Influence pattern and utility evaluation of connected vehicle warning information on driving behavior: A case study...

Debris incidents pose a severe threat to freeway traffic safety; however, research on how debris affects driver behavior and on the design and evaluation of corresponding warning measures remains insufficient. This study employs an interconnected driving simulation platform to analyze the effects of illumination conditions, driver attributes (sex, age, and driving experience), and warning measures (voice prompt, traffic-cone warning, and variable message sign [VMS] prompt) on driving behavior in typical freeway debris scenarios.

Using driving simulation techniques, five key driving indicators, including lane-change point position, were selected to examine the interactive effects among multiple factors and their influence on critical safety metrics through significance testing and a generalized linear mixed-effects model (GLMEN). Furthermore, an entropy-weighted fuzzy comprehensive evaluation was adopted to quantify the overall utility of each warning measure.

The results indicate that warning measures significantly affected drivers' speed control, steering operation, lane-change awareness, and longitudinal control. Among the evaluated measures, the voice prompt showed the best overall performance, achieving the highest safety utility scores under both daytime and nighttime conditions. The scores were 75.10 and 77.27, representing approximately 5.2% and 8.1% improvements compared with the corresponding no-warning scenarios, respectively.

Drivers with longer driving experience and middle-aged drivers demonstrate greater stability in speed control and lateral operations. Female drivers show smoother speed regulation, whereas male drivers exhibit higher stability in lateral maneuvers. Among the evaluated measures, the voice prompt performs best, markedly improving drivers' operational stability. This study provides new theoretical insights into freeway debris management and offers a valuable reference for developing practical warning-system strategies.