Browsing by Subject "Crash risk forecasting"
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Item Development of Guidelines for Permitted Left-Turn Phasing Using Flashing Yellow Arrows.(Minnesota Department of Transportation, 2015-06) Davis, Gary A.; Hourdos, John; Moshtagh, VahidThe objective of this project was to develop guidelines for time-of-day use of permitted left-turn phasing, which can then be implemented using flashing yellow arrows (FYA). This required determining how the risk for left-turn crashes varied as traffic-flow conditions varied during the course of a representative day. This was accomplished by developing statistical models, which expressed the risk of occurrence of a left-turn crash during a given hour as a function of the left-turn demand, the opposing traffic volume, and a classification of the approach with respect to the opposing traffic speed limit, the type of left-turn protection, and whether or not opposing left-turn traffic could obstruct sight distance. The models were embedded in a spreadsheet tool which will allow operations personnel to enter, for a candidate intersection approach, existing turning movement counts, and a classification of the approach with respect to speed limit, turn protection, and sight distance issues and receive a prediction of how the risk of left-turn crash occurrence varies throughout the day, relative to a user-specified reference condition.Item Pedestrian and Bicycle Crash Risk and Equity: Implications for Street Improvement Projects(2019-06) Lindsey, Greg; Tao, Tao; Wang, Jueyu; Cao, JasonTransportation managers need information about crash risk and equity to prioritize investments in street networks. This case study uses data from Minneapolis, Minnesota, to illustrate how estimates of pedestrian and bicycle crash risk and assessments of inequities in the distribution of that risk can inform prioritization of street improvement projects. Crash numbers and frequencies for pedestrian and bicycle crashes at intersections and mid-blocks in Minneapolis are determined for the 2005-2017 period. New models of pedestrian and bicycle crash risk at both intersections and mid-blocks that control for exposure are introduced and used to predict crashes at all intersections and mid-blocks in the city. Statistical tests are used to assess the equity of distribution of estimated crash risk between areas of concentrated poverty with majority-minority populations and other areas in the city. Crash indexes based on predicted crashes are used to illustrate how increased emphases can be placed on pedestrian and bicycle safety in street improvement rankings. Results show that pedestrian and bicycle crash risk is correlated with exposure, that different factors affect crash risk at intersections and mid-blocks, and that these factors differ for pedestrian and bicycle crashes. Results also show that mean crash risk is higher in neighborhoods with lower incomes and majority-minority populations. For street improvement projects in the city, different rankings result when segments are ranked according to modeled pedestrian and bicycle crash risk in addition to total crash rates based on historical numbers of crashes at particular locations. Results generally affirm efforts by the Minneapolis Department of Public Works to increase emphases on pedestrian and bicycle safety and equity in its prioritization of street improvements.