Chen, Peng; Shen, Qing; Childress, Suzanne. (2018). A GPS Data-based Analysis of Built Environment Influences on Bicyclist Route Preferences. International Journal Of Sustainable Transportation, 12(3), 218 – 231.
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Abstract
This study examines the effects of built environment features, including factors of land use and road network, on bicyclists' route preferences using the data from the city of Seattle. The bicycle routes are identified using a GPS dataset collected from a smartphone application named CycleTracks. The route choice set is generated using the labeling route approach, and the cost functions of route alternatives are based on principal component analyses. Then, two mixed logit models, focusing on random parameters and alternative-specific coefficients, respectively, are estimated to examine bicyclists' route choice. The major findings of this study are as follows: (1) the bicycle route choice involves the joint consideration of convenience, safety, and leisure; (2) most bicyclists prefer to cycle on shorter, flat, and well-planned bicycle facilities with slow road traffic; (3) some bicyclists prefer routes surrounded by mixed land use; (4) some bicyclists favor routes which are planted with street trees or installed with street lights; and (5) some bicyclists prefer routes along with city features. This analysis provides valuable insights into how well-planned land use and road network can facilitate efficient, safe, and enjoyable bicycling.
Keywords
Cyclists; Mobile Apps; Multiple Correspondence Analysis (statistics); Traffic Engineering; Cycling; Bicycle Route Choice; Built Environment; Labeling Routes; Mixed Logit Model; Principal Component Analysis; Smartphone GPS Data; Choice Sets; Safe Routes; Walking; Models; Health; Infrastructure; Facilities; California; Networks
Muni, Kennedy; Kobusingye, Olive; Mock, Charlie; Hughes, James P.; Hurvitz, Philip M.; Guthrie, Brandon. (2019). Motorcycle Taxi Programme is Associated with Reduced Risk of Road Traffic Crash among Motorcycle Taxi Drivers in Kampala, Uganda. International Journal Of Injury Control & Safety Promotion, 26(3), 294 – 301.
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Abstract
SafeBoda is a transportation company that provides road safety training and helmets to its motorcycle taxi drivers in Kampala. We sought to determine whether risk of road traffic crash (RTC) was lower in SafeBoda compared to regular (non-SafeBoda) motorcycle taxi drivers during a 6-month follow-up period. We collected participant demographic and behavioural data at baseline using computer-assisted personal interview, and occurrence of RTC every 2 months using text messaging and telephone interview from a cohort of 342 drivers. There were 85 crashes (31 in SafeBoda and 54 in regular drivers) during follow-up. Over the 6-month follow-up period, SafeBoda drivers were 39% less likely to be involved in a RTC than regular drivers after adjusting for age, possession of a driver's license, and education (RR: 0.61, 95% CI: 0.39-0.97, p = .04). These findings suggest that the SafeBoda programme results in safer driving and fewer RTCs among motorcycle taxi drivers in Kampala.
Keywords
Motorcyclists; Motorcycle Helmets; Text Messages; Telephone Interviewing; Motorcycles; Kampala (uganda); Uganda; Boda-boda; Crash; Injury; Road Safety; Injuries; Burden; Riders; Kenya; Traffic Accidents; Transportation; Risk Management; Crashes; Demographics; Transportation Safety; Short Message Service; Traffic; Traffic Accidents & Safety; Roads; Risk Reduction; Taxicabs; Protective Equipment; Drivers Licenses; Kampala Uganda
Aziz, Ahmed M. Abdel. (2021). The Practice of Roadway Safety Management in Public-Private Partnerships. Journal Of Construction Engineering And Management, 147(12).
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Abstract
As a matter of course, the private party in public-private partnerships (PPPs) assumes the responsibility for roadway safety management (RSM). However, because most PPPs are performance-based, public highway agencies must articulate the specifications and methods they develop to enforce RSM practices. Despite the increased interest in PPPs in recent decades, little has been published on developing and propagating the RSM practices used with this delivery system. To fill this research gap and explore RSM practices in PPPs, this work took a synthesis research approach, using content analysis to critically review and analyze 16 PPP agreements in seven states and provinces leading in PPP contracting in North America. The study discovered several methods and organized them under five mechanisms: Mechanism 1, integrating roadway safety into project performance specifications and initiating new tools such as safety compliance orders; Mechanism 2, imposing nonconformance monetary deductions based on point and classification systems; Mechanism 3, regulating safety payments on the basis of crash statistics; Mechanism 4, promoting safety initiative programs; and Mechanism 5, enforcing administrative countermeasures such as work suspension and default/termination triggers for persistent developer noncompliance. Mechanisms 1 and 5 were the default mechanisms in all toll- and availability-based projects, whereas Mechanism 2 was common in availability-only projects. The research reviewed the RSM packages in the PPP agreements, elucidating the particulars of the RSM mechanisms, highlighting RSM design considerations, presenting implementation guidelines, and articulating research needs. The research results were validated against PPP highways in five other states and provinces. This synthesis research provides highway agencies with an extensive practice review to support RSM package design for future PPP projects.
