A Pedestrian Exposure Model for the California State Highway System

Griswold, Julia B.; Medury, Aditya; Schneider, Robert J.; Amos, Dave; Li, Ang; Grembek, Offer

doi:10.1177/0361198119837235

Cited by 11 publications

(19 citation statements)

References 17 publications

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“…Pedestrian demand models are most common at the local level (7, 13-18), but they could also be applied across metropolitan regions and states (10). To our knowledge, California currently has the only statewide pedestrian volume model (19).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Common explanatory variables include measures of population or housing density, employment density, commercial retail density, and transit stop proximity and service frequency (4, 7). Explanatory variables are often collected at several different distances from the count location (i.e., different buffer widths) to identify the most influential scale of a particular characteristic on pedestrian activity (3,4,15,(17)(18)(19)(20). Many models include these common variables, but the magnitude and direction of influence of these variables in specific models can be different depending on the study area (4).…”

Section: Literature Reviewmentioning

confidence: 99%

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Development and Validation of a Seven-County Regional Pedestrian Volume Model

Schneider

Schmitz

Qin

2021

Transportation Research Record: Journal of the Transportation R

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This study describes the development and validation of pedestrian intersection crossing volume models for the seven-county Milwaukee metropolitan region. The set of three models, among the first developed at a multi-county scale, can be used to estimate the total number of pedestrian crossings per year at four-leg intersections along state highways and other major thoroughfares. Outputs are appropriate for annual volumes ranging from 1,000 to 650,000. We used negative binomial regression to relate annual pedestrian volumes at 260 intersections to roadway and surrounding neighborhood socioeconomic and land-use variables. The three models include seven variables that have significant positive associations with annual pedestrian volume: population density within 400 m of the intersection; employment density within 400 m; number of bus stops within 100 m; number of retail businesses within 100 m; number of restaurant and bar businesses within 100 m; presence of a school within 400 m; and proportion of households without a motor vehicle within 400 m. Results suggest that square root or cube root transformations of continuous explanatory variables could potentially improve model fit. The models have fair accuracy, with each of the three model formulations predicting 60% or more of validation intersection counts to within half or double the observed value. Future research could address overprediction by creating new variables to better represent the number of lanes on each intersection leg and low socioeconomic status of adjacent neighborhoods.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Development and Validation of a Seven-County Regional Pedestrian Volume Model

Schneider

Schmitz

Qin

2021

Transportation Research Record: Journal of the Transportation R

Self Cite

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“…For example, safety analysis requires measures of pedestrian exposure at the level of intersections and street segments. If the relationships inherent to direct-demand built-environment models of pedestrian volumes ( 59 , 60 ) are changing, then static estimates of activity may not reflect true pedestrian risk. This is particularly important because preliminary 2020 U.S. traffic safety data show a troubling continued increase in pedestrian deaths despite significant decreases in vehicle distances traveled ( 61 ).…”

Section: Discussionmentioning

confidence: 99%

Pedestrians and the Built Environment during the COVID-19 Pandemic: Changing Relationships by the Pandemic Phases in Salt Lake County, Utah, U.S.A.

Park

Singleton

Brewer

et al. 2022

Transportation Research Record: Journal of the Transportation R

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The COVID-19 pandemic has dramatically altered people’s travel behavior, in particular outdoor activities, including walking. Their behavior changes may have prolonged effects after the pandemic, and such changes vary by the context and are related to the characteristics of the built environment. But empirical studies about the relationships between pedestrians and the built environment during the pandemic are lacking. This study explores how COVID-19 and related travel restrictions have affected the relationship between pedestrian traffic volume and the built environment. We estimate daily pedestrian volumes for all signalized intersections in Salt Lake County, Utah, U.S.A., from pedestrian push-button log data between January 2019 and October 2020. Multilevel spatial filtering models show that the COVID-19 pandemic has altered the relationship between pedestrian traffic volume and the built environment. During the pandemic, the higher the number of COVID-19 cases, the less (or more negative) the effects of density, street connectivity, and destination accessibility on pedestrian volume being observed. The exception is access to urban parks, as it became more significant in increasing pedestrian activities during the pandemic. The models also highlight the negative impacts of the pandemic in economically disadvantaged areas. Our findings could help urban and transportation planners find effective interventions to promote active transportation and physical activity amid the global pandemic.

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“…The total of the overlaps produced the estimates of socioeconomic/demographic variables at each intersection. The specific variables considered included those that had known relationships with pedestrian exposure in the research literature, as identified in Frank et al ( 13 ), Griswold et al ( 14 ), Hampshire et al ( 15 ), and Hankey et al ( 16 ).…”

Section: Data Summarymentioning

confidence: 99%

“…However, direct measures are often expensive and difficult to implement over a large study area (e.g., a city or region). Previous research efforts have successfully developed pedestrian exposure models to address research needs in safety and public health ( 13 – 16 ). Furthermore, emerging data sources, such as vehicular probe data, have demonstrated applicability as transportation performance monitoring tools ( 17 , 18 ).…”

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confidence: 99%

Application of Emerging Data Sources for Pedestrian Safety Analysis in Charlotte, NC

Hamilton¹,

Kersavage²,

Porter³

et al. 2022

Transportation Research Record: Journal of the Transportation R

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Pedestrian safety is a growing concern for transportation planners and safety engineers at both local and state levels. Continued advancements in data availability, data integration abilities, and analysis methodologies offer new opportunities to identify factors influencing pedestrian safety and to quantify their effects to inform data-driven road safety management. The main objective of this study was to spatially integrate Highway Safety Information System data with multijurisdictional and emerging datasets to analyze two measures of pedestrian safety performance in Charlotte, NC: (1) the severity of a pedestrian crash that has occurred, and (2) the probability that a pedestrian crash will occur on a given roadway segment. To accomplish the objectives, the study explored several high-priority research topics in safety data and analysis, including pedestrian exposure analysis and probe data integration. The research team developed a pedestrian count model to predict pedestrian volumes at locations without pedestrian counts and integrated speed information from probe data to supplement other roadway and contextual transportation data available from several agencies. Pedestrian exposure at a given intersection was found to be significantly influenced by demographic and socioeconomic characteristics, employment, land use, sidewalk presence, transit access, and roadway and intersection characteristics. The project team identified numerous significant factors that influenced pedestrian crash severity and probability, including outputs from the pedestrian exposure model, observed vehicle speeds, traffic volumes, intersection proximity, and other crash-related factors. The results could be used to identify locations that are more susceptible to pedestrian safety issues.

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A Pedestrian Exposure Model for the California State Highway System

Cited by 11 publications

References 17 publications

Development and Validation of a Seven-County Regional Pedestrian Volume Model

Development and Validation of a Seven-County Regional Pedestrian Volume Model

Pedestrians and the Built Environment during the COVID-19 Pandemic: Changing Relationships by the Pandemic Phases in Salt Lake County, Utah, U.S.A.

Application of Emerging Data Sources for Pedestrian Safety Analysis in Charlotte, NC

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