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Promoting Public Bike-Sharing: A Lesson from the Unsuccessful Pronto System

Sun, Feiyang; Chen, Peng; Jiao, Junfeng. (2018). Promoting Public Bike-Sharing: A Lesson from the Unsuccessful Pronto System. Transportation Research: Part D, 63, 533 – 547.

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Abstract

In 2014, Seattle implemented its own bike-sharing system, Pronto. However, the system ultimately ceased operation three years later on March 17th, 2017. To learn from this failure, this paper seeks to understand factors that encourage, or discourage, bike-sharing trip generation and attraction at the station level. This paper investigates the effects of land use, roadway design, elevation, bus trips, weather, and temporal factors on three-hour long bike pickups and returns at each docking station. To address temporal autocorrelations and the nonlinear seasonality, the paper implements a generalized additive mixed model (GAMM) that incorporates the joint effects of a time metric and time-varying variables. The paper estimates models on total counts of pickups and returns, as well as pickups categorized by user types and by location. The results clarify that effects of hilly terrain and the rainy weather, two commonly perceived contributors to the failure. Additionally, results suggest that users in the University District, presumably mostly university students, tend to use shared bikes in neighborhoods with a higher household density and a higher percentage of residential land use, and make bike-sharing trips regardless workdays or non-workdays. The paper also contributes to the discussion on the relationship between public transportation service and bike-sharing. In general, users tend to use bike-sharing more at stations that have more scheduled bus trips nearby. However, some bike-sharing users may shift to bus services during peak hours and rainy weather. Several strategies are proposed accordingly to increase bike ridership in the future.

Keywords

Bicycle Sharing Programs; Urban Transportation; Transportation & The Environment; Land Use Planning; Time-varying Systems; Bike-sharing; Built Environment; Generalized Additive Mixed Model; Pronto; Temporal Factors; Built Environment Factors; Bicycle; Impact; Transportation; Walking; Usage

A Tutorial on Dynasearch: A Web-Based System for Collecting Process-Tracing Data in Dynamic Decision Tasks

Lindell, Michael K.; House, Donald H.; Gestring, Jordan; Wu, Hao-Che. (2019). A Tutorial on Dynasearch: A Web-Based System for Collecting Process-Tracing Data in Dynamic Decision Tasks. Behavior Research Methods, 51(6), 2646 – 2660.

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Abstract

This tutorial describes DynaSearch, a Web-based system that supports process-tracing experiments on coupled-system dynamic decision-making tasks. A major need in these tasks is to examine the process by which decision makers search over a succession of situation reports for the information they need in order to make response decisions. DynaSearch provides researchers with the ability to construct and administer Web-based experiments containing both between- and within-subjects factors. Information search pages record participants' acquisition of verbal, numeric, and graphic information. Questionnaire pages query participants' recall of information, inferences from that information, and decisions about appropriate response actions. Experimenters can access this information in an online viewer to verify satisfactory task completion and can download the data in comma-separated text files that can be imported into statistical analysis packages.

Keywords

Downloading; Text Files; Tasks; Access To Information; Statistics; Dynamic Decision Making; Process Tracing; Web-based Experiments; Information Search; Human-behavior; Eye-tracking; Choice; Expectations; Strategies; Mousetrap; Software; Time

Ancient and Current Resilience in the Chengdu Plain: Agropolitan Development Re-‘Revisited’

Abramson, Daniel B. (2020). Ancient and Current Resilience in the Chengdu Plain: Agropolitan Development Re-‘Revisited’. Urban Studies (sage Publications, Ltd.), 57(7), 1372 – 1397.

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Abstract

The Dujiangyan irrigation system, China's largest, is one of the world's most important examples of sustainable agropolitan development, maintained by a relatively decentralised system of governance that minimises bureaucratic oversight and depends on significant local autonomy at many scales down to the household. At its historic core in the Chengdu Plain, the system has supported over 2000 years of near-continuously stable urban culture, as well as some of the world's highest sustained long-term per-hectare productivity and diversity of grain and other crops, especially considering its high population density, forest cover, general biodiversity and flood management success. During the past decade, rapid urban expansion has turned the Chengdu Plain from a net grain exporter into a grain importer, and has radically transformed its productive functioning and distinctive scattered settlement pattern, reorganising much of the landscape into larger, corporately-managed farms, and more concentrated and infrastructure-intensive settlements of non-farming as well as farming households. Community-scale case studies of spatial-morphological and household socio-economic variants on the regional trend help to articulate what is at stake. Neither market-driven 'laissez-faire' rural development nor local state-driven spatial settlement consolidation and corporatisation of production seem to correlate well with important factors of resilience: landscape heterogeneity; crop diversity and food production; permaculture; and flexibility in household independence and choice of livelihood. Management of the irrigation system should be linked to community-based agricultural landscape preservation and productive dwelling, as sources of adaptive capacity crucial to the social-ecological resilience of the city-region, the nation and perhaps all humanity.

