Seeing through eyes of Drivers: Space consideration in investigating visibility of Vulnerable road users involved in crashes from Driver's perspective.

Vulnerable Road User's (VRUs) invisibility by vehicle drivers hasn't been well explored despite having a substantial influence on crash involvement and resulting severity level. Additionally, obtaining comparison crashes for analysis of the VRU invisibility has been a challenge. For that reason, this study used crashes that occurred between 2017 and 2022 in Ohio to understand VRU invisibility from the driver's perspective. The study further proposes the comparison of crashes as those that occurred within 250 feet of the crashes involving drivers not seeing the VRU. Two logistic regression models, one for the entire dataset (full model) and the second for only crashes that occurred within 250 feet (space-constrained model), were developed. It was found that the results from the full model and space-constrained model differ significantly in terms of the magnitude and the direction of the effect. Using the space-constrained model, the topmost key factors associated with the highest likelihood of VRU invisibility are lighting conditions, pre-action of the driver, and senior VRU involvement. Further, text network analysis was performed to understand the key reasons for VRU invisibility. The text network revealed that the VRU invisibility related to left turning pre-action was due to the driver's failure to yield at an intersection's pedestrian crossing. Further, the most invisible VRUs in the dark conditions were on the side of the roadway. Additionally, drivers backing up were more likely to report that they did not see pedestrians walking behind them. Lastly, senior-related crashes were associated with crossing in front of turning vehicles. The findings can be utilized to enhance VRU visibility at various locations to improve safety.