2023

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Open AccessArticle

Distributed Traffic Control Based on Road Network Partitioning Using Normalization Algorithm

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Sustainability 2023, 15(14), 11378; https://doi.org/10.3390/su151411378 - 21 Jul 2023

Viewed by 348

Abstract

With continuous economic development, most urban road networks are facing unprecedented traffic congestion. Centralized traffic control is difficult to achieve, and distributed traffic control based on partitioning a road network into subnetworks is a promising way to alleviate traffic pressure on urban roads. [...] Read more.

With continuous economic development, most urban road networks are facing unprecedented traffic congestion. Centralized traffic control is difficult to achieve, and distributed traffic control based on partitioning a road network into subnetworks is a promising way to alleviate traffic pressure on urban roads. In order to study the differences between different partitioning methods chosen for distributed traffic control, we used the normalization algorithm to partition a part of the road network in Changsha City, and we used the results of the Girvan–Newman algorithm and the manual empirical partitioning method as a control group. Meanwhile, an abstract road network was constructed using VISSIM simulation software based on realistic road network parameters. And then, the different partitioning results were applied to the simulated road network to analyze the control effect. The results of the simulation software show that different partitioning methods have different effects on traffic control at subnetwork boundaries and improve traffic pressure to different degrees. Partitioning the road network into four subnetworks provided the greatest degree of traffic improvement. Overall, the proposed distributed traffic control method effectively improved operational efficiency and alleviated the traffic pressure of the road network. Full article

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Open AccessArticle

Wind Power Interval Prediction via an Integrated Variational Empirical Decomposition Deep Learning Model

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Shuling Zhao

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Sishuo Zhao

Sustainability 2023, 15(7), 6114; https://doi.org/10.3390/su15076114 - 01 Apr 2023

Viewed by 580

Abstract

As global demand for renewable energy increases, wind energy has become an important source of clean energy. However, due to the instability and unpredictability of wind energy, predicting wind power becomes one of the keys to resolving the instability of wind power. The [...] Read more.

As global demand for renewable energy increases, wind energy has become an important source of clean energy. However, due to the instability and unpredictability of wind energy, predicting wind power becomes one of the keys to resolving the instability of wind power. The current point prediction model of wind power output has limitations and randomness in processing information. In order to improve the prediction accuracy and efficiency of wind power, a multi-step interval prediction method (VMD-TCN) is proposed in this article, which uses variational modal decomposition and an improved temporal convolutional network model to predict wind power. Additionally, it introduces attention mechanism, further improving the prediction performance of the model. The method first uses empirical mode decomposition to decompose the wind power generation sequence into six parts and obtains the trend, oscillation and noise components of the output power sequence; then, it optimizes the parameters of the six components, respectively, and uses the interval prediction method combined with the temporal convolutional network to construct a new power prediction model. Experiments show that the proposed method can effectively improve the prediction performance of the power prediction model, and it has strong robustness in interval prediction and high sensitivity to load changes, which can well help power system scheduling and new energy consumption. Full article

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2022

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Open AccessArticle

Spatial Heterogeneity of the Recovery of Road Traffic Volume from the Impact of COVID-19: Evidence from China

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Sustainability 2022, 14(21), 14297; https://doi.org/10.3390/su142114297 - 01 Nov 2022

Viewed by 802

Abstract

The impact of COVID-19 on traffic volume makes it essential to study the spatial heterogeneity and impact mechanisms of the recovery of road traffic volume to promote the sustainability of related industries. As the research method, this study used a principal component analysis [...] Read more.

The impact of COVID-19 on traffic volume makes it essential to study the spatial heterogeneity and impact mechanisms of the recovery of road traffic volume to promote the sustainability of related industries. As the research method, this study used a principal component analysis to evaluate the recovery of road traffic volume in China quantitatively, and further conducted an empirical study using a spatial autocorrelation index and a dynamic spatial panel model. The results show that income has a negative impact on the recovery of road traffic volume, while climate suitability has a positive impact. Economic development and COVID-19 can play moderating and mediating effects, respectively. From the aspect of spatial heterogeneity, the recovery of road traffic volume has a positive spatial spillover effect on the surrounding provinces, while the spread of COVID-19 has a negative short-term indirect spatial spillover effect. Corresponding practical insights are provided for the stakeholders based on the above findings. The results of this study will contribute to the development of effective policies to facilitate the recovery of road traffic volume from the impact of COVID-19 and the revitalization of the transportation industry. Full article