Keywords

Urbanization; Economies Of Agglomeration; Agricultural Ecology; Sustainability; Urban Planning; Land Use; China; Agglomeration/urbanisation; Agroecosystems; Environment/sustainability; History/heritage/memory; Redevelopment/regeneration; Cultivated Land; Countryside; Expansion; State; Rise; Modernization; Conservation; Integration; Earthquake; Agglomeration; Urbanisation; Environment; History; Heritage; Memory; Redevelopment; Regeneration; Population Density; Production; Farming; Agriculture; Decentralization; Autonomy; Food Production; Households; Landscape; Resilience; Rural Development; Food; Farms; Regional Development; Productivity; Economic Development; Case Studies; Agricultural Production; Biodiversity; Sustainable Development; Governance; Preservation; Crops; Flood Management; Irrigation; Permaculture; Radicalism; Socioeconomic Factors; Grain; Flexibility; Heterogeneity; Variants; Urban Areas; Irrigation Systems; Rural Communities; Bureaucracy; Landscape Preservation; Agricultural Land; Flood Control; Density; Infrastructure; Urban Sprawl; Livelihood; Farm Management; Rural Areas; Urban Farming; Settlement Patterns; Agribusiness; Market Economies

Residential Neighborhood Features Associated with Objectively Measured Walking Near Home: Revisiting Walkability Using the Automatic Context Measurement Tool (ACMT)

Mooney, Stephen J.; Hurvitz, Philip M.; Moudon, Anne Vernez; Zhou, Chuan; Dalmat, Ronit; Saelens, Brian E. (2020). Residential Neighborhood Features Associated with Objectively Measured Walking Near Home: Revisiting Walkability Using the Automatic Context Measurement Tool (ACMT). Health & Place, 63.

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Abstract

Many distinct characteristics of the social, natural, and built neighborhood environment have been included in walkability measures, and it is unclear which measures best describe the features of a place that support walking. We developed the Automatic Context Measurement Tool, which measures neighborhood environment characteristics from public data for any point location in the United States. We explored these characteristics in home neighborhood environments in relation to walking identified from integrated GPS, accelerometer, and travel log data from 681 residents of King Country, WA. Of 146 neighborhood characteristics, 92 (63%) were associated with walking bout counts after adjustment for individual characteristics and correction for false discovery. The strongest built environment predictor of walking bout count was housing unit count. Models using data-driven and a priori defined walkability measures exhibited similar fit statistics. Walkability measures consisting of different neighborhood characteristic measurements may capture the same underlying variation in neighborhood conditions.

Keywords

Built-environment; Physical-activity; Transit; Density; Obesity; Weight; Time; Gps; American Community Survey; Epa Walkability Index; Neighborhood Environment-wide Association; Study; Walking Bouts

Autonomous People: Identity, Agency, and Automated Driving

Dunn, Peter T. (2021). Autonomous People: Identity, Agency, and Automated Driving. Journal Of Urban Technology, 28(3-4), 25 – 44.

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Abstract

The prevailing discourse on autonomous vehicles (AVs) has not yet developed a sophisticated conceptualization of autonomy and has given insufficient attention to the autonomy of people. In response, this article shifts our attention away from the AV's autonomy and towards that of its user. Autonomy is conceived here as the socially and materially situated capacity of an individual to identify and act on one's own values and desires, a capacity that is desirable for collective political life. This definition is drawn selectively from a survey of thought illustrating the richness of this concept. I then examine how studies of transportation have already made use of certain themes of autonomy in understanding mobility practices beyond dominant utilitarian models. This sets up an examination of AVs, where the existing literature tends to use a narrow conceptualization of autonomy. I then briefly examine two examples of unsettled questions in AV development, discretionary user controls and shared ride systems, in light of autonomy. The goal of this article is both to show how autonomy can be productive in understanding mobility practices, and to argue for personal autonomy as a normative value worth pursuing in the technical, political, and social development of automated mobility systems.

Keywords

Car Use; Vehicles; Travel; Accidents; Policy; Autonomy; Agency; Autonomous Vehicles; Mobility

What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic

Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.

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Abstract

Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.

Keywords

Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us

Measuring Neighbourhood Air Pollution: The Case of Seattle’s International District.

Bassok, Alon; Hurvitz, Phil M.; Bae, C-H. Christine; Larson, Timothy. (2010). Measuring Neighbourhood Air Pollution: The Case of Seattle’s International District. Journal Of Environmental Planning & Management, 53(1), 23 – 39.