Keywords
Qualitative Research; Incentives; Public-private Partnerships (ppps); Performance Specifications; Roadway Safety; Payment Mechanisms; Availability Payment; Highways
Zou, Tianqi; Aemmer, Zack; Mackenzie, Don; Laberteaux, Ken. (2022). A Framework for Estimating Commute Accessibility and Adoption of Ridehailing Services Under Functional Improvements from Vehicle Automation. Journal Of Transport Geography, 102.
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Abstract
This paper develops an analytical framework to estimate commute accessibility and adoption of various ridehailing service concepts across the US by synthesizing individual commute trips using national Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data. Focusing on potential improvements in cost and time that could be enabled by vehicle automation, we use this modeling framework to simulate a lower-price autonomous service (e.g., 50% or 75% lower) with variable wait times and implementation levels (solo, pooled, and first/last mile transit connections services, alone or in combination) to determine how they might affect adoption rates. These results are compared across metrics of accessibility and trip density, as well as socioeconomic factors such as household income. We find - unsurprisingly - that major cities (e.g. New York, Los Angeles, and Chicago) support the highest adoption rates for ridehailing services. Decreases in price tend to increase market share and accessibility. The effect of a decrease in price is more drastic for lower income groups. The proposed method for synthesizing trips using the LODES contributes to current travel demand forecasting methods and the proposed analytic framework can be flexibly implemented with any other mode choice model, extended to non-commute trips, or applied to different levels of geographic aggregation.
Keywords
Choice Of Transportation; Demand Forecasting; Poor People; Adoption; Price Cutting; Metropolis; Employment Statistics; Los Angeles (calif.); New York (state); Chicago (ill.); Accessibility; Autonomous Vehicles; New Mobility Services; Ridehailing; Travel Demand; Preferences
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
Doescher, Mark P.; Lee, Chanam; Berke, Ethan M.; Adachi-mejia, Anna M.; Lee, Chun-kuen; Stewart, Orion; Patterson, Davis G.; Hurvitz, Philip M.; Carlos, Heather A.; Duncan, Glen E.; Moudon, Anne Vernez. (2014). The Built Environment and Utilitarian Walking in Small U.S. Towns. Preventive Medicine, 69, 80 – 86.
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Abstract
Objectives. The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. Methods. In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking (any versus none; high [>= 150 min per week] versus low [<150 min per week]) to retail, employment and public transit destinations. Results. Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p < 0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. Conclusions. Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population. (C) 2014 Elsevier Inc. All rights reserved.
Keywords
Cities & Towns -- Environmental Conditions; Walking; Telephone Surveys; Logistic Regression Analysis; Public Transit; Cities & Towns; Rural Conditions; United States; Exercise/physical Activity; Health Promotion; Physical Environment; Prevention; Rural Health; Social Environment; Physical-activity; Postmenopausal Women; Adults; Health; Risk; Transportation; Associations; Neighborhood; Travel; Determinants
Bae, Chang-hee Christine; Sinha, Debmalya. (2016). Measuring Pedestrian Exposure to PM-2.5: Case of the Seattle, Washington, International District. Transportation Research Record, 2570, 139 – 147.
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Abstract
Traffic-related air pollution is dangerous to human health. Although transportation and land use planning policies often focus on making walking more attractive, there is a lack of research on pedestrian exposure to air pollution levels. This research focused on pedestrian exposure to particulate matter with a diameter of 2.5 mu m or less (PM-2.5) in the International District (ID) adjacent to downtown Seattle, Washington. Several types of equipment were used: (a) a portable nephelometer (Radiance Research M903) mounted on a backpack (arranged by the Puget Sound Clean Air Agency); (b) an AirCasting mobile application (by Habitmap) in a cell phone to record the researcher's location and exposure levels while walking; and (c) a GoPro Hero camera to record visual images of the surrounding built environment, traffic volume, and other activities. The field data were collected three times a day (morning, midday, and evening) for one week in winter (December 31, 2014-January 9, 2015) and one week in spring (March 21-30, 2015) on selected routes in the ID. The study found seasonal and time-of-day variability of exposure levels: there were higher PM-2.5 concentration levels during the winter (57.77 mu g/m(3)) than in the spring (6.99 mu g/m(3)), and higher levels in the morning (25 mu g/m(3)) than in the evening (17 mu g/m(3)). Also, the average PM-2.5 levels of ID data were slightly higher (20.7 mu g/m(3)) than those at the nearest U.S. Environmental Protection Agency monitoring station (19.0 mu g/m(3)). The researchers concluded that the key contributors of pedestrian exposure to air pollution are traffic, construction activities, and smokers on sidewalks.
