Short-Duration Crash Modeling to Understand the Impact of Operating Speed on Freeway Crashes During COVID-19

Gaining an understanding of speed–crash relationships is a critical issue in highway safety research. Because of the ongoing pandemic (COVID-19) there has been a reduction in traffic volume, and some early studies explain that speeding in an environment with less traffic is associated with a high number of crashes, especially fatal and serious injury crashes. This study aims to quantify the impact of operating speed on traffic crash occurrences. The study conflated several databases (speed data, roadway inventory data, and crash data) that contain data from Dallas, Texas, spanning from 2018 to 2020, to examine the speed–crash association. Using the negative binomial Lindley regression model, this study showed that the trends of crash prediction models vary over the years (2018, 2019, and 2020) by different injury severity levels (i.e., fatal crashes, fatal and incapacitating injury crashes). The 2020 models show that operating speed measures (i.e., average operating speed) have a significant impact on crash frequencies. The magnitudes of the speed measures show variations across the models at different injury severity levels.

News Media Mining to Explore Speed-Crash-Traffic Association During COVID-19

The COVID-19 pandemic has affected the lives of everyone from almost every perspective. Research communities from many domains have contributed to quantifying and mitigating the influence of the ongoing pandemic. The public depend on news media for reliable information. At the start of the pandemic in March 2020, many news media articles started to report on quieter roads resulting from travel restriction and work from home mandates, but also more excessive speeding and more traffic fatalities. Although the news media’s representation of the crash-speed association is often not based on data-driven safety analysis, the extent to which the media place emphasis on such news content has never been adequately quantified. The current study performed content analysis and text mining (both text network analysis and topic modeling) to explore the representations of speed-crash association in news media (local, national, and international) to provide insights into the generated news content. Findings reveal that topics such as a surge in fatal crashes, careless driving, driving under the influence, law enforcement, and equity issues, as well as impacts on pedestrians and bicyclists, were frequently highlighted by local, national, and international news media during the pandemic era.

Content Analysis on Homelessness Issues at Airports by News Media Mining

The number of homeless people at airports has increased in recent years. As airports are safe, transit-accessible, convenient, and climate-controlled facilities with food and amenities, these places are attractive to homeless people who need a safe and secure place to stay. The main struggle of airports in this regard is maintaining a balance between customers, who are mostly the traveling public, and dealing with homeless people delicately. Moreover, because of their poverty and insufficient or no access to healthcare, these people suffer from physical and mental issues. With the COVID-19 pandemic, this problem became more critical. Many news media outlets started to report on homelessness at airports. News-framing impacts have some contribution in the context of this issue. However, the impact of news coverage on ?airport and homelessness? has not yet been studied. News-framing effects have been identified in the context of tourist destinations. Although many studies have explored homelessness and transit, this issue at airports has not been well studied. This study provides a brief overview of the issue of homelessness in the transportation domain, including transit and aviation. Additionally, this study collected news articles related to ?airport and homelessness? (71 articles) both during the COVID-19 pandemic (March 1, 2020?July 21, 2021) and before the pandemic (before March 1, 2020). These news articles contain around 50,000 words. As the data is unsupervised in nature, a text network analysis was performed to determine the latent information from these textual contents. The findings of this study can shed some light on this scientifically unexplored but widely discussed issue.

Did Operating Speeds During COVID-19 Result in More Fatal and Injury Crashes on Urban Freeways?

Impacts of the COVID-19 pandemic in the transportation arena included less traffic, higher speeds, and higher fatal and injury crash frequencies. Many news media reported on speeding and its impact. However, the majority of these reporting are based on partial or incomplete information. The current study aims to understand the association between speed and crash on the freeways of Dallas (Texas) by collecting data from the National Performance Management Research Dataset, the Texas Department of Transportation?s (TxDOT?s) roadway inventory, and TxDOT?s crash database for 2018?2020. The results show decreasing traffic volume, increasing average operating speed, and increasing fatal and severe crash frequencies per 100?million vehicle miles traveled during 2020 (April?November). This study developed 8-month- and daily-level safety prediction models for fatal and injury crashes. The 8-month-level dataset contains speed measures as an aggregate for the 8-month period. The daily-level database includes operating speeds and fatal and injury crashes at the daily level where segments experiencing fatal and injury crashes were temporally matched with the same segment with the same day of the week and with no fatal and injury crash occurrences. For the 8-month models, average operating speed and speed variability are positively associated with fatal and injury crash frequencies during the COVID period. This association was also found for daily-level models. The findings of this study can help transportation agencies in developing strategies (for example, posted speed limit reconsideration, additional enforcement at specific locations) for crash reduction.

