Data mining methodology for obtaining epidemiological data in the context of road transport systems.

Millions of people use public transport systems daily, hence their interest for the epidemiology of respiratory infectious diseases, both from a scientific and a health control point of view. This article presents a methodology for obtaining epidemiological information on these types of diseases in the context of a public road transport system. This epidemiological information is based on an estimation of interactions with risk of infection between users of the public transport system. The methodology is novel in its aim since, to the best of our knowledge, there is no previous study in the context of epidemiology and public transport systems that addresses this challenge. The information is obtained by mining the data generated from trips made by transport users who use contactless cards as a means of payment. Data mining therefore underpins the methodology. One achievement of the methodology is that it is a comprehensive approach, since, starting from a formalisation of the problem based on epidemiological concepts and the transport activity itself, all the necessary steps to obtain the required epidemiological knowledge are described and implemented. This includes the estimation of data that are generally unknown in the context of public transport systems, but that are required to generate the desired results. The outcome is useful epidemiological data based on a complete and reliable description of all estimated potentially infectious interactions between users of the transport system. The methodology can be implemented using a variety of initial specifications: epidemiological, temporal, geographic, inter alia. Another feature of the methodology is that with the information it provides, epidemiological studies can be carried out involving a large number of people, producing large samples of interactions obtained over long periods of time, thereby making it possible to carry out comparative studies. Moreover, a real use case is described, in which the methodology is applied to a road transport system that annually moves around 20 million passengers, in a period that predates the COVID-19 pandemic. The results have made it possible to identify the group of users most exposed to infection, although they are not the largest group. Finally, it is estimated that the application of a seat allocation strategy that minimises the risk of infection reduces the risk by 50%.

India's public transportation system: the repercussions of COVID-19

The COVID-19 pandemic has left scars on the Indian public transportation system. In order to regain its original momentum, policymakers will need to assess the barriers hindering the effectiveness of the public transportation sector. In this regard, this article analyzes the various factors affecting the public transportation sector in India and determines their interrelationships. The research is presented in three steps. First, we review the literature to identify the factors that affect the public transportation system in India. Next, we propose an integrated model of grey-DEMATEL and ANP, grey-DANP, to calculate the priority ranking and weight of the factors. The grey-DEMATEL method is used to find the interrelationships among the factors, while ANP determines the local and global weights of the factors to form a priority order. Then, we present the interrelationships in the form of influential relation maps. Furthermore, we provide a sensitivity analysis to enhance the credibility of our study. The paper reveals that governmental regulations are the most influential factors in India's public transportation system. The transportation authorities and policymakers must also focus on improving the financial stability and enhancing the customer's trust in the public transportation system. The framework provided in this paper can be applied to other countries where similar hindrances in the public transportation system have been caused by COVID-19. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Reliability-Oriented Route Generation Algorithm for Multimodal Transport: A Perspective from Supply Chain Reliability Enhancement

Sudden infectious diseases and other malignant events cause excessive costs in the supply chain, particularly in the transportation sector. This issue, along with the uncertainty of the development of global epidemics and the frequency of extreme natural disaster events, continues to provoke discussion and reflection. However, transport systems involve interactions between different modes, which are further complicated by the reliable coupling of multiple modes. Therefore, for the vital subsystem of the supply chain-multimodal transport, in this paper, a heuristic algorithm considering node topology and transport characteristics in a multimodal transport network (MTN): the Reliability Oriented Routing Algorithm (RORA), is proposed based on the super-network and improved k-shell (IKS) algorithm. An empirical case based on the Yangtze River Delta region of China demonstrates that RORA enables a 16% reduction in the boundary value for route failure and a reduction of about 60.58% in the route cost increase compared to the typical cost-optimal algorithm, which means that RORA results in a more reliable routing solution. The analysis of network reliability also shows that the IKS values of the nodes are positively correlated with the reliability of the MTN, and nodes with different modes may have different transport reliabilities (highest for highways and lowest for inland waterways). These findings inform a reliability-based scheme and network design for multimodal transportation. Practical Applications: Recently, the COVID-19 epidemic and the frequency of natural disasters such as floods have prompted scholars to consider transport reliability. Therefore, efficient and reliable cargo transportation solutions are crucial for the sustainable development of multimodal transport in a country or region. In this paper, a new algorithm is designed to obtain a reliability-oriented optimal routing scheme for multimodal transport. Using actual data from the Yangtze River Delta region of China as an example for experimental analysis, we obtain that: (1) the proposed algorithm is superior in terms of efficiency, accuracy, and route reliability, which means that the new algorithm can quickly find more reliable routing solutions in the event of urban transport infrastructure failures;and (2) highway hubs have the greatest transport reliability. Conversely, inland waterway hubs are the least reliable. The influence of national highways and railways on the multimodal transport system is unbalanced. These findings provide decision support to transport policymakers on reliability. For example, transport investments should be focused on building large infrastructure and increasing transport capacity, strengthening the connectivity of inland waterway hubs to hubs with higher transport advantages, and leveraging the role of large hubs. © 2023 American Society of Civil Engineers.

