题名: |
Use of Roadway Attribution in Hot Spot Identification and Analysis. |
作者: |
Schultz, G. G.; Bassett, D. R.; Saito, M.; Reese, C. S. |
关键词: |
Crash prediction, Transportation safety, Utah Crash Prediction Model(USPM), Hierarchical bayes, Empirical bayes, Highway Safety Manual(HSM), Poisson mixture model, Crash analysis, Hot spots, Safety, Roadway attributes |
摘要: |
This research focuses on the addition of roadway attributes in the selection and analysis of "hot spots." This is in conjunction with the framework for highway safety mitigation in Utah with its six primary steps: network screening, diagnosis, countermeasure selection, economic appraisal, project prioritization, and effectiveness evaluation. The addition of roadway attributes was included as part of the network screening, diagnosis, and countermeasure selection, which are included in the methodology titled "Hot Spot Identification and Analysis" in UDOT Report No. UT-13.15. Included in this research was the documentation of the steps and process for data preparation and model use for the step of network screening and the creation of report forms for the steps of diagnosis and countermeasure selection. The addition of roadway attributes is required at numerous points in the process. Methods were developed to locate and evaluate the usefulness of available data. Procedures and systemization were created to convert raw data into new roadway attributes, such as grade and vertical sag/crest curve location. For the roadway attributes to data into new roadway attributes, such as grade and vertical sag/crest curve location. For the roadway attributes to problem segments and problem spots. The methodology for "Hot Spot Identification and Analysis" was enhanced to include steps for inclusion and defining of the roadway attributes. These methods and procedures were used to help in the identification of safety hot spots to be analyzed and countermeasures selected. Examples of how the methods are to function are given with sites from Utah’s state roadway network. |
总页数: |
Schultz, G. G.; Bassett, D. R.; Saito, M.; Reese, C. S. |
报告类型: |
科技报告 |