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Open AccessArticle

The Impacts of a COVID-19 Related Lockdown (and Reopening Phases) on Time Use and Mobility for Activities in Austria—Results from a Multi-Wave Combined Survey

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Lukas Hartwig

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Reinhard Hössinger

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Yusak Octavius Susilo

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Astrid Gühnemann

Sustainability 2022, 14(12), 7422; https://doi.org/10.3390/su14127422 - 17 Jun 2022

Cited by 5 | Viewed by 1515

Abstract

When activity locations were shut down in the first lockdown to prevent the spread of COVID-19 in Austria, people reduced their trips accordingly. Based on a dataset obtained through a weeklong mobility and activity survey we analyse mobility and time use changes, as [...] Read more.

When activity locations were shut down in the first lockdown to prevent the spread of COVID-19 in Austria, people reduced their trips accordingly. Based on a dataset obtained through a weeklong mobility and activity survey we analyse mobility and time use changes, as well as changes in activity locations and secondary activities. Regression analysis is used to analyse differences in time use changes between socio-demographic groups. We show that trip rates and distances as well as public transport use dropped significantly during the lockdown and did not recover fully in the subsequent opening phase. Former travel time was used for additional leisure, sleep, domestic tasks, and eating in the lockdown, but only the latter two retained their increases in the opening phase. The lockdown resulted in a convergence of time use of socio-demographic groups with formerly different patterns, but the differences reappeared in the opening phase. Our findings are consistent with results from the literature but offer an integrated perspective on mobility and time use not found in either mobility- or time use-focussed studies. We conclude that there is a potential for trip reduction through a shift to virtual performance of activities, but the extent of this shift in post-pandemic times remains unclear. Full article

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2021

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Open AccessArticle

Influence of Disinfectants on Airport Conveyor Belts

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Sustainability 2021, 13(19), 10842; https://doi.org/10.3390/su131910842 - 29 Sep 2021

Cited by 2 | Viewed by 1166

Abstract

The coronavirus disease has influenced almost all of our everyday activities. Traveling and transportation have been influenced significantly and there is no doubt that air transportation has been restricted and therefore reduced considerably. It is predicted that the change back to pre-pandemic conditions [...] Read more.

The coronavirus disease has influenced almost all of our everyday activities. Traveling and transportation have been influenced significantly and there is no doubt that air transportation has been restricted and therefore reduced considerably. It is predicted that the change back to pre-pandemic conditions will take several years, and so it is a reasonable assumption that disinfectants will be used more frequently for a long time. The presented article initially deals with the possible impacts of the pandemic on aircraft infrastructure—namely, on the influence of disinfectants on the rubber materials used, for example, in conveyor belts. The proposed methodology is based on the Weibull analysis for conveyor belt lifetime prediction regarding the impact of disinfectants. The Weibull distribution is a continuous probability distribution that can be applied as a theoretical model for statistical data processing. It was named after Weibull, who suggested shape, scale, and location parameters that made the distribution meaningful and useful. Currently, this distribution is applied in many areas, such as biology, economics, and hydrology. In engineering applications, it can be used for reliability and survival analysis. It is used mainly in cases where failure time is dependent on the operating hours, cycles, or age of the component. In the reliability area, it can be used, for example, to predict the lifetime or failure time of a component. To show the consequences of material changes due to the use of disinfectants, this article also presents a CAE (Computer Aided Engineering) analysis that was used for the evaluation of other hyperelastic material characteristics. This research is based on the results of experimental measurements, during which the influence of the types of disinfectant commonly used for the elimination of the coronavirus disease on airport conveyor belt rubber segments was tested. From the performed analysis, it was found that the influence of disinfectants on the material characteristics, including material hardness, elasticity, and static and dynamic loading, could be significant. Therefore, the probability of mechanical damage to the rubber part of the conveyor belt becomes higher, and time intervals for the maintenance or repair of airport conveyor belts should be considered. Full article

