Chen, Peng; Zhou, Jiangping. (2016). Effects of the Built Environment on Automobile-involved Pedestrian Crash Frequency and Risk. Journal Of Transport & Health, 3(4), 448 – 456.
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Abstract
This area-based study explores the relationship between automobile-involved pedestrian crash frequency versus risk and various built environment factors such as road network and land use. The methodology involves the use of Bayesian hierarchical intrinsic conditional autoregressive model, which accounts for unobserved heterogeneities and spatial autocorrelations. The city of Seattle is selected for this empirical study, and the geospatial unit of analysis is traffic analysis zone. The primary data were obtained from collision profiles available at the Seattle Department of Transportation. The major findings of this study include: (1) the densities of 4-way intersections and more than 5-way intersections and land use mixture are positively correlated with the pedestrian crash frequency and risk; (2) sidewalk density and the proportion of steep areas are negatively associated with the pedestrian crash frequency and risk; (3) areas with a higher bus stop density are likely to have more pedestrian crashes; (4) areas with a greater proportion of industrial land use have lower pedestrian crash frequency; (5) areas with an averagely higher posted speed limit has higher pedestrian crash risk; (6) areas with a higher employment density has lower pedestrian crash risk; (7) the mode share of walking and the total number of trips are positively correlated with the pedestrian crash frequency, and the total number of trips is negatively correlated with the pedestrian crash risk. These findings provide support for planning policy making and road safety programs. Local authorities should improve walkability by providing more sidewalks and separate travel lanes for motorized traffic and pedestrians in areas with different land use purposes. Compact development should be encouraged to support building a safe walking environment. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Spatial-analysis; Urban Form; Land-use; Model; Counts; Transportation; Severity; Bicycle; Safety; Travel; Pedestrian Crash Frequency; Pedestrian Crash Risk; Built Environment; Spatial Autocorrelation; Road Network; Land Use
Yang, Liya; Shen, Qing; Li, Zhibin. (2016). Comparing Travel Mode and Trip Chain Choices Between Holidays and Weekdays. Transportation Research Part A: Policy & Practice, 91, 273 – 285.
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Abstract
Choices of travel mode and trip chain as well as their interplays have long drawn the interests of researchers. However, few studies have examined the differences in the travel behaviors between holidays and weekdays. This paper compares the choice of travel mode and trip chain between holidays and weekdays tours using travel survey data from Beijing, China. Nested Logit (NL) models with alternative nesting structures are estimated to analyze the decision process of travelers. Results show that there are at least three differences between commuting-based tours on weekdays and non-commuting tours on holidays. First, the decision structures in weekday and holiday tours are opposite. In weekday tours people prefer to decide on trip chain pattern prior to choosing travel mode, whereas in holiday tours travel mode is chosen first. Second, holiday tours show stronger dependency on cars than weekday tours. Third, travelers on holidays are more sensitive to changes in tour time than to the changes in tour cost, while commuters on weekdays are more sensitive to tour cost. Findings are helpful for improving travel activity modeling and designing differential transportation system management strategies for weekdays and holidays. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Choice Of Transportation; Transportation Management; Voyages & Travels; Travel Costs; Travel Time (traffic Engineering); Decision Structure; Nested Logit Model; Policy; Travel Behavior; Patterns; Behavior; Time
Kang, Mingyu; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Capturing Fine-Scale Travel Behaviors: A Comparative Analysis between Personal Activity Location Measurement System (PALMS) and Travel Diary. International Journal Of Health Geographics, 17(1).
