Case Study Tag: Systemic approach

AASHTOWare: Prioritizing Roadway Departure Crashes

AASHTO
AASHTOWare compares and contrasts three methods for safety improvement location identification: 1) crash prediction model, 2) expected crash frequency exceeding threshold, and 3) crash prediction model + systemic safety characteristics.

FDOT’s Statewide Systemic Analysis

Florida
FDOT uses a data-driven, risk-based approach to guide systemic investments. Their systemic analysis led FDOT leadership to approve $35 million in HSIP funds, plus additional state funding for safety investments.

Louisiana Vulnerable Road User (VRU) Safety Assessment

Louisiana
Using a systematic, data-driven approach, Louisiana’s VRU Safety Assessment identified target areas for improvements and recommended infrastructure countermeasures, education, programs and policies. Priority factors were mapped to focus on areas for project implementation.

Don’t Wait, Be Proactive! Systemic Safety for Minnesota’s District Safety Plans

Minnesota
MnDOT updated road safety plans in every district with a systemic crash analysis. Analysis confirmed that higher crash densities and severe crashes occurred at locations with higher risk scores.

Lane Constrictor Intersections in Minnesota

Minnesota
Concerned with rural intersections crashes, MnDOT developed a standard layout of lane constrictors. They installed lane constrictors at 61 side street, stop-controlled locations.

A Comprehensive Approach for Friction-Enhancing Treatment Selection

Kentucky
Kentucky replaced a needs-based, hot-spot approach with a more precise, systemic, “solutions-based” approach to friction-enhancing treatments and improved pavement safety performance.

Systemic Safety Countermeasures and Collaborative Approaches at GDOT

Georgia
Georgia DOT uses crash data analysis to implement proactive, systemic safety countermeasures, improve safety for vulnerable users, optimize project delivery, and target unsafe driving behaviors.

Systemic Countermeasures Implementation and Tracking

Virginia
Virginia DOT created a statewide inventory and tracking system for the performance of countermeasures, leading to better communication among employees and partners, and the ability to track ongoing progress.

A Machine Learning Approach to Systemic Safety Project Location Identification

Ohio
ODOT used machine learning to identify locations for systemic safety projects, focusing on pedestrian and roadway departure crashes.

Pedestrian Safety Improvements in Project Planning and Scoping

Nebraska
Nebraska DOT uses a variety of data analysis and screening methods during project planning and scoping to select countermeasures. Methods are also applied to systemic safety projects.