Work from home in the post-COVID world.

The working standard of shared office spaces has evolved in recent years. Due to the ongoing COVID-19 pandemic, many companies have instituted work from home (WFH) policies in accordance with public health guidelines in order to increase social distancing and decrease the spread of COVID-19. As the pandemic and WFH-related policies have continued for more than a year, there has been a rise in people becoming accustomed to the remote environments; however, others are more enthusiastic about returning to in-person work environments, reflecting the desire to restore pre-pandemic environments. As working from home is related to transportation issues such as changing commuting patterns and decreased congestion, motorized trips, and emission, there is a need to explore the extent of public attitudes on this important issue. This study used unique open-source survey data that provides substantial information on this topic. Using an advanced categorical data analysis method known as cluster correspondence analysis, this study identified several key findings. Not having prior WFH experiences, being eager to interact with colleagues, difficulties with adapting to virtual meeting technologies, and challenges with self-discipline while WFH were strongly associated with individuals who refused to continuously WFH at all after the pandemic. Individuals holding a strong view against the seriousness of the COVID-19 pandemic were also largely associated with never choosing WFH during and after the pandemic. For individuals with some prior WFH experiences, the transition to WFH every day in response to the outbreak was much easier, compared to those without prior experiences. Moreover, being forced to WFH during the COVID-19 pandemic positively influences the choice of WFH after the pandemic. The findings of this study will be beneficial to help policymakers and sustainable city planners understand public opinions about WFH.

Chapter 9 - Impact of COVID-19 on industries

The novel coronavirus disease 2019 (COVID-19) in the U.S. is part of the worldwide pandemic of this extremely infectious disease. As of November 2020, the U.S. has experienced 10,200,000 cases and 238,000 COVID-19 fatalities. The pandemic is still ongoing, with around 50,000 new cases and 800 deaths each day. A recent U.S. based report shows that the economic loss due to COVID-19 will be more than $22 trillion. Due to the lockdown and the urgency of a safe re-opening, the impact on different industries varies from state to state. A robust and granular level of analysis is needed to understand the impact of COVID-19 on various industries. This study collected data (before and after COVID-19) from the U.S. Bureau of Labor Statistics (USBLS) to perform a quantitative analysis. Using current employment statistics (CES) data from the USBLS, an observational before-after analysis was conducted by using the difference-in-difference method. The results show the highly-impacted industries, and the temporal patterns of the impact are also evaluated.

Pandemic and Transportation Research: Bibliometric Analysis and Topic Modeling

‘Pandemic and transportation,’ a latent topic, has become of the most discussed topics in recent days due to the extraordinary impacts of COVID-19. The number of studies has been exponentially growing for this topic. It can be noted that transportation is one of the sectors that has been drastically affected by the consequences of COVID-19. As this branch of research is growing fast, it is important to get an overall understanding of the ‘pandemic and transportation’ related studies. This study collected relevant studies on this topic from the past 15 years. This study performed three major tasks: 1) conducted a brief literature review on the related studies, 2) performed bibliometric and scientometric analysis on the collected studies, and 3) developed topic models from the unstructured textual data in paper or report titles and abstracts. The findings show that the research trends in ‘COVID-19’ and ‘pre COVID-19’ studies have some common issues. However, ‘pre COVID-19’ papers are mostly associated with guidelines and strategic planning. As COVID-19 is still an ongoing pandemic, the research topics are mostly associated with impact and consequences. As one of the earlier studies on this topic, this study sheds some insights into the ongoing discussions about ‘pandemic and transportation.’