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Abstract
BackgroundDevice-collected data from GPS and accelerometers for identifying active travel behaviors have dramatically changed research methods in transportation planning and public health. Automated algorithms have helped researchers to process large datasets with likely fewer errors than found in other collection methods (e.g., self-report travel diary). In this study, we compared travel modes identified by a commonly used automated algorithm (PALMS) that integrates GPS and accelerometer data with those obtained from travel diary estimates.MethodsSixty participants, who made 2100 trips during seven consecutive days of data collection, were selected from among the baseline sample of a project examining the travel behavior impact of a new light rail system in the greater Seattle, WA (USA) area. GPS point level analyses were first conducted to compare trip/place and travel mode detection results using contingency tables. Trip level analyses were then performed to investigate the effect of proportions of time overlap between travel logs and device-collected data on agreement rates. Global performance (with all subjects' data combined) and subject-level performance of the algorithm were compared at the trip level.ResultsAt the GPS point level, the overall agreement rate of travel mode detection was 77.4% between PALMS and the travel diary. The agreement rate for vehicular trip detection (84.5%) was higher than for bicycling (53.5%) and walking (58.2%). At the trip level, the global performance and subject-level performance of the PALMS algorithm were 46.4% and 42.4%, respectively. Vehicular trip detection showed highest agreement rates in all analyses. Study participants' primary travel mode and car ownership were significantly related to the subject-level mode agreement rates.ConclusionsThe PALMS algorithm showed moderate identification power at the GPS point level. However, trip level analyses found lower agreement rates between PALMS and travel diary data, especially for active transportation. Testing different PALMS parameter settings may serve to improve the detection of active travel and help expand PALMS's applicability in geographically different urbanized areas with a variety of travel modes.
Keywords
Transportation Planning; Public Health; Accelerometers; Global Positioning System; Voyages & Travels; Cycling; Algorithms; Accelerometer; Automated Algorithm; Gis; Gps; Places; Trips; Global Positioning Systems; Physical-activity; Data-collection; Health Research; Gps Data; Accelerometry; Validity
Bautista-Hernández, Dorian. (2020). Urban Structure and its Influence on Trip Chaining Complexity in the Mexico City Metropolitan Area. Urban, Planning And Transport Research, 8(1), 71 – 97.
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Abstract
This project studies the relationship between the urban structure of the Mexico City Metropolitan Area (MCMA) and two aspects of commuter travel patterns: (1) number of stops in a tour and (2) complexity of trip chaining. Two regression models were explored, one for each dependent variable of interest. The analysis was applied for car drivers, transit users and travelers with mixed transportation separately. Covariates include individual, household, travel and urban form variables, which showed differential effects according to the transportation mode. According to the number of significant covariates, it can be said that there is less impact of urban form on trip generation and complexity of travel for car drivers (only mixed land use at destination being significant for complexity of travel) and mixed transportation (being only significant job access for complexity of travel) than for transit users (being significant job access, population density, mixed land use at origin for extra trip, number of trips and complexity of travel). The directions of these effects vary according to the transportation mode and are discussed in terms of reported literature.
Keywords
Trip Generation; Urban Structures; Chaining; Drivers; Population Density; Land Use; Regression Analysis; Regression Models; Transportation; Travel; Complexity; Automobile Drivers; Metropolitan Areas; Travel Patterns; Urban Areas; Dependent Variables; Mexico
Chen, Chen; Lindell, Michael K.; Wang, Haizhong. (2021). Tsunami Preparedness and Resilience in the Cascadia Subduction Zone: A Multistage Model of Expected Evacuation Decisions and Mode Choice. International Journal Of Disaster Risk Reduction, 59.
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Abstract
Physical scientists have estimated that the Cascadia Subduction Zone (CSZ) has as much as a 25% chance to produce a M9.0 earthquake and tsunami in the next 50 years, but few studies have used survey data to assess household risk perceptions, emergency preparedness, and evacuation intentions. To understand these phenomena, this study conducted a mail-based household questionnaire using the Protective Action Decision Model (PADM) as a guide to collect 483 responses from two coastal communities in the CSZ: Crescent City, CA and Coos Bay, OR. We applied multistage regression models to assess the effects of critical PADM variables. The results showed that three psychological variables (risk perception, perceived hazard knowledge, and evacuation mode efficacy) were associated with some demographic variables and experience variables. Evacuation intention and evacuation mode choice are associated with those psychological variables but not with demographic variables. Contrary to previous studies, location and experience had no direct impact on evacuation intention or mode choice. We also analyzed expected evacuation mode compliance and the potential of using micro-mobility during tsunami response. This study provides empirical evidence of tsunami preparedness and intentions to support interdisciplinary evacuation modeling, tsunami hazard education, community disaster preparedness, and resilience plans.
