the creation of systems' causal loop diagrams (CLD) in their basic state of functionality, when affected by pandemics, and still operating owing to its resilience. Our findings indicated that the CLD of a resilient system is driven by strategic preparedness and response plans, as well as research and development, which balance the spread of the pandemic and increase support on technological strengths and the activities performed from home.

The impact of the COVID-19 pandemic on the behaviour of bike sharing users

Globally most governments implemented a 'Working from Home' (home office) strategy to contain the spread of the coronavirus in 2020 in order to ensure public safety and minimize the transmission of the virus. Unsurprisingly studies have found that COVID-19 has had a detrimental impact on urban transportation systems; however, the number of shared bicycle riders is progressively growing compared to other modes of public transit. The aim of this study is to investigate the influence of COVID-19 on the usage of shared bicycle systems in order to identify passenger travel patterns and habits. In addition, bicycle rentals are becoming more popular in some locations. This demonstrates that bike sharing as a transport option has a high level of social adaptability and is progressively being adopted by the general population in a fashion that promotes the resilience of transport systems.

The Effects of Barriers and Freight Vehicle Restrictions on Logistics Costs: A Comparison before and during the COVID-19 Pandemic in Brazil

The COVID-19 pandemic exposed the fragility of the supply chains, in which the production, distribution, and transportation systems were disrupted, permanently or temporarily. Despite the enormous influences the pandemic had on transportation systems, no study has yet assessed the extent to which the freight restrictions and barriers influenced logistics costs after the start of the COVID-19 outbreak. However, understanding them is necessary to guide and stimulate public policies that intend to optimize the effects of freight restrictions on logistics costs. Thus, this paper assesses and compares the effects that such barriers in urban freight transport, and the restrictions imposed on freight vehicles, had on logistics costs before and during the pandemic. We surveyed more than 120 logistics professionals in Brazil in both 2018 and 2020/2021, making comparisons using models that were assessed using partial least squares structural equation modelling. The findings suggest that barriers and freight restrictions influenced the logistics costs positively, but such influences reduced during the pandemic. Being aware of the barriers and restrictions that influence logistics costs and of how the pandemic increased the effects of some restrictions is essential for managers to be able make timely and appropriate decisions and to plan and implement initiatives to prevent or reduce costs.

ANN-Based traffic volume prediction models in response to COVID-19 imposed measures

Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with their impact on economy, education, social and recreational activities, and domestic and international travels. Intuitively, the different imposed policies and measures have indirect impacts on urban traffic mobility. As a result of those imposed measures and policies, urban traffic flows have changed. However, those impacts are neither measured nor quantified. Therefore, estimating the impact of these combined yet different policies and measures on urban traffic flows is a challenging task. This paper demonstrates the development of an artificial neural networks (ANN) model which correlates the impact of the imposed response measure and other factors on urban traffic flows. The results show that the adopted ANN model is capable of mapping the complex relationship between traffic flows and the response measures with a high level of accuracy and good performance. The predicted values are closed to the observed ones. They are clustered around the regression line, with a coefficient of determination ( R 2 ) of 0.9761. Furthermore, the developed model can be generalized to determine the anticipated demand levels resulted from imposing any of the response measures in the post-pandemic era. This model can be used to manage traffic during mega-events. It can be also utilized for disaster or emergency situations, where traffic flow estimates are highly required for operational and planning purposes.

Assessing the impact of mobility on the incidence of COVID-19 in Dublin City

COVID-19 has had a major impact on the transport systems around the world. Several transport-related policies were implemented in short period of time to contain the spread of the pandemic. These policies had a major influence on travel behavior and people's perception towards the safety of different modes of transport, especially public transport, thus affecting several sustainable mobility initiatives. To build a resilient and sustainable transport system and to rebuild trust in public transport, it is important to understand the role of mobility in the spread of COVID-19 pandemic. The present study investigates the relationship between mobility and reported COVID-19 infections using data from Dublin city. Different modes of transport including traffic volume, bus passengers, pedestrians and cyclists were considered in the study during a forty week period. Multiple scenarios involving two-week lag and three-week lag of mobility data and COVID-19 infections were considered in building statistical models. Results showed that, 36.2% of the reported COVID-19 infections after a two-week lag and 33% of the infections after a three-week lag. Our research examines the links between movements and COVID-19 numbers, but clearly this was not the only reason for increased case numbers as many other events impacted on increased numbers. The study further discusses the policy implications and strategies for ensuring a resilient and sustainable transport system.

Application of Wasted and Recycled Materials for Production of Stabilized Layers of Road Structures

The construction industry, as one of the most complex sectors, depends on using wasted and recycled materials, timely decision-making, and adequate execution of all activities in supply chains. This paper presents tests of mixtures for cold in-place recycling where existing material is used. In this research, we used cement and bitumen emulsion as well as fly ash, zeolite, slag, and Bakelite. A total of seven mixtures were tested in order to increase sustainability. It was tested the indirect tensile strength and dynamic modulus of elasticity after seven and 28 days for dry specimens, after 28 days for water-saturated specimens and for specimens exposed to frost. After completing the tests using the MEREC (MEthod based on the Removal Effects of Criteria) and CoCoSo (Combined Compromise Solution) multi-criteria model, mixtures were evaluated and ranked in terms of mechanical properties, price, and environmental protection. Considering the ranking of mixtures using the CoCoSo method, the highest quality mixtures, for most combinations of weight factors, are mixtures with slag, mixtures with fly ash, and mixtures with 2% of cement and 2% of bitumen emulsion. Sensitivity analysis was also performed with new simulated values of the criteria in order to determine the individual influence of the criteria on the ranking of mixtures. The conclusions are as follows: the use of bitumen emulsion, cement, waste materials, and other materials in cold recycling would reduce the cost of recycling pavement structures, increase environmental protection, while the mechanical properties of the pavement structures are within acceptable limits.