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Open AccessArticle

Global Optimization Algorithm Based on Kriging Using Multi-Point Infill Sampling Criterion and Its Application in Transportation System

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Sustainability 2021, 13(19), 10645; https://doi.org/10.3390/su131910645 - 25 Sep 2021

Cited by 2 | Viewed by 1232

Abstract

Public traffic has a great influence, especially with the background of COVID-19. Solving simulation-based optimization (SO) problem is efficient to study how to improve the performance of public traffic. Global optimization based on Kriging (KGO) is an efficient method for SO; to this [...] Read more.

Public traffic has a great influence, especially with the background of COVID-19. Solving simulation-based optimization (SO) problem is efficient to study how to improve the performance of public traffic. Global optimization based on Kriging (KGO) is an efficient method for SO; to this end, this paper proposes a Kriging-based global optimization using multi-point infill sampling criterion. This method uses an infill sampling criterion which obtains multiple new design points to update the Kriging model through solving the constructed multi-objective optimization problem in each iteration. Then, the typical low-dimensional and high-dimensional nonlinear functions, and a SO based on 445 bus line in Beijing city, are employed to test the performance of our algorithm. Moreover, compared with the KGO based on the famous single-point expected improvement (EI) criterion and the particle swarm algorithm (PSO), our method can obtain better solutions in the same amount or less time. Therefore, the proposed algorithm expresses better optimization performance, and may be more suitable for solving the tricky and expensive simulation problems in real-world traffic problems. Full article

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Open AccessArticle

Optimization Model of Regional Traffic Signs for Inducement at Road Works

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Sustainability 2021, 13(13), 6996; https://doi.org/10.3390/su13136996 - 22 Jun 2021

Cited by 1 | Viewed by 1277

Abstract

A variety of pipelines are distributed under urban roads. The upgrading of pipelines is bound to occupy certain road resources, compress the driving space of motor vehicles for a long time, aggravate the traffic congestion in the construction section, and then affect the [...] Read more.

A variety of pipelines are distributed under urban roads. The upgrading of pipelines is bound to occupy certain road resources, compress the driving space of motor vehicles for a long time, aggravate the traffic congestion in the construction section, and then affect the traffic operation of the whole region. A reasonable layout of traffic signs for inducement to guide the traffic flow in the area where the construction section is located is conducive to promoting a balanced distribution of traffic flow in the regional road network, so as to achieve the reduction of automobile exhaust emissions and the sustainable development of traffic. In this paper, the layout optimization method of regional traffic signs for inducement is proposed. Taking the maximum amount of guidance information that the regional traffic signs can provide as the objective function, and taking the traffic volume, the characteristics of intersection nodes and the standard deviation of road saturation as the independent variables, the layout optimization model of guidance facilities is constructed, which can optimize the layout of traffic guidance signs in the area affected by the construction section, and achieve the goal that the minimum number of facilities can provide the maximum amount of guidance information. The results of the case study show that among the 64 alternative locations where traffic guidance signs can be set in the study area, eight optimal locations are finally determined as the setting points of guidance facilities through this model, and the effective increment of guidance information is the largest at this time. The model proposed in this paper can be used for reference to promote the sustainable development of traffic in the area where the construction section is located. Full article

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Open AccessArticle

Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking

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Sustainability 2021, 13(9), 5146; https://doi.org/10.3390/su13095146 - 04 May 2021

Cited by 8 | Viewed by 1585

Abstract

Lane-changing behavior is one of the most common driving behaviors while driving. Due to the complexity of its operation, vehicle collision accidents are prone to occur when changing lanes. Under the environment of vehicle networking, drivers can obtain more accurate traffic information in [...] Read more.

