Human predictions of another vehicle at an intersection

Abstract

Annually, thousands of lives are lost to traffic accidents. To improve the safety of all traffic participants, the understanding and modelling of the limitations of human behaviour in traffic have continuously been researched. Currently, there is a lack of existing research on human predictions of other vehicles in traffic beyond binary decisions, such as whether the pedestrian will cross or whether another vehicle will accept the gap. This study conducted a human factors experiment with a novel response method where 30 participants viewed 168 unique scenarios for 5 seconds and then had to predict the intended direction the other vehicle would continue at the intersection. The direction predictions are a measure of how likely humans think the observed vehicle will go forward, left or right at the intersection. Analysis of the results showed that the heading angle and the relative position of the other vehicle had the greatest influence on the predicted direction and confidence of the response. Blinker use and deceleration had a lesser impact on prediction direction but significantly affected confidence. The lateral offset showed no statistical significance on the responses. The results highlight the limitations and inconsistencies in human predictions for other vehicles, particularly when the observed vehicle was positioned on the left or right side of an intersection, even when participants could focus solely on the other vehicle and no other distractions were present. Accounting for these inconsistencies when developing driving systems or testing autonomous vehicles can significantly enhance the safety and awareness of all traffic participants involved in an intersection.