Analysis of the Current State of Passenger Traffic as a Component of the Transport System and the Prospects for Its Development

The article examines the current state and prospects for the development of transport and the transport system in Ukraine. The study of the state of development of transport and the transport system of Ukraine in recent years shows unstable dynamics, which is mainly related to the economic and geopolitical crisis in the country, the consequences of the COVID-19 pandemic. The level of transport service for the population of Ukraine is significantly inferior to the indicators of developed countries of the world. A necessary condition for effective development and overcoming the consequences of crisis phenomena in the transport industry, in particular those caused by the COVID-19 pandemic, is the development and modernization of Ukraine's transport infrastructure in accordance with modern technological requirements. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Climate Change and Health, Related to Transport

Transport-related carbon emissions have a wide range of detrimental health effects for the global population. At the same time, they play a key role in the aggravation of climate change which, in itself, is a main threat to human livelihoods and wellbeing. Although the COVID-19 pandemic brought a temporary and unexpected decrease in emissions, maintaining these positive effects, and effectively and permanently decarbonising the sector, still constitutes a substantial challenge, as it requires a radical reconfiguration of lifestyles and cities, with a major reduction in car dependency, long-distance travel, carbon-intensive import-export markets, etc. This chapter explores the strong links between existing high-carbon transport-systems, climate change, and human health in a negative, self-reinforcing cycle, the risks we face if no action is taken and the possibilities we still have to break this negative cycle. © 2021 Elsevier Ltd. All rights reserved

Design and implementation of IoT enabled ultraviolet C(UVC) irradiation-based sanitizer system for public transport with remote monitoring

During the ongoing Covid19 Pandemic, it is a need of the hour to have a fully sanitized public transport system, free from Covid19 virus. Public transport is one of the major segments responsible for the spreading of covid19 like pandemic infections. It is required to sanitize public transport before every new trip. During the Covid19 pandemic, human beings are forced to live with viruses, hence making disinfection a routine work and making disinfection more user-friendly and efficient is the main objective of this research work. Spraying alcohol-based solution inside public transport is not suitable due to fire safety and other reasons. Ultraviolet C (UVC) based disinfection is more suitable in such applications, as disinfection can be done anytime, anywhere without damaging the interiors of the vehicle. It can kill viruses or bacteria in less than 20 seconds and can disinfect any surfaces, seats, or any point of public contact inside any public transport by effectively killing bacteria, fungi, dust mites, viruses, etc. This research paper aims to offer the design and implementation of an Ultraviolet C irradiation-based sanitizer system for the public transport system, which can disinfect the public contact surfaces inside the public transport, to make our travel safe from Covid19 like viruses. The sanitization system is developed using a NODEMCU microcontroller, UVC led arrays, switching circuit, PIR sensor, and mobile app. Ultraviolet sensor is used to read UVC irradiation index inside the transport to measure the effectiveness of the developed system and real-time data is linked with internet cloud for remote monitoring and control. © 2022 IEEE.

Exploring the potential role of bikeshare to complement public transit: The case of San Francisco amid the coronavirus crisis.

The recent worldwide SARS-CoV-2 (COVID-19) pandemic has reshaped the way people live, how they access goods and services, and how they perform various activities. For public transit, there have been health concerns over the potential spread to transit users and transit service staff, which prompted transportation agencies to make decisions about the service, e.g., whether to reduce or temporarily shut down services. These decisions had substantial negative consequences, especially for transit-dependent travelers, and prompted transit users to explore alternative transportation modes, e.g., bikeshare. However, local governments and the public in general have limited information about whether and to what extent bikeshare provides adequate accessibility and mobility to those transit-dependent residents. To fill this gap, this study implemented spatial and visual analytics to identify how micro-mobility in the form of bikesharing has addressed travel needs and improved the resilience of transportation systems. The study analyzed the case of San Francisco in California, USA, focusing on three phases of the pandemic, i.e., initial confirmed cases, shelter-in-place, and initial changes in transit service. First, the authors implemented unsupervised machine learning clustering methods to identify different bikesharing trip types. Moreover, through spatiotemporally matching bikeshare ridership data with transit service information (i.e., General Transit Feed Specification, GTFS) using the tool called OpenTripPlanner (OTP), the authors studied the travel behavior changes (e.g., the proportion of bikeshare trips that could be finished by transit) for different bikeshare trip types over the three specified phases. This study revealed that during the pandemic, more casual users joined bikeshare programs; the proportion of recreation-related bikeshare trips increased; and routine trips became more prevalent considering that docking-station-based bikeshare trips increased. More importantly, the analyses also provided insights about mode substitution, because the analyses identified an increase in dockless bikeshare trips in areas with no or limited transit coverage.

