Type | Journal Article |
---|---|
Author | Aoyong Li |
Author | Pengxiang Zhao |
Author | Xintao Liu |
Author | Ali Mansourian |
Author | Kay W. Axhausen |
Author | Xiaobo Qu |
URL | https://www.sciencedirect.com/science/article/pii/S1361920922000591 |
Volume | 105 |
Pages | 103229 |
Publication | Transportation Research Part D: Transport and Environment |
Date | 2022-04-01 |
Journal Abbr | Transportation Research Part D: Transport and Environment |
DOI | 10.1016/j.trd.2022.103229 |
Library Catalog | ScienceDirect |
Language | en |
Abstract | Although e-scooter sharing has become increasingly attractive, little attention has been paid to a comprehensive comparison of e-scooter sharing mobility in multiple cities. To fill this gap, we conduct a comparative study to reveal the similarity and difference of e-scooter sharing mobility by collecting and analyzing vehicle availability data from 30 European cities during post COVID-19 pandemic. The comparisons are implemented from four perspectives, including temporal trip patterns, statistical characteristics (i.e., trip distance and duration), utilization efficiency, and wasted electricity during idle time. Results suggest that the similarity and difference co-exist between e-scooter sharing services in the cities, and utilization efficiency is significantly related with the number of e-scooters per person and per unit area. Surprisingly, on average nearly 33% of electricity are wasted during idle time in these cities. These research findings can be beneficial to further optimizing e-scooter sharing mobility services for transportation planners and micro-mobility operators. |
Date Added | 4/4/2022, 9:48:56 AM |
Type | Journal Article |
---|---|
Author | Qian He |
Author | Dana Rowangould |
Author | Alex Karner |
Author | Matthew Palm |
Author | Seth LaRue |
URL | https://www.sciencedirect.com/science/article/pii/S1361920922000475 |
Volume | 105 |
Pages | 103217 |
Publication | Transportation Research Part D: Transport and Environment |
Date | 2022-04-01 |
Journal Abbr | Transportation Research Part D: Transport and Environment |
DOI | 10.1016/j.trd.2022.103217 |
Library Catalog | ScienceDirect |
Language | en |
Abstract | The Covid-19 pandemic has decimated public transit service across the United States and caused significant decreases in ridership. Little is known about the reasons for unevenness in pandemic-era mode shifts and the impacts of pandemic-related transit reductions on riders’ day-to-day lives. Using a national survey of U.S. transit riders (n = 500) conducted in fall 2020, this study examines changes in transit use since the pandemic began, the reasons for transit reductions, and the effects of reduced transit use and transit service on transit riders’ ability to meet their travel needs. The Covid-19 pandemic has exacerbated existing transportation burdens for those who have limited mobility options, those facing socioeconomic challenges, Hispanic or Latinx riders, and female, non-binary or genderqueer people. We close with recommendations for strengthening transit service for these groups in the long term as we recover from the pandemic. |
Date Added | 4/4/2022, 9:42:18 AM |
Type | Journal Article |
---|---|
Author | Jesus Osorio |
Author | Yining Liu |
Author | Yanfeng Ouyang |
URL | https://www.sciencedirect.com/science/article/pii/S1361920922000566 |
Volume | 105 |
Pages | 103226 |
Publication | Transportation Research Part D: Transport and Environment |
Date | 2022-04-01 |
Journal Abbr | Transportation Research Part D: Transport and Environment |
DOI | 10.1016/j.trd.2022.103226 |
Library Catalog | ScienceDirect |
Language | en |
Abstract | The COVID-19 pandemic has induced significant transit ridership losses worldwide. This paper conducts a quantitative analysis to reveal contributing factors to such losses, using data from the Chicago Transit Authority’s bus and rail systems before and after the COVID-19 outbreak. It builds a sequential statistical modeling framework that integrates a Bayesian structural time-series model, a dynamics model, and a series of linear regression models, to fit the ridership loss with pandemic evolution and regulatory events, and to quantify how the impacts of those factors depend on socio-demographic characteristics. Results reveal that, for both bus and rail, remote learning/working answers for the majority of ridership loss, and their impacts depend highly on socio-demographic characteristics. Findings from this study cast insights into future evolution of transit ridership as well as recovery campaigns in the post-pandemic era. |
Date Added | 4/4/2022, 9:43:57 AM |