Optimization method to reduce the risky driving behaviors of ride-hailing drivers.

Introduction: To promote the safety level of ride-hailing services, this study develops the Targeted and Differentiated Optimization Method of Risky Driving Behavior Education and Training (TDOM-RDBET) founded on driver type classification of high-risk drivers.
Method: Based on value and goal orientations, 689 drivers were classified into four driver types and were assigned to three groups, including an experimental group, a blank control group, and a general control group. This research preliminarily analyzes the effectiveness of the TDOM-RDBET to reduce mobile phone use while driving by assessing the main effects of the group and test session on the risk value ranking of mobile phone use while driving (AR), the frequency per 100 km of mobile phone use while driving (AF), and the frequency per 100 km of risky driving behaviors (AFR), as well as the interactive effects of the two factors on AR, AF, and AFR, based on a two-way analysis of variance (two-way ANOVA).
Results: The results demonstrate an overall significant reduction in AR (F = 8.653, p = 0.003), AF (F = 11.027, p = 0.001), and AFR (F = 8.072, p = 0.005) for the experimental group after training. Moreover, significant interactive effects of the driver group × test session on AR (F = 7.481, p = 0.001) and AF (F = 15.217, p < 0.001) were found. AR was significantly lower for the experimental group than for the blank control group (p < 0.05) in the post-training condition. Moreover, AF was also significantly lower for the experimental group than for the blank control group (p < 0.05) and general control group (p < 0.05) in the post-training condition.
Practical Applications: On the whole, it was preliminarily verified that the TDOM-RDBET is more effective than the general training method at modifying the risky driving behavior.
(Published by Elsevier Ltd.)