Keywords
Particulate Air-pollution; Long-term Exposure; Particle Number; Fine; Quality; Health; Pm2.5; Risk; Road
Stewart, Orion T.; Carlos, Heather A.; Lee, Chanam; Berke, Ethan M.; Hurvitz, Philip M.; Li, Li; Moudon, Anne Vernez; Doescher, Mark P. (2016). Secondary GIS Built Environment Data for Health Research: Guidance for Data Development. Journal Of Transport & Health, 3(4), 529 – 539.
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Abstract
Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the 9 BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Geographic Information-systems; Physical-activity; Land-use; Walking; Neighborhood; Associations; Density; Design; Adults; Travel; Active Travel; Pedestrian; Urban Design; Community Health; Rural
Chen, Peng; Sun, Feiyang; Wang, Zhenbo; Gao, Xu; Jiao, Junfeng; Tao, Zhimin. (2018). Built Environment Effects on Bike Crash Frequency and Risk in Beijing. Journal Of Safety Research, 64, 135 – 143.
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Abstract
Introduction: Building a safe biking environment is crucial to encouraging bicycle use. In developed areas with higher density and more mixed land use, the built environment factors that pose a crash risk may vary. This study investigates the connection between biking risk factors and the compact built environment, using data for Beijing. Method: In the context of China, this paper seeks to answer two research questions. First, what types of built environment factors are correlated with bike-automobile crash frequency and risk? Second, how do risk factors vary across different types of bikes? Poisson lognormal random effects models are employed to examine how land use and roadway design factors are associated with the bike-automobile crashes. Results: The main findings are: (1) bike-automobile crashes are more likely to occur in densely developed areas, which is characterized by higher population density, more mixed land use, denser roads and junctions, and more parking lots; (2) areas with greater ground transit are correlated with more bike-automobile crashes and higher risks of involving in collisions; (3) the percentages of wider streets show negative associations with bike crash frequency; (4) built environment factors cannot help explain factors contributing to motorcycle-automobile crashes. Practical Applications: In China's dense urban context, important policy implications for bicycle safety improvement drawn from this study include: prioritizing safety programs in urban centers, applying safety improvements to areas with more ground transit, placing bike-automobile crash countermeasures at road junctions, and improving bicycle safety on narrower streets. (C) 2018 National Safety Council and Elsevier Ltd. All rights
Keywords
Motorcycling Accidents; Built Environment; Motorcycling; Poisson Distribution; Safety; Beijing (china); Bike-automobile Crash; Frequency; Poisson Lognormal Random Effects Model; Risk; Signalized Intersections; Transportation Modes; Urban Intersections; Bicycle Crashes; Motor-vehicle; Riders; Infrastructure; China; Severity; Frequency Distribution; Risk Factors; Bicycles; Fatalities; Collisions; Traffic Accidents; Safety Programs; Urban Environments; Traffic Safety; Population Density; Crashes; Streets; Environmental Effects; Environmental Engineering; Roads; Land Use; Risk Analysis; Urban Areas; Road Design; Construction; Ecological Risk Assessment; Design Factors; Motorcycles; Urban Transportation; Studies; Safety Management; Beijing China
Sheth, Manali; Butrina, Polina; Goodchild, Anne; McCormack, Edward. (2019). Measuring Delivery Route Cost Trade-Offs between Electric-Assist Cargo Bicycles and Delivery Trucks in Dense Urban Areas. European Transport Research Review, 11(1).
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Abstract
Introduction: Completing urban freight deliveries is increasingly a challenge in congested urban areas, particularly when delivery trucks are required to meet time windows. Depending on the route characteristics, Electric Assist (EA) cargo bicycles may serve as an economically viable alternative to delivery trucks. The purpose of this paper is to compare the delivery route cost trade-offs between box delivery trucks and EA cargo bicycles that have the same route and delivery characteristics, and to explore the question, under what conditions do EA cargo bikes perform at a lower cost than typical delivery trucks? Methods: The independent variables, constant variables, and assumptions used for the cost function comparison model were gathered through data collection and a literature review. A delivery route in Seattle was observed and used as the base case; the same route was then modelled using EA cargo bicycles. Four separate delivery scenarios were modeled to evaluate how the following independent route characteristics would impact delivery route cost - distance between a distribution center (DC) and a neighborhood, number of stops, distance between each stop, and number of parcels per stop. Results: The analysis shows that three of the four modeled route characteristics affect the cost trade-offs between delivery trucks and EA cargo bikes. EA cargo bikes are more cost effective than delivery trucks for deliveries in close proximity to the DC (less than 2 miles for the observed delivery route with 50 parcels per stop and less than 6 miles for the hypothetical delivery route with 10 parcels per stop) and at which there is a high density of residential units and low delivery volumes per stop. Conclusion: Delivery trucks are more cost effective for greater distances from the DC and for large volume deliveries to one stop.
Keywords
Transportation; Sustainable Transportation; Parcel Post; Tricycles; Warehouses; Metropolitan Areas; Cargo Bicycles; Cargo Bike; Delivery Modes; E-trike; Electric Assist Cargo Bicycle; Electric Tricycle; Green Transportation; Parcel Deliveries; Urban Deliveries; Urban Logistics