14 research outputs found
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American Micromobility Panel (Part 2): Transit Connection, Mode Substitution, and VMT Reduction
This study examined the sustainability of shared micromobility services using data from 48 cities in the US using a 21-day smartphone travel diary and survey data. Population-weighted analysis indicated a much smaller share of transit connection than in prior reported studies, with more reliable data. However methodological decisions could be a cause for such discrepancies suggesting a sensitivity analysis of this same data may be a good next research step. Results also indicated median VMT reduced per micromobility trip to be roughly 0.15 miles for e-scooter share trips and 0.25 miles for bike share (including e-bike) trips. Models of mode substitution confirm prior evidence of factors affecting car substitution including trip distance as the strongest factor. This study also proposed two frameworks for building a sketch planning tool for examining VMT reduction from future micromobility services. This tool could help cities and regions better plan for the micromobility services to achieve real VMT and GHG reduction goals. While more research is needed to employ this framework, it helps motivate a series of additional research topics to inform a decision support tool for shared micromobility planning. View the NCST Project Webpag
Impacts of the COVID-19 pandemic on the spatio-temporal characteristics of a bicycle-sharing system: A case study of Pun Pun, Bangkok, Thailand
The COVID-19 pandemic is found to be one of the external stimuli that greatly affects mobility of people, leading to a shift of transportation modes towards private individual ones. To properly explain the change in people's transport behavior, especially in pre- and post- pandemic periods, a tensor-based framework is herein proposed and applied to Pun Pun-the only public bicycle-sharing system in Bangkok, Thailand-where multidimensional trip data of Pun Pun are decomposed into four different modes related to their spatial and temporal dimensions by a non-negative Tucker decomposition approach. According to our computational results, the first pandemic wave has a sizable influence not only on Pun Pun but also on other modes of transportation. Nonetheless, Pun Pun is relatively more resilient, as it recovers more quickly than other public transportation modes. In terms of trip patterns, we find that, prior to the pandemic, trips made during weekdays are dominated by business trips with two peak periods (morning and evening peaks), while those made during weekends are more related to leisure activities as they involve stations nearby a public park. However, after the first pandemic wave ends, the patterns of weekday trips have been drastically changed, as the number of business trips sharply drops, while that of educational trips connecting metro/subway stations with a major educational institute in the region significantly rises. These findings may be regarded as a reflection of the ever-changing transport behavior of people seeking a sustainable mode of private transport, with a more positive outlook on the use of bicycle-sharing system in Bangkok, Thailand
Incentive-Based Approach to Rebalancing a Dock-Less E-Bike-Share System for Sustainability
The spatial mismatch between demand and supply over time is a significant concern in a bike-share service. One primary strategy to fill the mismatch is to rebalance a shared bike fleet by vans or trucks. The more vans operators use to meet the demand, the more vehicle miles traveled (VMT) the system produces, offsetting the VMT reduction benefit that was at least a part of the motivation for the city to authorize the service. Another approach to the problem is an incentive-based approach to rebalancing a fleet. This approach incentivizes users to walk farther to get a bike from the oversupplied area (origin-based incentives) or to take a bike to the undersupplied area (destination-based incentives) by offering some reward, such as free bike-share use or a prize of some sort. This approach has proven to be successful in docked bike-share services, but the potential in the context of dock-less bike-share services is unknown. This dissertation examines the potential effect of an incentive-based approach to rebalancing a dock-less e-bikeshare fleet on bike-share use and social benefits, focusing mainly on VMT reduction, using a e-bike-share service in the Sacramento area, CA
Phase II
