| Type | Report |
|---|---|
| Author | San Jose State University |
| Author | Gordon Douglas |
| Author | David Moore |
| Author | San Jose State University |
| URL | https://scholarworks.sjsu.edu/mti_publications/411/ |
| Date | 07/2022 |
| Extra | DOI: 10.31979/mti.2022.2152 |
| Institution | Mineta Transportation Institute |
| Library Catalog | DOI.org (Crossref) |
| Language | en |
| Abstract | This report presents the results of a mixed-methods study of the 2020-2022 Oakland Slow Streets program. An official response to the Covid-19 pandemic, the program used signs and temporary barricades to limit thru-traffic on 21 miles of city streets to create more and safer space for walking, cycling, and outdoor recreation. Researchers collected data throughout the summer of 2021 on seven designated slow streets plus one cross street and one control street for each – a total of 21 street segments representing conditions in seven different neighborhoods across Oakland. Data collection comprised in-person passerby counts, observations and photographs of local conditions, and logged traffic speed data. Findings vary widely across study sites. In certain cases, observed slow streets saw less car traffic or more bicycle/pedestrian use than one or both of their comparison streets, and in at least one case the slow street was clearly embraced by the local community and used as planners intended; in others the slow street was no different than neighboring streets. The study draws on these findings to identify local conditions that seem likely to make slow treet treatments more or less successful. However, acknowledging that all neighborhoods deserve safer streets and greater outdoor recreational opportunities, the authors argue that better community outreach must be implemented to ensure areas not predisposed to make full use of slow streets can have the opportunity to do so. The study also makes suggestions regarding the potential for rapid, low-cost bike and pedestrian street safety improvements going forward. |
| Date Added | 8/23/2022, 11:07:35 AM |
| Type | Journal Article |
|---|---|
| Author | Bruno De Borger |
| Author | Stef Proost |
| URL | https://www.sciencedirect.com/science/article/pii/S0965856422001665 |
| Volume | 163 |
| Pages | 20-42 |
| Publication | Transportation Research Part A: Policy and Practice |
| Date | 2022-09-01 |
| Journal Abbr | Transportation Research Part A: Policy and Practice |
| DOI | 10.1016/j.tra.2022.06.012 |
| Library Catalog | ScienceDirect |
| Language | en |
| Abstract | Covid-19 has important implications for public transport operations. Increased teleworking and the perceived infection risk on public transport vehicles have drastically reduced demand in many cities. At the same time, physical distancing has effectively reduced available peak-period public transport capacity. In this paper, we use a simple model to study the effect of these changes on second-best optimal pricing and frequency provision, assuming that car use is underpriced. A numerical application reflecting the public transport situation in Brussel is provided. Results include the following. First, more telework and the increased perceived infection risk have opposite effects on the fare, so that it may be optimal not to change the fare at all. Optimal frequency is likely to decline. Second, holding the fare and frequency constant at their pre-Covid second-best optimal values, more telework reduces the public transport deficit if car use is underpriced. Third, extending the model to allow for passengers with different vulnerability towards Covid-19, allowing fare and frequency differentiation implies that vulnerable users will face higher fares only if their risk perception is sufficiently higher than that of the non-vulnerable, and car use is not too much underpriced. Occupancy rates will be lower for the vulnerable passengers. Fourth, the numerical results for Brussels show that telework and a high perceived infection risk for workers may yield a welfare optimum whereby commuters do almost not use public transport. Offering a low frequency suffices to deal with the captive demand by school children and students. Lastly, reserved capacity for the vulnerable users and stimuli for walking and biking to school may be useful policies to deal with the crowding risk. |
| Date Added | 8/30/2022, 10:20:57 AM |
| Type | Web Page |
|---|---|
| URL | https://pew.org/3R3Ik4I |
| Language | en |
| Abstract | Some cities are making permanent changes to discourage driving. |
