Browsing by Author "Levinson, David, M"

Now showing 1 - 8 of 8
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    Accessibility Analysis of Risk Severity
    (2015) Cui, Mengying; Levinson, David, M
    Risk severity in transportation network analysis is defined as the effects of a link or network failure on the whole system. Change accessibility (reduction in the number of jobs which can be reached) is used as an integrated indicator to reflect the severity of a link outage. The changes of accessibility before-and-after the removing of a freeway segment from the network represent its risk severity. The analysis in the Minneapolis - St. Paul (Twin Cities) region show that links near downtown Minneapolis have relative higher risk severity than those in rural area. The geographical distribution of links with the highest risk severity displays the property that these links tend to be near or at the intersection of freeways. Risk severity of these links based on the accessibility to jobs and to workers at different time thresholds and during different dayparts are also analyzed in the paper. The research finds that network structure measures: betweenness, straightness and closeness, help explain the severity of loss due to network outage.
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    Accessibility and Centrality Based Estimation of Urban Pedestrian Activity
    (2015) Murphy, Brendan; Levinson, David, M; Owen, Andrew
    Non-motorized transportation, particularly including walking and bicycling, are increasingly becoming important modes in modern cities, for reasons including individual and societal wellness, avoiding negative environmental impacts of other modes, and resource availability. Institutions governing development and management of urban areas are increasingly keen to include walking and bicycling in urban planning and engineering; however, proper placement of improvements and treatments depends on the availability of good usage data. This study attempts to predict pedestrian activity at 1123 intersections in the Midwestern, US city of Minneapolis, Minnesota, using scalable and transferable predictive variables such as economic accessibility by sector, betweenness network centrality, and automobile traffic levels. Accessibility to jobs by walking and transit, automobile traffic, and accessibility to certain economic job categories (Education, Finance) were found to be significant predictors of increased pedestrian traffic, while accessibility to other economic job categories (Management, Utilities) were found to be significant predictors of decreased pedestrian traffic. Betweenness centrality was not found to be a significant predictor of pedestrian traffic, however the specific calculation methodology can be further tailored to reflect real-world pedestrian use-cases in urban areas. Accessibility-based analysis may provide city planners and engineers with an additional tool to predict pedestrian and bicycle traffic where counts may be difficult to obtain, or otherwise unavailable.
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    Accessibility and the Ring of Unreliability
    (2016) Cui, Mengying; Levinson, David, M
    This study measures the variability of job accessibility via automobile for the Minneapolis-St. Paul region. The accessibility analysis uses cumulative opportunity measures. The travel times on the network are tested at various level (10th percentile speed, 50th percentile speed, 90th percentile speed) using the TomTom speed data for 2010. It is shown that accessibility varies widely day-to-day as travel speeds on the network vary. Some parts of the region (a ring around the core) have more volatility in accessibility (and are thus less reliable) than others.
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    Accessibility and Transit Performance
    (2015) Ermagun, Alireza; Levinson, David, M
    This study disentangles the impact of financial and physical dimensions of transit service operators on net transit accessibility for 46 of the 50 largest metropolitan areas in the United States. To investigate this interaction along with the production efficiency of transit agencies, two types of analysis are used: a set of linear and quadratic regressions and a data envelopment analysis. We find that vehicle revenue kilometers and operational expenses play a pivotal role in enhancing the accessibility to jobs by transit. The bivariate linear regression models indicate a 1% increase in operational expenses and vehicle revenue kilometers increase the number of jobs that can be reached within 30 minutes by 0.96 and 0.95%, respectively. The results of the quadratic functional form, also, show transit services may have both increasing and decreasing accessibility returns to scale depending on system size, and the results are sensitive to the model used. Overall, the highest system efficiency (access produced per input) is found in the New York, Washington, and Milwaukee metropolitan areas, while Riverside, Detroit, and Austin perform with the lowest efficiency.
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    Cohort Effects and Their Influence on Car Ownership
    (2015) Iacono, Michael, J; Levinson, David, M
    Recent trends in the United States suggest a movement toward saturation of vehicle ownership. This paper examines this trend through an analysis of car ownership in the Minneapolis- St. Paul, Minnesota (USA) metropolitan region. Data from pooled cross-sectional household surveys are used to calibrate a model of car ownership that includes birth cohort effects to capture unobserved variations in preference toward car ownership across generations. Declines in household size and worker status have significant impacts in limiting the growth of car ownership, but they are also coupled by an apparent softening of preferences toward ownership among young adults.
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    The cost of equity: Assessing transit accessibility and social disparity using total travel cost
    (2016) El-Geneidy, Ahmed; Levinson, David, M; Diab, Ehab; Boisjoly, Genevieve; Verbich, David; Loong, Charis
    Social equity is increasingly incorporated as a long-term objective into urban transportation plans. Researchers used accessibility measures to assess equity issues, such as determining the amount of jobs reachable by marginalized groups within a defined travel time threshold and compare these measures across socioeconomic categories. However, allocating public transit resources in an equitable manner is not only related to travel time, but also related to the out-of- pocket cost of transit fares, which can represent a major barrier to accessibility for many disadvantaged groups. Therefore, this research proposes a set of new accessibility measures that incorporates both travel time and transit fares. It then applies those measures to determine whether people residing in socially disadvantaged neighborhoods in Montreal, Canada experience the same levels of transit accessibility as those living in other neighborhoods. Results are presented in terms of regional accessibility and trends by social indicator decile. Travel time accessibility measures estimate a higher number of jobs that can be reached compared to combined travel time and cost measures. However, the degree and impact of these measures varies across the social deciles. Compared to other groups in the region, residents of socially disadvantaged areas have more equitable accessibility to jobs using transit; this is reflected in smaller decreases in accessibility when fare costs are included. Generating new measures of accessibility combining travel time and transit fares provides more accurate measures that can be easily communicated by transportation planners and engineers to policy makers and the public since it translates accessibility measures to a dollar value.
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    An empirical study of the deviation between actual and shortest travel time paths
    (2015) Tang, Wenyun; Levinson, David, M
    Few empirical studies of revealed route characteristics have been reported in the literature. This study challenges the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis - St. Paul metropolitan area, as measured by the GPS Component of the 2011 Twin Cities Travel Behavior Inventory. It finds that most travelers used paths longer than the shortest path. Some reasons for this are conjectured.
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    Physical Activity in School Travel: A Cross-Nested Logit Approach
    (2016) Ermagun, Alireza; Levinson, David, M
    This paper considers school access by both active (walk, bike), quasi-active (walk to transit) and non-active modes (car) in a two-level cross-nested logit framework. A sample of 3,272 middle and high school students was collected in Tehran. The results of the cross-nested logit model suggest that for people who choose walking, increasing a 1 percent in home-to-school distance reduces the probability of walking by 3.51 percent. While, this reduction is equal to 2.82 and 2.27 percent as per the multinomial and nested logit models, respectively. This is a direct consequence of the model specification that results in underestimating the effect of distance by 1.24 percent. It is also worth mentioning that, a one percent increase in home-to-school distance diminishes the probability of taking public transit by 1.04 among public transit users, while increases the probability of shifting to public transit from walking by 1.39 percent. Further, a one percent increase of the distance to public transport, decreases the probability of students' physical activity, approximately, 0.04 percent.