Lane-changing behavior is one of the most common driving behaviors while driving. Due to the complexity of its operation, vehicle collision accidents are prone to occur when changing lanes. Under the environment of vehicle networking, drivers can obtain more accurate traffic information in time, which can be of great help in terms of improving lane-changing safety. This paper analyzes the core factors that affect the safety of vehicles changing lanes, establishes the weight model of influencing factors of lane-changing behavior using the analytic hierarchy process (AHP), and obtains the calculation method of lane-changing behavior factors (LCBFs). Based on the fuzzy reasoning theory, the headway between the lane-changing vehicle and adjacent vehicles in the target lane was examined, and fuzzy logic lane-changing models were established for both situations (i.e., change to the left and change to the right lane). The fuzzy logic lane-changing models were tested via simulation experiments, and the test results showed that the models have a better warning effect on lane changing (LCBF = 1.5), with an accuracy of more than 90%. Thus, the established model in this paper can provide theoretical support for safety warnings when changing lanes and theoretical support for the sustainable development of transportation safety. Full article

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Open AccessArticle

Analysis on Stability of Roadside Parking System in a Rail-Integrated Transport Hub

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Sustainability 2021, 13(9), 4855; https://doi.org/10.3390/su13094855 - 26 Apr 2021

Viewed by 1401

Abstract

Roadside parking systems plays an important role in the planning and design of parking spaces, parking management and operation, and ensuring the safety of passengers. Firstly, we proposed a traffic wave theory and an avoidance logic algorithm to analyze the interaction mechanism of [...] Read more.

Roadside parking systems plays an important role in the planning and design of parking spaces, parking management and operation, and ensuring the safety of passengers. Firstly, we proposed a traffic wave theory and an avoidance logic algorithm to analyze the interaction mechanism of the roadside parking system in a rail-integrated transport hub. Moreover, we researched the evaluation indexes of the stability of roadside parking systems via two new concepts, namely static roadside parking time and dynamic roadside parking time. We found these improved the algorithm of the time utilization rate of the berth. Secondly, the coupling relationship between parking rate, delay and time utilization of berth was also discussed, and mathematical models of stability of the curb parking system were established. Furthermore, the feasibility of models was verified by multi-agent simulation through the VISSIM simulation platform. Finally, a new rail-integrated transport hub was taken as a practical case and studied alongside the simulation of the stability of curb parking system. Our study concluded that the curb parking system was ultimate stable when the time utilization rate was 37.5% and the parking rate was 91.2%. The results of these studies will provide theoretical support for designing curb parking berths in rail-integrated transport hubs. Full article

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Open AccessArticle

Local Dynamic Path Planning for an Ambulance Based on Driving Risk and Attraction Field

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Sustainability 2021, 13(6), 3194; https://doi.org/10.3390/su13063194 - 15 Mar 2021

Viewed by 1617

Abstract

Path planning is one of the most important aspects for ambulance driving. A local dynamic path planning method based on the potential field theory is presented in this paper. The potential field model includes two components—repulsive potential and attractive potential. Repulsive potential includes [...] Read more.

Path planning is one of the most important aspects for ambulance driving. A local dynamic path planning method based on the potential field theory is presented in this paper. The potential field model includes two components—repulsive potential and attractive potential. Repulsive potential includes road potential, lane potential and obstacle potential. Considering the driving distinction between an ambulance and a regular vehicle, especially in congested traffic, an adaptive potential function for a lane line is constructed in association with traffic conditions. The attractive potential is constructed with target potential, lane-velocity potential and tailgating potential. The design of lane-velocity potential is to characterize the influence of velocity on other lanes so as to prevent unnecessary lane-changing behavior for the sake of time-efficiency. The results obtained from simulation demonstrate that the proposed method yields a good performance for ambulance driving in an urban area, which can provide support for designing an ambulance support system for the ambulance personnel and dispatcher. Full article

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Open AccessPerspective

Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective

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Hafiz Suliman Munawar

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Sustainability 2021, 13(3), 1276; https://doi.org/10.3390/su13031276 - 26 Jan 2021

Cited by 56 | Viewed by 14415

Abstract

The Coronavirus Disease 2019 (COVID-19) is a major virus outbreak of the 21st century. The Australian government and local authorities introduced some drastic strategies and policies to control the outspread of this virus. The policies related to lockdown, quarantine, social distancing, shut down [...] Read more.

