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Autonomous vehicles (AVs) represent a new, growing segment of transportation research. While there have been prior studies and deployments of AVs worldwide, full autonomy in bus transit has gained interest among researchers and practitioners within the last decade, which presents an opportunity to synthesize early trends. Therefore, the objective of this paper is to provide a review of the latest research on fully autonomous buses to summarize findings and identify gaps needing future research. Forty studies were reviewed in detail, and five main themes were identified, which are (1) technology deployment; (2) user acceptance; (3) safety; (4) social and economic aspects; and (5) regulations, policies, and legal issues. The results reveal that most prior studies have focused on technology development, and the area of regulation and policy would benefit from additional study. Noteworthy differences between research in Europe and the United States were also identified. In Europe, large funded projects involving real-world deployments have focused on user acceptance, security and safety, costs, and related legal issues, whereas in the United States, research has primarily concentrated on simulation modelling with limited real-world deployments. The results of this review are important for policy-makers and researchers as AV technology continues to evolve and become more widely available. [ABSTRACT FROM AUTHOR]

• This study aims to quantify the impact of shared e-scooters on bus ridership. • Shared e-scooters trips were assigned to nearby bus routes. • Several fixed effects regression models of route level bus ridership were estimated. • The findings suggest e-scooters are not a primary cause of bus ridership decline. Shared electric scooters (shared e-scooters) are rapidly growing in popularity across the United States. In 2019, more than 88 million shared e-scooter trips occurred nationwide. However, the impact of this growing mode on transit ridership is still largely unknown and limited to the findings of user surveys. The overarching goal of this study is to conduct an empirical analysis to quantify the impact of shared e-scooters on bus ridership using Louisville, Kentucky, as a case study conducted prior to the COVID-19 pandemic. To assess if shared e-scooters decrease or increase bus ridership, this study evaluated more than half a million shared e-scooters trips, and estimated several daily, weekly, and monthly fixed effects regression models of route level bus ridership. The results of the preferred fixed effect regression models indicate that shared e-scooters do not have a significant impact on local bus ridership. However, the model results suggest that shared e-scooters could potentially complement express bus routes as they serve the first/last mile of a trip, but further research on express routes is recommended. Most critically, the results of this study indicate that shared e-scooters are not one of the primary causes of bus ridership decline in Louisville. This finding is important for cities across the United States as they explore the causes of the recent declines in bus ridership. [ABSTRACT FROM AUTHOR]

Technology advancements in the last two decades have changed several aspects of public transit service, particularly related to fares. Transit agencies seek to benefit from new technologies to improve the customer experience by launching mobile fare payment applications ("apps") and adopting more sophisticated fare policies such as fare capping ("caps"). However, there is a limited understanding of the impacts of these two fare innovations on bus ridership. Therefore, this study seeks to quantify the impacts of mobile fare payment applications and fare capping policies (both daily and monthly) on bus ridership. Staggered difference-in-difference techniques were used to evaluate system-level bus ridership for the 50 largest transit agencies in the United States. This approach considers the effect on multiple treated units that adopted apps or caps at different times; it also considers heterogeneity of the treatment effect between treated agencies and over time. The results suggest that the launch of mobile fare payment applications and the adoption of daily fare capping policies did not have significant impacts on system-level ridership. On the other hand, monthly fare capping policies were associated with significant ridership gains. Transit systems that adopted monthly fare capping policies for more than one year experienced an average increase in annual bus ridership ranging from 3.6% to 4.1%; these results were heterogenous and increased over time. These findings can help to inform transit agencies across the United States as they consider different strategies to increase ridership and reverse recent bus ridership declines. Perhaps most important, the staggered difference-in-difference methodology used in this study could potentially be applied to evaluate a wide range of transportation technology and policy innovations with staggered (gradual) rollouts. • Technology innovations have transformed public transit fare collection and policy. • Mobile fare payment apps and fare capping are increasingly common in the USA. • Staggered Diff-in-Diff was used to study these innovations impacts of on ridership. • Monthly fare capping policies increased annual bus ridership by 3.6%–4.1%. • Monthly fare capping policies impact was heterogenous and increased over time. [ABSTRACT FROM AUTHOR]

• Bus ridership in the USA dropped to unprecedented levels during COVID-19. • A framework to explore the drivers of ridership declines was proposed. • The direct and indirect impacts of COVID-19 were untangled using multiple mediators. • Unemployment, telework, and people relocating mediated 13% to 38% of the decline. The COVID-19 pandemic has resulted in major consequences for many aspects of human life and the broader economy. Many transportation modes were severely impacted, including public transportation. During the early months of the pandemic in 2020, transit ridership dropped to unprecedented levels. Even by the end of 2022, bus ridership in the United States had not recovered to pre-pandemic levels. Despite the longstanding effects on public transportation, the direct and indirect impacts of the COVID-19 pandemic on bus ridership are largely unknown. In the context of this study, the direct impact refers to a change in travel behavior (i.e., due to the increased spread of COVID-19), while the indirect impact refers to reduced ridership due to factors such as lower employment or increased teleworking. This study proposes a framework to explore the drivers of transit ridership declines during COVID-19. The method is a multiple mediation analysis to estimate the monthly direct and indirect impacts of COVID-19 on bus ridership from March 2020 to December 2021. The results of this study revealed that three mediators (employment, telework, and people relocating) mediated about 13% to 38% of the total decline in bus ridership during the analysis period. The multiple mediation approach used in this study could be applied in many other transportation applications. [ABSTRACT FROM AUTHOR]

[Display omitted] • Between 2012 and 2018, bus ridership in the US declined 15% and rail ridership declined 3%. • We identify the factors responsible and quantify the contribution of each. • Expanded transit service and land-use changes would have led to higher ridership but were offset by other factors. • Ride-hailing is the biggest contributor to transit ridership decline. • Higher fares, incomes, teleworking and car ownership, and lower gas prices also contribute. Between 2012 and 2018, bus ridership in the United States declined 15% and rail ridership declined 3%. These losses are widespread and in contrast to trends in other countries. Using data from 215 Metropolitan Statistical Areas (MSAs) prior to the COVID-19 pandemic, we identify the factors responsible for this decline and quantify the contribution of each. We show that expanded transit service and land-use changes increased ridership 4.7% on bus and 10.7% on rail. However, losses due to other factors exceed these gains. Ride-hailing is the biggest contributor to transit ridership decline over this period, reducing bus ridership by 10%. Ride-hailing's effect on rail varies by metropolitan area size: it has little effect on rail ridership in the largest metropolitan areas but decreases rail ridership 10% in mid-sized metropolitan areas. Lower gas prices and higher fares contribute to lower transit ridership, as do higher incomes, more teleworking and higher car ownership. By providing a clear understanding of the causes of transit ridership decline, our research provides the foundation on which communities can craft an effective response to the problem. [ABSTRACT FROM AUTHOR]