COVID-19 and suburban public transport in the conditions of the Czech Republic.

This article focuses on possible approaches to safe regional public transport during the COVID-19 pandemic. The purposes of the research are examination the conditions for ensuring safe transport and the impact on the planning of transport services. The result is an assessment of the operation of regional public transport, consisting of the possibility of maintaining safe distances in public transport. Authors work on suburban transport cases in selected regions of the Czech Republic (Prague and Moravian-Silesian Region). Census devices in public transport, periodical transport surveys, Google mobility reports and data on fare sales from regional transport were used as data sources. Emphasis is placed on a safe distance between commuters, this condition leads to lower occupancy of the vehicle while maintaining the capacity of the vehicles. The value of this new occupancy is determined for selected vehicles and the coefficient that represents the maximum occupancy level to ensure safe transport is established. The capacity of the connections is examined in the period before and during the COVID-19 pandemic. Compared to the period before COVID-19, the daily variation of passengers is expected to change significantly, leading to different occupancy rates during the day.

Transport System of the Smart City Concept vs Pandemics: COVID-19 Case Study

In this article, we analysed the situation during the pandemics of COVID-19 virus in the Slovak Republic. We summarized measures within transport system, that Slovak Republic took in an attempt to soften the impact of the virus and to minimize its spread. We found out that these measures and the swiftness of their adoption had strong influence on flattening the curve of virus spreading. The main contribution of this article is in deeper look into possibilities of a smart transport system, aimed to identify, what more could the smart transport system offer to help in a fight of the country against spreading virus. For this purpose, we need to remind our previous work, where we described concept Smart City, concept Safe City, and their systems. One of these systems is system smart transport, and its description in previous work was the base ground for our design of additional solutions, improving safety in the time of pandemics. Therefore, this article will start with description of system Safe City and system smart transport, followed by examination of the case, evaluation of adopted measures, and proposal of additional measures. The focus of proposed measures will be given to the original design of mass transport system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

MaaS (Mobility as a Service) market futures explored

The term Mobility as a Service (MaaS) refers to a single interface, fully integrated and customised transport service. Whilst the technological barriers to implementing MaaS are steadily being overcome, less is known about how the MaaS eco-system might evolve. This paper unpicks the MaaS concept in light of broader societal trends to suggest how it could evolve and offers insights for practitioners and policy makers. The paper draws on relevant literature, together with discussions with stakeholders, to better understand how MaaS has emerged. It then constructs four future MaaS market scenarios and identifies implications. It is concluded that current expectations of how the MaaS concept may evolve are limited in their understanding of how the transport system could change should MaaS be adopted on a wide scale. The major challenges for policy makers will likely relate to balancing the promised benefits offered with issues such as safety (including bio-safety in our post Covid-19 world), data security and privacy, equity and the threat of dominant suppliers distorting the marketplace. Together, these insights suggest that the MaaS reality may be messy and difficult to manage, and that future transport systems might look very different to now.

Study of Different Seat Allocation Strategies to Reduce the Risk of Contagion Among Passengers in a Public Road Transport System

As a result of the COVID-19 pandemic, public transport systems suffered a significant reduction in passengers due to the suppression of services and reduced vehicle capacity. This reduction jeopardized their role as facilitators of sustainable mobility, causing large economic losses to public transport operators. Therefore, an intelligent management aimed at reducing the risk of contagion among its users is an aspect of interest for public transport operators and a challenge from a scientific point of view. This paper presents the results of a study aimed at analyzing the effect of different seat allocation strategies on the risk of contagion among passengers. Starting from a formalization of the problem based on epidemiological and public transport entities, the methodology employed, based on Data Mining, makes use of simulation processes to analyze the effect of these strategies. The paper presents the results obtained by analyzing a route of a public road passenger transport operator. The results allow us to evaluate the risk of contagion of different seat allocation strategies and to evaluate how this risk varies according to the number of passengers who have traveled on a vehicle journey. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Changes in Transportation due to the Influence of SARS-CoV-2