The Coronavirus Disease 2019 (COVID-19) is a major virus outbreak of the 21st century. The Australian government and local authorities introduced some drastic strategies and policies to control the outspread of this virus. The policies related to lockdown, quarantine, social distancing, shut down of educational institute, work from home, and international and interstate travel bans significantly affect the lifestyle of citizens and, thus, influence their activity patterns. The transport system is, thus, severely affected due to the COVID-19 related restrictions. This paper analyses how the transport system is impacted because of the policies adopted by the Australian government for the containment of the COVID-19. Three main components of the transport sector are studied. These are air travel, public transport, and freight transport. Various official sources of data such as the official website of the Australian government, Google mobility trends, Apple Mobility trends, and Moovit were consulted along with recently published research articles on COVID-19 and its impacts. The secondary sources of data include databases, web articles, and interviews that were conducted with the stakeholders of transport sectors in Australia to analyse the relationship between COVID-19 prevention measures and the transport system. The results of this study showed reduced demand for transport with the adoption of COVID-19 prevention measures. Declines in revenues in the air, freight, and public transport sectors of the transport industry are also reported. The survey shows that transport sector in Australia is facing a serious financial downfall as the use of public transport has dropped by 80%, a 31.5% drop in revenues earned by International airlines in Australia has been predicted, and a 9.5% reduction in the freight transport by water is expected. The recovery of the transport sector to the pre-pandemic state is only possible with the relaxation of COVID-19 containment policies and financial support by the government. Full article

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Open AccessArticle

Transmission Path Tracking of Maritime COVID-19 Pandemic via Ship Sailing Pattern Mining

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Sustainability 2021, 13(3), 1089; https://doi.org/10.3390/su13031089 - 21 Jan 2021

Cited by 9 | Viewed by 2086

Abstract

Since the spread of the coronavirus disease 2019 (COVID-19) pandemic, the transportation of cargo by ship has been seriously impacted. In order to prevent and control maritime COVID-19 transmission, it is of great significance to track and predict ship sailing behavior. As the [...] Read more.

Since the spread of the coronavirus disease 2019 (COVID-19) pandemic, the transportation of cargo by ship has been seriously impacted. In order to prevent and control maritime COVID-19 transmission, it is of great significance to track and predict ship sailing behavior. As the nodes of cargo ship transportation networks, ports of call can reflect the sailing behavior of the cargo ship. Accurate hierarchical division of ports of call can help to clarify the navigation law of ships with different ship types and scales. For typical cargo ships, ships with deadweight over 10,000 tonnages account for 95.77% of total deadweight, and 592,244 berthing ships’ records were mined from automatic identification system (AIS) from January to October 2020. Considering ship type and ship scale, port hierarchy classification models are constructed to divide these ports into three kinds of specialized ports, including bulk, container, and tanker ports. For all types of specialized ports (considering ship scale), port call probability for corresponding ship type is higher than other ships, positively correlated with the ship deadweight if port scale is bigger than ship scale, and negatively correlated with the ship deadweight if port scale is smaller than ship scale. Moreover, port call probability for its corresponding ship type is positively correlated with ship deadweight, while port call probability for other ship types is negatively correlated with ship deadweight. Results indicate that a specialized port hierarchical clustering algorithm can divide the hierarchical structure of typical cargo ship calling ports, and is an effective method to track the maritime transmission path of the COVID-19 pandemic. Full article

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Open AccessArticle

Exploring the Impact of Climate and Extreme Weather on Fatal Traffic Accidents

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Yajie Zou

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Yue Zhang

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Kai Cheng

Sustainability 2021, 13(1), 390; https://doi.org/10.3390/su13010390 - 04 Jan 2021

Cited by 20 | Viewed by 3538

Abstract

Climate change and the extreme weather have a negative impact on road traffic safety, resulting in severe road traffic accidents. In this study, a negative binomial model and a log-change model are proposed to analyse the impact of various factors on fatal traffic [...] Read more.

