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Human Perceptions of Vehicle Turning Intention

All pedestrians, drivers, and cyclists regularly make predictions about where they think an oncoming vehicle is intending to travel so that they can successfully and safely navigate road systems. Despite the importance of these predictions, the effectiveness of this process is currently poorly understood, as all existing research has been focused on predictions from in-vehicle technologies. This study investigated how well observers were able to predict a vehicle's turning intention as it approached an intersection. Logistic regression analysis was used to explore the explanatory variables involved in the success of this process. An interactive touch screen experiment was developed, and more than 100 participants attempted to predict the turning intention of several vehicles. The participants were very good overall at predicting turning intention, with a median success rate of approximately 90% when the vehicle was 0 to 20 m (0 to 21.9 yd) away from the intersection; however, the median success rate fell substantially to approximately 70% when the vehicle was 30 to 50 m (32.8 to 54.7 yd) away. Other key explanatory variables included both vehicle-specific factors (e.g., use of indicator lights) and, crucially, the intersection layout, which together provided valuable information on the relationship between intersection design and road safety.