UC-ITS-2020-05Dock-less, electric bike-share services offer cities a new transportation option with the potential to improve environmental, social, and health outcomes. But these benefits accrue only if bike-share use replaces car travel. The purpose of this study is to examine factors influencing whether bike-share substitutes for driving and the degree to which and under what circumstances bike-share use reduces car travel. Major findings in this report include (1) bike-share in the Sacramento region most commonly substitutes for car and walking trips, (2) each bike in the Sacramento bike-share fleet reduces users\u2019 VMT by an average of approximately 2.8 miles per day, (3) areas with a higher proportion of low-income households tend to use bike-share less, (4) bike-share availability appears to induce new trips to restaurants and shopping and for recreation, (5) bike-share trips from commercial and office areas were more likely to replace walking or transit trips, while bike-share trips from non-commercial areas (and trips to home or restaurants) were more likely to replace car trips, (6) expanding the bike-share service boundary at the same fleet density decreases system efficiency and VMT reductions per bike. Our result suggests the need for an efficient rebalancing strategy specific to areas by time of day to increase the service efficiency and its benefits. Further analysis of the data used in this study to examine questions such as how bike share can improve transit connections and factors inducing bike use at the individual level will contribute to the development of more robust models and provide additional insights for bike share operation strategies and policy implementation
American Micromobility Panel: Part 1
Caltrans 65A0686 Task Order 024 USDOT Grant 69A3551747114This report presents preliminary findings from the American Micromobility Panel, the largest study of shared micromobility services in the United States incorporating riders from multiple major operators. Micromobility services (bike-share and scooter-share) have recently emerged in many U.S. cities. Given that the substitution of bicycling, scooting, and other small vehicle travel for car travel will help cities reach numerous planning goals (e.g., accessibility, emissions, climate, health, equity, etc.), there is a need for understanding the effects of these mobility services. The purpose of this study was to examine the impact of micromobility services on travel behavior and outcomes such as mode shift, car ownership, access, equity, safety, and physical activity
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Incentive-based Approach to Rebalancing a Dock-less E-Bike-Share System for Sustainability
The spatial mismatch between demand and supply over time is a significant concern in a bike-share service. One primary strategy to fill the mismatch is to rebalance a shared bike fleet by vans or trucks. The more vans operators use to meet the demand, the more vehicle miles traveled (VMT) the system produces, offsetting the VMT reduction benefit that was at least a part of the motivation for the city to authorize the service. Another approach to the problem is an incentive-based approach to rebalancing a fleet. This approach incentivizes users to walk farther to get a bike from the oversupplied area (origin-based incentives) or to take a bike to the undersupplied area (destination-based incentives) by offering some reward, such as free bike-share use or a prize of some sort. This approach has proven to be successful in docked bike-share services, but the potential in the context of dock-less bike-share services is unknown. This dissertation examines the potential effect of an incentive-based approach to rebalancing a dock-less e-bike-share fleet on bike-share use and social benefits, focusing mainly on VMT reduction, using a e-bike-share service in the Sacramento area, CA. This dissertation consists of four studies. The first and the second studies are self-standing. The third study is built on the second study, and the fourth and final study assembles an agent-based model from the models presented in the prior three studies. In the first study, I examine bike-share users’ willingness-to-walk to pick up a bike or drop off a bike at some distance from their origins or destinations if rewarded and identify characteristics influencing willingness-to-walk. I find that half of the respondents use bike-share if the available bike is located 8.9 minutes away. Estimates of willingness-to-walk farther than the mean distance for incentives at origins and destinations were 3.8 minutes and 4.2 minutes per dollar, respectively. Based on these results, I find the potential effectiveness of incentives as a strategy for spatially rebalancing bike-share fleets.
The second study examines the factors influencing mode substitution, defined here as the mode that is replaced when bike-share is used. I find that walking is the dominant mode substitution for trips of less than 1 mile for most trip purposes. Long trips and non-commute trips that start at non-commercial locations are likely to represent car substitution and some groups, such as women, non-membership holders, and those who have a private car, are more likely to report car substitution for any trip purpose.
The third study develops a framework for estimating vehicle miles reduced from the introduction of a dock-less e-bike-share service. I find that the daily car substitution rate, including both “private car” and “ride-haling,” was 28% on weekdays. Furthermore, I find that the dock-less bike-share service with a fleet size ranging between 950 and 1100 was responsible for an estimated VMT reduction of 2,131 vehicle miles per day in total and 0.79 miles per trip on average across the service region on weekdays.