| Date Added | 8/29/2022, 10:07:55 AM |
| Type | Journal Article |
|---|---|
| Author | Benjamin Gramsch |
| Author | C. Angelo Guevara |
| Author | Marcela Munizaga |
| Author | Daniel Schwartz |
| Author | Alejandro Tirachini |
| URL | https://www.sciencedirect.com/science/article/pii/S0967070X22001779 |
| Volume | 126 |
| Pages | 136-150 |
| Publication | Transport Policy |
| Date | 2022-09-01 |
| Journal Abbr | Transport Policy |
| DOI | 10.1016/j.tranpol.2022.06.012 |
| Library Catalog | ScienceDirect |
| Language | en |
| Abstract | Governments around the globe have taken different measures to tackle the COVID-19 pandemic, including the lockdown of people to decrease infections. The effect of such a strategy on transport demand is important not only for the current pandemic but also to understand changes in transport use and for future emergencies. We analyse a 2019–2020 database of smartcard data of trips from the city of Santiago, Chile, which followed a dynamic lockdown strategy in which its municipalities were temporarily restricted. We use this variation over time across municipalities to study the effect of lockdowns on public transportation using trips on buses and metro, accounting for the variation of municipalities that were under lockdown in a given day. We found a decrease of 72.3% at the beginning of the pandemic when schools suspended in-person classes, while the dynamic lockdowns reduced public transport demand by 12.1%. We also found that the effect of lockdowns decreased after the fifth week of their application, suggesting a short-term effectiveness of such policy to reduce mobility. Regarding sociodemographic effects, we found that lockdowns have a stronger impact on reducing public transport demand in municipalities with a larger proportion of the elderly population (2% additional reduction per 1% increase in the share of the elderly population) and high-income households (16% additional reduction for 1000 USD increase in GDP per capita). |
| Date Added | 8/26/2022, 11:59:02 AM |
| Type | Journal Article |
|---|---|
| Author | Lucy Downey |
| Author | Achille Fonzone |
| Author | Grigorios Fountas |
| Author | Torran Semple |
| URL | https://www.sciencedirect.com/science/article/pii/S0965856422001598 |
| Volume | 163 |
| Pages | 338-352 |
| Publication | Transportation Research Part A: Policy and Practice |
| Date | 2022-09-01 |
| Journal Abbr | Transportation Research Part A: Policy and Practice |
| DOI | 10.1016/j.tra.2022.06.005 |
| Library Catalog | ScienceDirect |
| Language | en |
| Abstract | This paper examines the determinants of changes in future public transport use in Scotland after the COVID-19 pandemic. An online questionnaire was distributed to 994 Scottish residents in order to identify travel habits, attitudes and preferences during the different phases of the COVID-19 outbreak and travel intentions after the pandemic. Quota constraints were enforced for age, gender and household income to ensure the sample was representative of the Scottish population. The respondents indicated that they anticipated they would make less use of buses and trains at the end of the pandemic. Over a third expect to use buses (36%) and trains (34%) less, whilst a quarter expect to drive their cars more. As part of the analysis, a random parameter bivariate probit model with heterogeneity in the means of random parameters was estimated to provide insights into the socio-demographic, behavioural and perceptual factors which might affect future public transport usage. The inclusion of random parameters allows for the potential effects of unobserved heterogeneity within the independent variables to be captured, whilst making allowances for heterogeneity in the means of the random parameters. The model estimation showed that several factors, including pre-lockdown travel choices, perceived risk of COVID-19 infection, household size and region significantly affected intended future use of public transport. In addition, several variables related to age, region, pre-lockdown travel choices and employment status resulted in random parameters. The current paper contributes to our understanding of the potential loss of demand for public transport and the consequences for future equitable and sustainable mobility. Our findings are highly relevant for transport policy when developing measures to strengthen the resilience of the public transport system during and after the pandemic. |
| Date Added | 8/30/2022, 10:44:25 AM |