Keywords
False Discovery Rate; American-samoa; Earthquake; Washington; Behavior; Oregon; Wellington; Responses; Disaster; Tsunami Evacuation; Cascadia Subduction Zone; Risk Perception
Wang, Yiyuan; Moudon, Anne Vernez; Shen, Qing. (2022). How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region. Transportation Research Record, 2676(3), 621 – 633.
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Abstract
This study investigates the impacts of ride-hailing, which we define as mobility services consisting of both conventional taxis and app-based services offered by transportation network companies, on individual mode choice. We examine whether ride-hailing substitutes for or complements travel by driving, public transit, or walking and biking. The study overcomes some of the limitations of convenience samples or cross-sectional surveys used in past research by employing a longitudinal dataset of individual travel behavior and socio-demographic information. The data include three waves of travel log data collected between 2012 and 2018 in transit-rich areas of the Seattle region. We conducted individual-level panel data modeling, estimating independently pooled models and fixed-effect models of average daily trip count and duration for each mode, while controlling for various factors that affect travel behavior. The results provide evidence of substitution effects of ride-hailing on driving. We found that cross-sectionally, participants who used more ride-hailing tended to drive less, and that longitudinally, an increase in ride-hailing usage was associated with fewer driving trips. No significant associations were found between ride-hailing and public transit usage or walking and biking. Based on detailed travel data of a large population in a major U.S. metropolitan area, the study highlights the value of collecting and analyzing longitudinal data to understand the impacts of new mobility services.
Keywords
Shared Mobility; Ride-hailing; Longitudinal Data; Substitution Between Travel Modes; Complementarity Between Travel Modes; Services; Uber
Sohn, Dong Wook; Moudon, Anne Vernez; Lee, Jeasun. (2012). The Economic Value of Walkable Neighborhoods. Urban Design International, 17(2), 115 – 128.
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Abstract
This study investigated how the benefits of a walkable neighborhood were reflected in the American real estate market by examining the economic values of urban environmental factors supporting walking activities. Property values were used as a proxy measure for economic value and analyzed in relation to land use characteristics that have been known to correlate with walking at the neighborhood scale. Four aspects of the built environment supporting walking were included in the analyses: development density, land use mix, public open space and pedestrian infrastructure. Hedonic models were employed where the property value was regressed on the measures of the four sets of correlates of walking in a neighborhood. Models were estimated for four land use types - single-family residential, rental multi-family residential, commercial and office. The findings did not support previous arguments that increasing density weakens the quality of a neighborhood. To the contrary, the positive association of higher development density with the value of single-family residential properties detected in King County suggested that high development density might increase surrounding property values. The pedestrian infrastructure and land use mix significantly contributed to increases in rental multi-family residential property values. Higher development density with higher street and sidewalk coverage were also favored by retail service uses. In relation to land use mix, mixing retail service uses and rental multi-family residential uses helped make rental housings more attractive. URBAN DESIGN International (2012) 17, 115-128. doi:10.1057/udi.2012.1; published online 4 April 2012
Keywords
Land-use; Physical-activity; Travel Behavior; Smart Growth; Mode Choice; Urban Form; Walking; Gis; Transportation; Accessibility; Mixed Land Use; Neighborhood; Urban Design
Lee, Namhun; Schaufelberger, John E. (2014). Risk Management Strategies for Privatized Infrastructure Projects: Study of the Build-Operate-Transfer Approach in East Asia and the Pacific. Journal Of Management In Engineering, 30(3).
