This essay analyses the possible impact that COVID-19 will have on the transport sector. It also gives the prospect on how the sector should approach the “new normal” which will follow the current health emergency and be resilient in case of future outbreaks. The paper identifies several impacts that are already taking place in different instances such as the global consumers’ behaviour. Due to the current lockdown situation interaction between producers and consumers has changed radically, and the supply chain had to adapt to cover necessities of citizens. The effects of the outbreak have been profound in consumption, however a growth in eCommerce and digital services have gained in importance and it is supposed to continue growing. The pandemic also had effects on the transport sector, to the point that a new paradigm of mobility will be necessary to meet environmental demands. The crisis halted passengers’ mobility and limited air and sea freight capacity significantly. On the contrary, long-distance trans-Eurasian rail lines have been untouched. The pandemic had positive impacts on the environment as well. However, the trend of low production of GHG emission is expected to reverse course once containment measures are lifted. Transport will have an important role in the predicted rebound effect of GHG emissions; thus, the development of green new mobility is essential. Analysing the forecast of the transport sector, railways will have distinct advantages over other transport modes both during the acute phase of the pandemic and the “new normal”. On the other hand, underuse of the rail sector can lead to a collapse of the urban transport system. Lastly, this paper introduces the concept of 5 “R” as the necessary steps the rail sector needs to undertake to play a significant role in tomorrow’s mobility. These steps are Resilience, Return, Reimagination, Reform, and Research. In particular, the paper highlights research needs which are considered essential in enhancing rail competitiveness. In conclusion, this paper reminds that this historic event must be considered as an opportunity to truly establish rail as the backbone of the European sustainable mobility.

To slow down the spread of the Coronavirus, the population has been instructed to stay at home if possible. This measure consequently has a major impact on our daily mobility behaviour. But who is being affected, and how? The MOBIS-COVID-19 research project, an initiative of ETH Zurich and the University of Basel, is a continuation of the original MOBIS study. The aim of the project is to get a picture of how the crisis is affecting mobility and everyday life in Switzerland.

In response to the Coronavirus disease (COVID-19) outbreak and the Transportation Research Board’s (TRB) urgent need for work related to transportation and pandemics, this paper contributes with a sense of urgency and provides a starting point for research on the topic. The main goal of this paper is to support transportation researchers and the TRB community during this COVID-19 pandemic by reviewing the performance of software models used for extracting large-scale data from Twitter streams related to COVID-19. The study extends the previous research efforts in social media data mining by providing a review of contemporary tools, including their computing maturity and their potential usefulness. The paper also includes an open repository for the processed data frames to facilitate the quick development of new transportation research studies. The output of this work is recommended to be used by the TRB community when deciding to further investigate topics related to COVID-19 and social media data mining tools.

To slow down the spread of the Coronavirus, the population has been instructed to stay at home if possible. This measure consequently has a major impact on our daily mobility behaviour. But who is being affected, and how? The MOBIS-COVID-19 research project, an initiative of ETH Zurich and the University of Basel, is a continuation of the original MOBIS study. The aim of the project is to get a picture of how the crisis is affecting mobility and everyday life in Switzerland.

To slow down the spread of the Coronavirus, the population has been instructed to stay at home if possible. This measure consequently has a major impact on our daily mobility behaviour. But who is being affected, and how? The MOBIS-COVID-19 research project, an initiative of ETH Zurich and the University of Basel, is a continuation of the original MOBIS study. The aim of the project is to get a picture of how the crisis is affecting mobility and everyday life in Switzerland.

The COVID-19 pandemic has plagued the world for months. The U.S. has taken measures to counter it. On a daily basis, newly confirmed cases have been reported. In the early days, these numbers showed an increasing trend. Recently, the numbers have been generally flattened out. This report tries to estimate the hidden number of currently alive infections in the population by using the confirmed cases. A major result indicates an existing infections estimate at about 10-50 times the daily confirmed new cases, with the stringent social distancing policy tipping to the upper end of this range. It clarifies the relationship between the infection rate and the test rate to put the epidemic under control, which says that the test rate shall keep up at the same pace as infection rate to prevent an outbreak. This relationship is meaningful in the wake of business re-opening in the U.S. and the world. The report also reveals the connections of all the measures taken to the epidemic spread. A stratified sampling method is proposed to add to the current tool kits of epidemic control. Again, this report is a summary of some straight observations and thoughts, not through a thorough study backed with field data. The results appear obvious and suitable for general education to interested policymakers and the public.

Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types. This paper proposes a new method that uses an improved version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. This method uses the Gaussian cumulative density function as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of different noise conditions. This method proved to be time and cost-efficient as it took less than 3.15 seconds per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to determine the detection results. This makes the model a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of low to severe-level cracks (Accuracy = 97.3%, Precision = 79.21%, Recall= 89.18% and F1 score = 83.9%).