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Abstract

Current US regulatory air quality monitoring networks measure ambient levels of pollutants and cannot capture the effects of mobile sources at the micro-scale. Despite the fact that overall air quality has been getting better, more vulnerable populations (children, the elderly, minorities and the poor) continue to suffer from traffic-related air pollution. As development intensifies in urban areas, more people are exposed to road-related air pollution. However, the only consideration given to air quality, if any, is based on ambient measures. This paper uses an inexpensive, portable Particle Soot Absorption Photometer (PSAP) to measure Black Carbon (BC) emissions, a surrogate for diesel fuels emissions, in Seattle's International District. With the aid of a GPS receiver, street-level BC data were geocoded in real space-time. It was found that pollution levels differed substantially across the study area. The results show the need for street-level air pollution monitoring, revisions in current land use and transportation policies, and air quality planning practice.

Keywords

Emission Standards; Air Pollution; Atmospheric Deposition; Social Groups; Waste Products; Sanitary Landfills; Black Carbon; Freeway Air Pollution Sheds (faps); Land Use; Mobile Monitoring; Neighbourhood Air Quality; Aerosol Light-absorption; Respiratory Health; Coefficient; Exposure; Symptoms; Children; Pollutants; Particles; Exhaust; Asthma

Impact of Gasoline Prices on Transit Ridership in Washington State

Stover, Victor W.; Bae, C.-H. Christine. (2011). Impact of Gasoline Prices on Transit Ridership in Washington State. Transportation Research Record, 2217, 1 – 10.

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Abstract

Gasoline prices in the United States have been extremely volatile in recent years and rose to record high levels during the summer of 2008. According to the U.S. Energy Information Administration, the average U.S. gasoline price for the year 2008 was $3.26 a gallon, which was the second highest yearly average in history when adjusted for inflation. Transportation agencies reported changes in travel behavior as a result of the price spike, with transit systems experiencing record ridership and state departments of transportation reporting reductions in traffic volumes. This study examined the impact of changing gasoline prices on transit ridership in Washington State by measuring the price elasticity of demand of ridership with respect to gasoline price. Ordinary least-squares regression was used to model transit ridership for transit agencies in 11 counties in Washington State during 2004 to 2008. The price of gasoline had a statistically significant effect on transit ridership for seven systems studied, with elasticities ranging from 0.09 to 0.47. A panel data model was estimated with data from all 11 agencies to measure the overall impact of gasoline prices on transit ridership in the state. The elasticity from the panel data model was 0.17. Results indicated that transit ridership increased as gasoline prices increased during the study period. The findings were consistent with those from previous studies on the topic.

Keywords

Time-series Analysis; Gas Prices; Elasticities; Demand

Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection

Hong, Jinhyun; Shen, Qing. (2013). Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection. Transportation Research Part D-transport And Environment, 22, 75 – 79.

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Abstract

This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions. (C) 2013 Elsevier Ltd. All rights reserved.

Keywords

Urban Form; Travel; Transportation Emissions; Residential Density; Confounding By Location; Self-selection

How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales

Hong, Jinhyun; Shen, Qing; Zhang, Lei. (2014). How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales. Transportation, 41(3), 419 – 440.

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Abstract

Much of the literature shows that a compact city with well-mixed land use tends to produce lower vehicle miles traveled (VMT), and consequently lower energy consumption and less emissions. However, a significant portion of the literature indicates that the built environment only generates some minor-if any-influence on travel behavior. Through the literature review, we identify four major methodological problems that may have resulted in these conflicting conclusions: self-selection, spatial autocorrelation, inter-trip dependency, and geographic scale. Various approaches have been developed to resolve each of these issues separately, but few efforts have been made to reexamine the built environment-travel behavior relationship by considering these methodological issues simultaneously. The objective of this paper is twofold: (1) to better understand the existing methodological gaps, and (2) to reexamine the effects of built-environment factors on transportation by employing a framework that incorporates recently developed methodological approaches. Using the Seattle metropolitan region as our study area, the 2006 Household Activity Survey and the 2005 parcel and building data are used in our analysis. The research employs Bayesian hierarchical models with built-environment factors measured at different geographic scales. Spatial random effects based on a conditional autoregressive specification are incorporated in the hierarchical model framework to account for spatial contiguity among Traffic Analysis Zones. Our findings indicate that land use factors have highly significant effects on VMT even after controlling for travel attitude and spatial autocorrelation. In addition, our analyses suggest that some of these effects may translate into different empirical results depending on geographic scales and tour types.

Keywords

Land-use; Urban Form; Multilevel Models; Physical-activity; Neighborhood; Choice; Impact; Specification; Accessibility; Causation; Built Environment; Travel Behavior; Self-selection; Spatial Autocorrelation; Bayesian Hierarchical Model