2020 and 2021 were years dominated by COVID-19. Fear of an unknown pathogen, circulating conspiracy theories, introduced administrative restrictions and their loosening significantly influenced social life and all economic sectors. Large changes were also observed in transport, manifested by a decrease in the transport volume and lower revenues. The article presents the changes on Polish transport market and shows the correlation between their level and the introduced sanitary restrictions. The analysis of the available data revealed: fragility of the transport system and its lack of resistance to unexpected events;relatively quick adaptation/overcoming of difficulties on the railways, especially in the transport of goods;changes in social mobility;differences in individual countries, and draw the conclusions about: the possibility of quick adaptation of rail transport in crisis situations;the existing transport potential in the railway sector;the need to adopt solutions that make transport immune to unexpected events. The article uses data obtained as a result of a review of world literature, studies of many institutions and organizations as well as obtained from the Office of Rail Transport and individual carriers. © 2022 Kaunas University of Technology. All rights reserved.

Proposal of the Systematic Measures to Support Rail Passenger Transport During the Pandemic Period

Efficient, high-quality and competitive urban, suburban and long-distance rail passenger transport is very important and key public passenger transport system that needs to be constantly developed as a whole. However, the demand for public passenger transport has been significantly lower than the long-term trend so far since March 2020, mainly due to the pandemic caused by COVID-19. The situation improved slightly in the summer months of 2020 and 2021, but traffic flows are still not at the required level before the pandemic period. Therefore, it is now necessary to take several measures for the revitalization and conceptual systematic development of rail passenger transport as well. This is necessary, in particular, to re-attract passengers to public passenger transport and also to ensure better and more efficient transport services in the particular regions. This paper analyses the current status of the measures that have been introduced in rail passenger transport in the Slovak Republic during the individual waves of the COVID-19 pandemic. Subsequently there are proposed strategic solutions and long-term systematic measures that can be implemented in pandemic times in order to maintain safe and attractive rail passenger transport. © 2022 Kaunas University of Technology. All rights reserved.

Analysis of COVID-19 Impact on Public Transport Usage based on Smart Card Data-A Regional Case Study in Australia

The outbreak of COVID-19 has made a profound impact on mobility, especially for public transport users. Extensive research has been conducted on the change of travel patterns in major cities where public transport systems have been well developed and heavily used. However, in small cities, the public transport network is relatively sparse, especially in suburban areas, which makes the corresponding travel patterns differ from those in major cities. Therefore, proper investigation of the public transport usage in such small cities is still needed, especially under the COVID-19 impact. This paper aims to reveal the change of public transport users' travel patterns based on a comparative study of public transport usage Pre-COVID and during the COVID-19 period. The Illawarra, a coastal region close to Sydney in Australia is used as a case study. Smart card data is used to reveal relevant changes in both intraregion (in the Illawarra) and inter-region (between the Illawarra and Sydney) travels in consideration of heterogeneous user groups. The results show a significant decrease (around 47%) in public transport ridership by both train and bus. However, compared to intra-region ridership, the inter-region trips by train drop much more (around 62%). Moreover, heterogeneous age group passengers show different changes after the COVID-19 outbreak. The research findings are expected to provide valuable suggestions for policy making and public transport service adjustment when a similar crisis occurs again. © 2022 IEEE.

Model predictive control of bus platoons in a circular route considering dispatching, holding and boarding limits

Public transport forms the backbone of the city's operation. Proper planning and investment of public transport can create additional jobs to revitalize and recover cities from covid-19. In this paper, we propose a combined dispatching-operation bus model predictive control strategy, where a rolling horizon mechanism is adopted to control the bus system in a real-time manner. Either a bus platoon or a single bus is allowed to be dispatched in each trip, and bus re-dispatching is captured in the system to realistically reflect the real-world. Also, the additional bus initial constraints allow control to be applied at any time when buses are either driving on the road or loading at the stop. Model complexity is investigated by solving the optimization problem under various prediction horizons, number of buses and bus stops. Furthermore, the comparison experiment with a high-frequency fixed dispatching method is performed on the Singapore bus line 179A developed in SUMO simulator to illustrate the effectiveness of the proposed method. © 2022 IEEE.