To slow down the spread of the Coronavirus, the population has been instructed to stay at home if possible. This measure consequently has a major impact on our daily mobility behaviour. But who is being affected, and how? The MOBIS-COVID-19 research project, an initiative of ETH Zurich and the University of Basel, is a continuation of the original MOBIS study. The aim of the project is to get a picture of how the crisis is affecting mobility and everyday life in Switzerland.

This article provides a curated list of resources regarding COVID-19 - Coronavirus and the marine transportation system which includes ocean shipping, harbor operations, seaports, ferry systems, cruise ships, offshore industries, barge operations, and inland waterway system.

This paper provides information and links to resources concerning public transportation and COVID-19.

Support for transportation planning and systems during the Coronavirus outbreak.

This paper investigates the perceptions of various tourism industries’ stakeholders regarding the readiness of the airlines to handle growing numbers of baby boomer air travellers; within an Australian context. A qualitative research methodology was applied, extracting data from 32 in-depth interviews. The views of the stakeholders in regard to the readiness of the civil aviation industry to handle the increasing numbers of baby boomers flying were complex, varied and fragmented; and were compared to existing literature. It provides a categorisation of issues on which further quantitative or stakeholder research could be based in which airlines may improve their competitive advantage by developing dynamic capabilities to meet the demands of baby boomers. The research was conducted with the approval of Southern Cross University HREC.

This paper provides information and links to resources that address the public and private sector surface transportation impacts of Covid-19.

This paper provides information and links to resources that address the Transportation Infrastructure impacts of Covid-19.

The launch of app-based for-hire vehicle (FHV) services like Uber and Lyft has led to increased mobility options, but the associated increase in vehicular traffic has also presented challenges. In New York City, the number of FHVs tripled between 2010 and 2019, to over one hundred thousand, due to the advent of such companies. This study seeks to understand the impact this increase in FHV usage has had on greenhouse gas emissions in New York City. The study uses data collected by the NYC Taxi and Limousine Commission, which regulates the FHV and taxi industries, and the NYC Mayor’s Office of Sustainability, which publishes the City’s greenhouse gas emissions inventory. The main result of the study is that although the overall per-vehicle efficiency of the fleet has improved, the high growth in registered vehicles has led to emissions from FHVs and taxis increasing 66 percent from 2010 to 2018. Electric vehicles present an opportunity for emissions reductions in New York City’s FHV fleet if barriers to vehicle adoption are adequately addressed and if adoption of EVs does not outpace vehicle attrition.

Abstract: This project aims to identify the impact of the Commonwealth of Virginia government’s response to COVID-19 on travel behavior using naturalistic driving data. While the macroscopic effects of these restrictions on travel are easily observable through substantial shifts in aggregate vehicle volumes on roadways, microscopic observation of unique trips and unique drivers may yield additional useful insights. In an ongoing naturalistic driving study in Southwest Virginia that will be the basis for this investigation, approximately 40 personal vehicles were instrumented with data acquisition systems prior to the first recommendations to stay at home to reduce the rate of spread of the virus. Data collection has continued throughout the pandemic, as restrictions have continued to evolve. Analyzing this driving data over the course of the COVID-19 progression timeline (and associated restrictions on travel and work) for trip volume, trip purpose, trip duration, trip distance, destination variability, and other similar characteristics will help inform how the restrictions have impacted microscopic travel behavior. The data will also be used to provide similar insight into how travel is affected as restrictions are eased.

On March 16, 2020, 3700 participants who completed the MOBIS study between September 2019 and January 2020 were invited to reinstall the GPS Logger and Travel Diary App ‘Catch-My-Day’, developed by MotionTag, to record their mobility behaviour during the period of special measures implemented to control the spread of the Corona Virus. The first 4 weeks of mobility data from the original MOBIS Study is taken for each participant as a baseline against which to compare current mobility patterns. These 4 weeks start place anywhere between 1st September and 15th November, depending on the participant. Only trips in Switzerland are currently considered, although data on cross border travel is available.

On March 16, 2020, 3700 participants who completed the MOBIS study between September 2019 and January 2020 were invited to reinstall the GPS Logger and Travel Diary App ‘Catch-My-Day’, developed by MotionTag, to record their mobility behaviour during the period of special measures implemented to control the spread of the Corona Virus. The first 4 weeks of mobility data from the original MOBIS Study is taken for each participant as a baseline against which to compare current mobility patterns. These 4 weeks start place anywhere between 1st September and 15th November, depending on the participant. Only trips in Switzerland are currently considered, although data on cross border travel is available.