The right turn: Modeling driver yielding behavior to e-scooter riders

Electric scooters (e-scooters) are a relatively new and popular means of personal transportation in many cities. Unfortunately, they have been involved in crashes with other road users with whom they share the infrastructure. Crashes with motorized vehicles are particularly critical since they result in more severe injuries or even fatalities. While previous work has highlighted the consequences of failed interactions, we know little about how drivers interact with e-scooters and how to improve such interactions. In this paper, we conducted a test-track experiment to study how drivers negotiate a right turn at an intersection with an e-scooter. Using Bayesian regression, we modeled whether drivers yield to the e-scooter according to the projected post-encroachment time and approaching speed, and we were able to predict drivers’ intentions with an AUC of 0.94 and an accuracy of 0.82 in cross-validation. The model coefficients indicate that drivers yield less often when approaching the intersection at a higher speed or larger projected gap. We further modeled drivers’ braking timing (time-to-arrival) and strength (mean deceleration), yielding an RMSE of 1.42 s and 0.33 m/s^2^, respectively. Being a reference for driver behavior when interacting with an e-scooter rider, the model can be integrated into simulations and inform the development driver support system to warn drivers more effectively.