Climate change and the extreme weather have a negative impact on road traffic safety, resulting in severe road traffic accidents. In this study, a negative binomial model and a log-change model are proposed to analyse the impact of various factors on fatal traffic accidents. The dataset used in this study includes the fatal traffic accident frequency, social development indicators and climate indicators in California and Arizona. The results show that both models can provide accurate fitting results. Climate variables (i.e., average temperature and standard precipitation 24) can significantly affect the frequency of fatal traffic accidents. Non-climate variables (i.e., beer consumption, rural Vehicle miles travelled ratio, and vehicle performance) also have a significant impact. The modelling results can provide decision-making guidelines for the transportation management agencies to improve road traffic safety. Full article

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2020

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Open AccessArticle

Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network

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Sustainability 2021, 13(1), 147; https://doi.org/10.3390/su13010147 - 25 Dec 2020

Cited by 17 | Viewed by 1941

Abstract

Sustainable growth should not only be beneficial to the shipping industry in the future, but is also an urgent need to respond to resource and environmental crises and strengthen shipping governance. Maritime traffic in Arctic waters is prone to encounter dangerous ice conditions, [...] Read more.

Sustainable growth should not only be beneficial to the shipping industry in the future, but is also an urgent need to respond to resource and environmental crises and strengthen shipping governance. Maritime traffic in Arctic waters is prone to encounter dangerous ice conditions, and it is essential to study the mechanism of ice collision risk formation in relation to ice conditions. Taking the ship-ice collision risk in Arctic waters as the research object, we propose a dynamic assessment model of ship-ice collision risk under sea ice status dynamic association (SDA) effect. By constructing the standard paradigm of risk factor dynamic association (DA) effect, taking SDA as the key association factor. Combing with other risk factors that affect ship-ice collision accidents, the coupling relationship between risk factors were analyzed. Then, using the Bayesian network method to build a ship-ice collision accident dynamic risk assessment model and combing with the ice monitoring data in summer Arctic waters, we screen five ships’ position information on the trans-Arctic route in August. The risk behavior of ship-ice collision accidents on the selected route under SDA is analyzed by model simulation. The research reveal that the degree of SDA is a key related factor for the serious ice condition and the possibility of human error during ship’s navigation, which significantly affects the ship-ice collision risk. The traffic in Arctic waters requires extra vigilance of the SDA effect from no ice threat to ice threat, and continuous ice threat. According to the ship-ice collision risk analysis under the SDA effect and without SDA effect, the difference in risk reasoning results on the five stations of the selected route are 32.69%, −32.33%, −27.64%, −10.26%, and −30.13% respectively. The DA effect can optimize ship-ice collision risk inference problem in Arctic waters. Full article

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Open AccessArticle

Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

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Sustainability 2021, 13(1), 112; https://doi.org/10.3390/su13010112 - 24 Dec 2020

Cited by 4 | Viewed by 1880

Abstract

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas [...] Read more.

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility. Full article

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Open AccessArticle

Data-Driven Approach to Understand the Mobility Patterns of the Portuguese Population during the COVID-19 Pandemic

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Tiago Tamagusko

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Adelino Ferreira

Sustainability 2020, 12(22), 9775; https://doi.org/10.3390/su12229775 - 23 Nov 2020

Cited by 26 | Viewed by 3086

Abstract

SARS-CoV-2 emerged in late 2019. Since then, it has spread to several countries, becoming classified as a pandemic. So far, there is no definitive treatment or vaccine, so the best solution is to prevent transmission between individuals through social distancing. However, it is [...] Read more.

SARS-CoV-2 emerged in late 2019. Since then, it has spread to several countries, becoming classified as a pandemic. So far, there is no definitive treatment or vaccine, so the best solution is to prevent transmission between individuals through social distancing. However, it is not easy to measure the effectiveness of these distance measures. Therefore, this study uses data from Google COVID-19 Community Mobility Reports to understand the Portuguese population’s mobility patterns during the COVID-19 pandemic. In this study, the Rt value was modeled for Portugal. In addition, the changepoint was calculated for the population mobility patterns. Thus, the mobility pattern change was used to understand the impact of social distance measures on the dissemination of COVID-19. As a result, it can be stated that the initial Rt value in Portugal was very close to 3, falling to values close to 1 after 25 days. Social isolation measures were adopted quickly. Furthermore, it was observed that public transport was avoided during the pandemic. Finally, until the emergence of a vaccine or an effective treatment, this is the new normal, and it must be understood that new patterns of mobility, social interaction, and hygiene must be adapted to this reality. Full article

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