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Reducing risky driving: Assessing the impacts of an automatically-assigned, targeted web-based instruction program.

Matthew C Camden¹, Susan A Soccolich¹, Jeffrey S Hickman¹

¹Virginia Tech Transportation Institute, 3500 Transportation Research Blvd., Blacksburg, VA 24061, United States of America.

Journal of Safety Research

|December 19, 2019

Summary

A web-based instruction (WBI) program significantly reduced risky driving behaviors, including speeding, hard braking, and cornering. This targeted training program proved effective for all drivers, not just those completing the coursework.

Keywords:

Driver monitoring Implicit feedback Implicit goals Safety Speeding

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Area of Science:

Transportation safety
Driver behavior analysis
Human factors in driving

Background:

Driver behavior is the leading cause of traffic crashes.
Existing safety research highlights the need for effective interventions to modify driver actions.
Web-based instruction (WBI) offers a scalable platform for targeted driver training.

Purpose of the Study:

To evaluate the effectiveness of an automatically-assigned, targeted WBI program in reducing risky driving behaviors.
To determine if the WBI program impacts drivers who receive training and those who do not.
To identify which aspects of the WBI program are most effective in behavior modification.

Main Methods:

A quasi-experimental, within-subjects, multiple-baseline stepwise ABC design was employed.
Phase I: Baseline data collection.
Phase II: Driver awareness of the program.
Phase III: Implementation of the WBI program.

Main Results:

A significant reduction in risky driving behaviors was observed across all drivers following WBI implementation.
Excessive speeding decreased by 73.93% from baseline.
Drivers who received WBI showed significant reductions in speeding, hard braking, and hard cornering; the first assigned course was most impactful.

Conclusions:

The automatically-assigned, targeted WBI program effectively reduced risky driving behaviors for all drivers.
Hypothesized mechanisms include implicit feedback, goal setting, and increased driver accountability.
Fleet implementation can lead to fewer crashes, reduced insurance claims, lower premiums, and improved safety outcomes, potentially saving lives.