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1.
Transp Policy (Oxf) ; 134: 217-230, 2023 Apr.
Article in English | MEDLINE | ID: mdl-36855673

ABSTRACT

The novel coronavirus (COVID-19) pandemic created an environment where nearly all aspects of mobility changed to ensure the health and safety of the public. The Centers for Disease Control and Prevention (CDC) recommended that people quarantine for 14 days if they were potentially exposed to the virus, stay at least six feet apart from others, and stay at home as much as possible. Delivery via third-party restaurant app, grocery, and package delivery quickly became an essential service. This study assesses customer's changes in use and perceived quality of delivery services in Southwest Virginia, via an online stated-preference survey (n = 423). The responses were analyzed using ordered logit and generalized ordered logit models to identify which population segments had changing delivery behavior and perceptions due to the pandemic. Findings include that before the pandemic, only households with an income greater than $100,000 had a significantly higher demand for package delivery services than those making less than $25,000. During the pandemic, all income brackets had a significantly higher demand for package delivery "weekly" than households with less than a $25,000 income, with a 19.50%, 22.54%, and 45.59% greater chance of use for income levels $25,000 to $50,000, $50,000 to $100,000, and over $100,000, respectively. This trend highlights that package delivery became necessary during the pandemic. Respondents who lived within town limits were statistically significantly more likely to use third-party restaurant delivery apps at least once a week before (3.10%), during (9.20%), and after (4.50%) the pandemic compared to those outside town limits. The results also found people who lived within town limits were 7.77% more likely to be satisfied with delivery services in general than those who lived outside town limits. The findings from this paper identify expanding delivery equity gaps within the population and provide recommendations for policymakers and delivery agencies. Some limitations include that low sample size did not allow for fully segmented models and meant that the study should be considered exploratory in nature.

2.
PLoS One ; 15(12): e0243567, 2020.
Article in English | MEDLINE | ID: mdl-33306711

ABSTRACT

This study explores speed choice behavior of travelers under realistic and fabricated Dynamic Message Signs (DMS) content. Using web-based survey information of 4,302 participants collected by Amazon Mechanical Turk in the United States, we develop a set of multivariate latent-based ordered probit models participants. Results show female, African-Americans, drivers with a disability, elderly, and drivers who trust DMS are likely to comply with the fabricated messages. Drivers who comply with traffic regulations, have a good driving record, and live in rural areas, as well as female drivers are likely to slow down under fabricated messages. We highlight that calling or texting, taking picture, and tuning the radio are distracting activities leading drivers to slow down or stop under fictitious scenarios.


Subject(s)
Choice Behavior/physiology , Distracted Driving/trends , Accidents, Traffic/statistics & numerical data , Adult , Aged , Automobile Driving/statistics & numerical data , Distracted Driving/psychology , Distracted Driving/statistics & numerical data , Female , Humans , Male , Middle Aged , Models, Theoretical , Safety , Surveys and Questionnaires , Text Messaging , United States
3.
J Safety Res ; 62: 1-12, 2017 09.
Article in English | MEDLINE | ID: mdl-28882255

ABSTRACT

INTRODUCTION: Animal-vehicle collisions (AVCs) can result in serious injury and death to drivers, animals' death, and significant economic costs. However, the cost effectiveness of the majority of AVC mitigation measures is a significant issue. METHOD: A mobile-based data collection effort was deployed to measure signs under the Utah Department of Transportation's (UDOT) jurisdiction. The crash data were obtained from the UDOT risk management database. ArcGIS was employed to link these two data sets and extract animal-related crashes and signs. An algorithm was developed to process the data and identify AVCs that occurred within sign recognition distance. Kernel density estimation (KDE) technique was applied to identify potential crash hotspots. RESULTS: Only 2% of AVCs occurred within the recognition distance of animal crossing signs. Almost 58% of animal-related crashes took place on the Interstate and U.S. highways, wherein only 30% of animal crossing signs were installed. State routes with a higher average number of signs experienced a lower number of AVCs per mile. The differences between AVCs that occurred within versus outside of sign recognition distance were not statistically significant regarding crash severity, time of crash, weather condition, driver age, vehicle speed, and type of animal. It is more likely that drivers become accustomed to deer crossing signs than cow signs. CONCLUSIONS: Based on the historical crash data and landscape structure, with attention given to the low cost safety improvement methods, a combination of different types of AVC mitigation measures can be developed to reduce the number of animal-related crashes. After an in-depth analysis of AVC data, warning traffic signs, coupled with other low cost mitigation countermeasures can be successfully placed in areas with higher priority or in critical areas. Practical applications: The findings of this study assist transportation agencies in developing more efficient mitigation measures against AVCs.


Subject(s)
Accident Prevention/economics , Accidents, Traffic/prevention & control , Cost-Benefit Analysis , Location Directories and Signs , Safety/economics , Animals , Cattle , Deer , Humans , Utah
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