Case Study Tag: Roadway departure

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.

High-Speed Lane Separation Project

Michigan
US-31/M-72 had frequent fog, blowing snow, and a severe crash pattern. After adding a center median, edgeline and centerline corrugations, guardrail, new pavement, and a flashing low visibility warning system, the segment had less severe crashes.

Oklahoma Safety Performance Measures

Oklahoma
Oklahoma DOT uses safety performance measures to identify and address safety issues like roadway departure, wrong-way driving, and work zone safety.

Safety Circuit Rider Program

Virginia
The Safety Circuit Rider program provides training and technical assistance to improve safety on local roadways.

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.

FoRRRwD in Massachusetts

Massachusetts
MassDOT’s FoRRRwD initiative provided municipalities with low-cost safety countermeasures. As countermeasures were implemented, MassDOT noted reduced crashes and serious injuries from crashes.

Enhancing Nighttime Visibility for Safety

FHWA
The nighttime fatality rate on the nation's roadways is three times higher than the daytime rate, and 76% of pedestrian fatalities occur at night. FHWA offers tools including safety countermeasures, updated and new approaches for lighting design and traffic control devices.

Local and Tribal Match Road Safety Program

FHWA
FHWA’s Match program connects local and tribal agencies with peer mentors to help resolve local and tribal road safety issues.

Mumble Strip and Stripe Research and Evaluation

Arkansas
ARDOT evaluated mumble strips as a variation of rumble strips that reduce noise pollution while maintaining driver safety. They found comparable safety effectiveness with less environmental impact.