The fourth and final study develops a simulator using an agent-based model to examine how an incentive-based approach helps reduce the spatial mismatch between demand and supply and to estimate impacts on VMT reduction and its social cost in the context of a dock-less e-bike-share service. I find that incentive strategies improve the willingness of bike-share users to go out of their way to pick up or drop off a bike, but the effect varies by fleet size and the size of the incentive budget. The number of trips per bike does not change significantly with rebalancing strategies, suggesting that operators must determine the fleet size carefully before entering the market. I estimate that introducing incentive strategies reduces VMT by 3-6% by increasing the number of bike-share trips and saves US$20-29 in social costs per day. Based on the first three studies, this study demonstrates the potential of the rebalancing strategy's incentive approach to increase the bike-share operation's efficiency and social benefits regarding VMT reduction
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Bike-Share in the Sacramento Region Primarily Substitutes for Car and Walking Trips and Reduces Vehicle Miles Traveled
Dock-less, electric bike-share services offer cities a new transportation option with the potential to improve environmental, social, and health outcomes by increasing physical activity and reducing vehicle miles traveled (VMT) and related greenhouse gas emissions. But these benefits accrue only if bike-share use replaces car travel. If bikeshare pulls users from public transit, personal bikes, or walking, the benefits will be limited. Little is known about the factors influencing whether bike-share substitutes for driving. Understanding the degree to which and under what circumstances bike-share use reduces car travel can inform cities’ efforts to meet VMT reduction goals set under California’s Sustainable Communities and Climate Protection Act of 2008 (Senate Bill 375). Researchers at the University of California, Davis collected user surveys and system-wide trip data from a Sacramentoarea dockless e-bike-share program in 2018 and 2019 to examine factors influencing travel mode substitution and estimated system-wide VMT reductions caused by bikeshare use. They developed a model to examine factors influencing bike-share demand and estimated potential VMT reductions for hypothetical expanded service scenarios
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Bike-Share in the Sacramento Region Primarily Substitutes for Car and Walking Trips and Reduces Vehicle Miles Traveled
Dock-less, electric bike-share services offer cities a new transportation option with the potential to improve environmental, social, and health outcomes by increasing physical activity and reducing vehicle miles traveled (VMT) and related greenhouse gas emissions. But these benefits accrue only if bike-share use replaces car travel. If bikeshare pulls users from public transit, personal bikes, or walking, the benefits will be limited. Little is known about the factors influencing whether bike-share substitutes for driving. Understanding the degree to which and under what circumstances bike-share use reduces car travel can inform cities’ efforts to meet VMT reduction goals set under California’s Sustainable Communities and Climate Protection Act of 2008 (Senate Bill 375). Researchers at the University of California, Davis collected user surveys and system-wide trip data from a Sacramentoarea dockless e-bike-share program in 2018 and 2019 to examine factors influencing travel mode substitution and estimated system-wide VMT reductions caused by bikeshare use. They developed a model to examine factors influencing bike-share demand and estimated potential VMT reductions for hypothetical expanded service scenarios
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How Dock-less Electric Bike Share Influences Travel Behavior, Attitudes, Health, and Equity: Phase II
Dock-less, electric bike-share services offer cities a new transportation option with the potential to improve environmental, social, and health outcomes. But these benefits accrue only if bike-share use replaces car travel. The purpose of this study is to examine factors influencing whether bike-share substitutes for driving and the degree to which and under what circumstances bike-share use reduces car travel. Major findings in this report include (1) bike-share in the Sacramento region most commonly substitutes for car and walking trips, (2) each bike in the Sacramento bike-share fleet reduces users’ VMT by an average of approximately 2.8 miles per day, (3) areas with a higher proportion of low-income households tend to use bike-share less, (4) bike-share availability appears to induce new trips to restaurants and shopping and for recreation, (5) bike-share trips from commercial and office areas were more likely to replace walking or transit trips, while bike-share trips from non-commercial areas (and trips to home or restaurants) were more likely to replace car trips, (6) expanding the bike-share service boundary at the same fleet density decreases system efficiency and VMT reductions per bike. Our result suggests the need for an efficient rebalancing strategy specific to areas by time of day to increase the service efficiency and its benefits. Further analysis of the data used in this study to examine questions such as how bike share can improve transit connections and factors inducing bike use at the individual level will contribute to the development of more robust models and provide additional insights for bike share operation strategies and policy implementation
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New Metrics Are Needed to Understand the Environmental Benefits of Micromobility Services
Micromobility services (e.g., conventional and electric bikeshare programs and electric scootershare programs) hold great potential for reducing vehicle miles traveled and greenhouse gas emissions if these services are used as substitutes for car travel and/or to access public transit. But estimating these environmental effects is challenging, as it requires measuring changes in human behavior—that is, the choice of what transportation mode to use. While many cities collect various micromobility usage metrics to regulate services, these metrics are not sufficient for calculating the sustainability benefits of these services