Using Data Mining to Estimate Patterns of Contagion-Risk Interactions in an Intercity Public Road Transport System

The COVID-19 pandemic has had very negative effects on public transport systems. These effects have compromised the role they should play as enablers of social equity and environmentally sustainable mobility and have caused serious economic losses for public transport operators. For this reason, in the context of pandemics, meaningful epidemiological information gathered in the specific framework of these systems is of great interest. This article presents the findings of an investigation into the risk of transmission of a respiratory infectious disease in an intercity road transport system that carries millions of passengers annually. To achieve this objective, a data mining methodology was used to generate the data required to ascertain the level of risk. Using this methodology, the occupancy of vehicle seats by passengers was simulated using two different strategies. The first is an empirical approach to the behaviour of passengers when occupying a free seat and the second attempts to minimise the risk of contagion. For each of these strategies, the interactions with risk of infection between passengers were estimated, the patterns of these interactions on the different routes of the transport system were obtained using k-means clustering technique, and the impact of the strategies was analysed.

An Analysis of the Integration of DRT Services with Local Public Transport in Post-pandemic Period: Some of the Preliminary Insights in the Italian Context

Italy was one of the first country in Europe which was severely affected by COVID-19 pandemic. Several critical issues emerged during the different pandemic phases, especially in the health and mobility sector. Restrictions on public transport reduced the supply of transport, highlighting the need to rethink complementary transport systems. Since May 2020, in the post-lockdown phase, the provision of local public transport has been based on ordinary services, such as bus services, which are mainly intended to meet the needs of systematic travel between the places of residence and work on main development routes of the territory. These services have undergone reductions both in the on-board capacity and in some cases the complete elimination of transit routes. The rebalancing in favour of sustainable modes of transport and the reduction of the share of road mobility is pursued through the encouragement of ad-hoc measures aimed at balancing-off the supply-demand mechanism and improving the quality of services. The application of an on-demand responsive transit system has the ability to improve the transit needs in order to reach the places where personal or family services are provided or to enjoy the resources distributed within desired territory. In Italy since March 2020, new areas of weak demand for transport have been created, i.e. areas with a certain number of users that need to be transferred to and from places that have generally never had access to public transport or have had it restricted. The Demand Responsive Transport (DRT) system is, therefore, used in both urban and suburban areas, allowing even those who do not have their own means of transport (for example, disadvantaged social categories or users with a short stay in the area) or who are suitably equipped (people with reduced or no motor skills), to move around in areas easily. The present work focuses on an analysis of the current state of affairs, starting from the literature and regulations concerning the diffusion of the DRT systems in Italy, and offers some ideas for the optimisation of an integrated public transport service. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Logistics of critical supply and resilience during the covid-19 pandemic in Norway

The covid-19 pandemic has challenged the logistics of critical supplies such as food, fuel, and necessary medical supplies. A research project was executed to document how regional actors in the transport sector handle the logistic challenges during the pandemic in 2020, in Mid-Norway. Key research questions were: (1) How is demand and logistics impacted by the pandemic (especially on critical supplies);(2) What is the impact on and between transport modes (e.g. air, sea, road, rail), and their ability to operate as normal;and (3) What is the effect on Norwegian import and export activities? This paper presents the results of a limited literature review on the risks of a pandemic on critical supplies, and systematic interviews of key actors in transportation and logistics. Eleven candidates were interviewed in the period April to June 2020 and then analysed. In addition, nine candidates were approached for more informal conversations. All candidates were interviewed minimum two times to identify possible effects from the pandemic over a period. Key findings show that logistics of critical supplies have been identified as an area in national risk assessments but has not been prioritized through actual action plans. Furthermore, the project discovered poor emergency preparedness and poor preparedness in logistics operations, although mitigated by the ability to improvise and use of existing resources to ensure necessary supply of critical items. © ESREL 2021. Published by Research Publishing, Singapore.

Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma.

Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.

Digitalization of railway service with the use of post-covid-19 events

Every year there is a digitalization of transport systems where it is discussed how stations will play an important role in the digital railway revolution and highlights a project that aims to accelerate the adoption of new technologies. The world of transport is undergoing a digital revolution and railway stations may be a key platform for the implementation of new innovations. A project undertaken by the transport is seeking to accelerate the adoption of new technologies in this space. New technologies, an increased focus on integrated travel solutions and the need to maximise capacity across the rail network to cope with demand, is placing a new emphasis on innovation in railway stations. Every year, billions of people travel by rail around the world. But as passenger numbers continue to grow, and the expectations of passengers continue to be more demanding, the pressure on rail organisations to deliver high-quality passenger journeys increases. Transport for Wales (TfW) has today launched its new smartphone app, providing enhanced features and, for the first time, a bilingual service. Passenger rail has been one of the most impacted sectors by the COVID-19 pandemic, suffering a catastophic decrease in passenger numbers since March 2020. © 2022 Elsevier B.V.. All rights reserved.