Drivers’ ability to distinguish consecutive horizontal curves

Abstract

Driver error in distinguishing preceding and upcoming horizontal curves can lead to single-vehicle fatal crashes. The 3D perspective views of different horizontal curve stimuli were used to examine a representative sample of volunteering drivers’ ability to distinguish consecutive horizontal curves. A probit model, developed using the recorded responses, revealed that differences in radius and deflection angle between the consecutive curves are more likely to influence, whereas radius and deflection angle of reference curve are less likely to influence drivers in distinguishing consecutive curves. The sensitivity analysis of the model parameters indicated a difference in radius between the consecutive curves as the most and deflection angle of reference curve as the least sensitive parameters. The estimated marginal effects are useful for evaluating the design and safety of consecutive curves from the drivers’ perspective. Finally, nomograms were developed for relevant applications.

'I Did Not See that Coming': A Latent Variable Structural Equation Model for Understanding the Effect of Road Predictability on Crashes Along Horizontal Curves

“…This finding implies that while the deflection angle of horizontal curves may not have a direct statistically significant effect on crashes, larger differences in such deflection angles are associated with lower predictability that, in turn, increases the likelihood of crashes. This finding is in-line with the finding by (Sil et al, 2022) who found that differences in radius and deflection angle between consecutive curves are more likely to influence drivers' ability to distinguish preceding and upcoming curves compared to only the radius and deflection angle of the reference curve. Similarly, the negative parameters of curve preceded by a straight segment, absolute difference in vertical grades, and absolute difference in road width indicate that predictability decreases if there is a significant change in road geometry.…”

Exploring road safety using alignment perspective features in real driving images: A case study on mountain freeways

“…While driving, drivers visually observe the scene of the road ahead, which is projected onto their retinas, forming the alignment perspective views. In fact, the perspective view is considered a critical method for evaluating the effectiveness of road alignment design, since it can reflect the intrinsic characteristics of road alignment from the driver’s perspective [ 19 , 20 ].…”