Dataset Information

Evaluating the impacts of grades on vehicular speeds on interstate highways.

ABSTRACT: Grade variation on interstate highways affects the roadway geometric design, vehicle performance and driver behavior, thus possibly exerting an unexpected effect on vehicular speed. Hence, determining the internal relationship between grade and speed is important and useful for drivers, traffic regulators and other traffic participants. However, the problem with performing this research is the lack of large-scale gradient and speed data. Google Earth (GE) provides an application programming interface for extracting elevation data worldwide. The elevation dataset from GE can be easily converted to grade data. In addition, our team has collected and stored speed series data for different freeways over several years. Based on the above obtainable grade and speed datasets, we conducted research on the effect of grades on free flow speeds from two perspectives. First, the influence of grades on speed was analyzed from both quantitative and qualitative aspects. The analysis of the distributions of four typical types of speeds demonstrated a decreasing tendency as the speed increased. Steeper grades generated a more intense speed fluctuation in terms of the four types of speeds. Second, a model based on the Student's t-test was developed to evaluate the level of significant difference among speed series under neighboring grades. The Student's t-test demonstrated that adjacent grades do not significantly influence the speeds. In summary, speeds under different grades showed obviously different tendencies. The findings of this study can help transport authorities set more reasonable speed limits and improve the geometric design of interstates with grade variation constraints.

SUBMITTER: Chen X

PROVIDER: S-EPMC5581186 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Evaluating the impacts of grades on vehicular speeds on interstate highways.

Chen Xinqiang X Li Zhibin Z Wang Yinhai Y Cui Zhiyong Z Shi Chaojian C Wu Huafeng H

PloS one 20170901 9

Grade variation on interstate highways affects the roadway geometric design, vehicle performance and driver behavior, thus possibly exerting an unexpected effect on vehicular speed. Hence, determining the internal relationship between grade and speed is important and useful for drivers, traffic regulators and other traffic participants. However, the problem with performing this research is the lack of large-scale gradient and speed data. Google Earth (GE) provides an application programming inte ...[more]

PMID: 28863157

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Project description:BACKGROUND:Reliable predictions of regional-scale population connectivity are needed to prioritize conservation actions. However, there have been few examples of regional connectivity models that are empirically derived and validated. The central goals of this paper were to (1) evaluate the effectiveness of factorial least cost path corridor mapping on an empirical resistance surface in reflecting the frequency of highway crossings by American black bear, (2) predict the location and predicted intensity of use of movement corridors for American black bear, and (3) identify where these corridors cross major highways and rank the intensity of these crossings. RESULTS:We used factorial least cost path modeling coupled with resistant kernel analysis to predict a network of movement corridors across a 30.2 million hectare analysis area in Montana and Idaho, USA. Factorial least cost path corridor mapping was associated with the locations of actual bear highway crossings. We identified corridor-highway intersections and ranked these based on corridor strength. We found that a major wildlife crossing overpass structure was located close to one of the most intense predicted corridors, and that the vast majority of the predicted corridor network was "protected" under federal management. However, narrow, linear corridors connecting the Greater Yellowstone Ecosystem to the rest of the analysis area had limited protection by federal ownership, making these additionally vulnerable to habitat loss and fragmentation. CONCLUSIONS:Factorial least cost path modeling coupled with resistant kernel analysis provides detailed, synoptic information about connectivity across populations that vary in distribution and density in complex landscapes. Specifically, our results could be used to quantify the structure of the connectivity network, identify critical linkage nodes and core areas, map potential barriers and fracture zones, and prioritize locations for mitigation, restoration and conservation actions.

Dataset Information

Evaluating the impacts of grades on vehicular speeds on interstate highways.

Publications

Evaluating the impacts of grades on vehicular speeds on interstate highways.

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