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Abstract
Private-public partnerships have been adopted for the development of public infrastructure to meet the growing demand for public services. Many Asian countries have used the build-operate-transfer (BOT) approach to develop public infrastructure projects. However, the potential benefits of undertaking a BOT project are accompanied by corresponding risks from the private sector's perspective. The objectives of this study are (1)to identify and discuss major risks inherent in the East Asia and Pacific regions, and (2)to propose risk management strategies for future BOT projects to be successful. This paper reports the results of five case study analyses undertaken to review their primary risks and mitigated methods. In addition, this paper proposes some strategies for future BOT projects. Two main categories of risks were analyzed: general risks and project-specific risks. Risk management strategies were suggested for each category of risk. The main finding of this study indicates that the private sector cannot be the only participant in risk management. The host government's active support is the most essential factor for the profitability and economic viability of a BOT project in the East Asia and Pacific regions.
Keywords
Organisational Aspects; Project Management; Public Administration; Public Utilities; Risk Management; Structural Engineering; Risk Management Strategies; Privatized Infrastructure Projects; Build-operate-transfer Approach; East Asia; Private-public Partnerships; Public Services; Asian Countries; Public Infrastructure Projects; Pacific Regions; Future Bot Projects; Project-specific Risks; General Risks; Build-operate-transfer; Privatized Infrastructure
Choi, Kunhee; Lee, Hyun Woo; Mao, Zhuting; Lavy, Sarel; Ryoo, Boong Yeol. (2016). Environmental, Economic, and Social Implications of Highway Concrete Rehabilitation Alternatives. Journal Of Construction Engineering And Management, 142(2).
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Abstract
Currently, there is no comprehensive benchmark of life-cycle assessment for the rigid pavement alternatives for highway rehabilitation. To fill this gap, the major objective of this study is to investigate the environmental, economic, and social impacts of the three most widely adopted rigid pavement choices through a life-cycle assessment approach with custom-built economic input-output life-cycle assessment (EIO-LCA) models. Quantity takeoffs were performed for each alternative assuming a 1-lane-km highway rehabilitation. Subsequently, the construction costs of each alternative were computed in order to determine the present values for a life span of 50years, while at the same time accounting for a different life expectancy for each pavement rehabilitation strategy. The present values were then incorporated into a corresponding EIO-LCA model. The results clearly indicate that continuously reinforced concrete pavement (CRCP) is the most sustainable choice and much preferable to the other alternatives for minimizing negative environmental, economic and social impacts from the life-cycle perspective. This finding champions a wider adoption of CRCP for future sustainable transportation infrastructure development projects, as CRCP's relatively high initial construction cost can be recouped by long-term sustained benefits. The results and findings of this study can serve as a solid foundation for industry practitioners and decision-makers to make better-informed project decisions when choosing the most sustainable pavement alternatives from a life-cycle perspective. (C) 2015 American Society of Civil Engineers.
Keywords
Construction Industry; Environmental Management; Life Cycle Costing; Product Life Cycle Management; Project Management; Reinforced Concrete; Road Building; Socio-economic Effects; Sustainable Development; Economic Implications; Environmental Implications; Industry Practitioners; Sustainable Transportation Infrastructure Development Projects; Continuously Reinforced Concrete Pavement; Crcp; Eio-lca Model; Life Span; Construction Costs; Custom-built Economic Input-output Life-cycle Assessment Models; Rigid Pavement Alternatives; Highway Concrete Rehabilitation Alternatives; Life-cycle Assessment Approach; Social Implications; Life-cycle Assessment; Pavement; Asphalt; Pavement Rehabilitation; Environmental Assessment; Economic Factors; Land Use
Chaix, Basile; Duncan, Dustin; Vallee, Julie; Vernez-moudon, Anne; Benmarhnia, Tarik; Kestens, Yan. (2017). The Residential Effect Fallacy in Neighborhood and Health Studies Formal Definition, Empirical Identification, and Correction. Epidemiology, 28(6), 789 – 797.
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Abstract
Background: Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this residential effect fallacy bias applicable to a large fraction of neighborhood and health studies. Methods: Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naive intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions). Results: There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naive model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naive estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8. Conclusions: Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.
Keywords
Self-rated Health; Record Cohort; Physical-activity; Transportation Modes; Built Environment; Activity Spaces; Research Agenda; Risk-factors; Associations; Exposure