External Human-Machine Interfaces for Autonomous Vehicles from Pedestrians' Perspective: A Survey Study.

With the increasing number of automated vehicles (AVs) being tested and operating on roads, external Human-Machine Interfaces (eHMIs) are proposed to facilitate interactions between AVs and other road users. Considering the need to protect vulnerable road users, this paper addresses the issue by providing research evidence on various designs of eHMIs. Ninety participants took part in this experiment. Six sets of eHMI prototypes-Text, Arrowed (Dynamic), Text and Symbol, Symbol only, Tick and Cross and Traffic Lights, including two sub-designs (Cross and Do Not Cross)-were designed. The results showed that 65.1% of participants agreed that external communication would have a positive effect on pedestrians' crossing decisions. Among all the prototypes, Text, and Text and Symbol, eHMIs were the most widely accepted. In particular, for elderly people and those unfamiliar with traffic rules, Text, and Text and Symbol, eHMIs would lead to faster comprehension. The results confirmed that 68.5% of participants would feel safer crossing if the eHMI had the following features: 'Green', 'Text', 'Symbol', or 'Dynamic'. These features are suggested in the design of future systems. This research concluded that eHMIs have a positive effect on V2X communication and that textual eHMIs were clear to pedestrians.

Modeling pedestrian violation behavior at signalized crosswalks in China: a hazards-based duration approach.

OBJECTIVE: Pedestrian violation is a major cause of traffic accidents involving pedestrians. The research objectives were to investigate the relationship between waiting duration and pedestrian violation and to provide a qualitative and quantitative analysis of the effects of human factors and external environmental factors on street-crossing behavior. METHODS: Pedestrians' street-crossing behavior was examined by modeling the waiting duration at signalized crosswalk. Pedestrian waiting duration was collected by video cameras and it was assigned as censored and uncensored data to distinguish between normal crossing and violating crossing. A nonparametric baseline duration model was introduced, and variables revealing personal characteristics, traffic conditions, and trip features were defined as covariates to describe the effects of internal and external factors. RESULTS: Pedestrians' crossing behaviors represented positive duration dependence that the longer the waiting time elapsed the more likely pedestrians would end the wait soon. The violation inclination of most pedestrians increased with the increasing waiting duration, but about 10 percent of pedestrians were at high risk of violation to cross the street. About half of pedestrians would still obey the traffic rules even after waiting for 50 s by the street. Human factors and the external environment played an important role in street-crossing behavior, especially for factors that involved pedestrians' subjective willingness. CONCLUSIONS: The street-crossing behavior of pedestrians was time dependent. Pedestrians behave differently under the effects of various factors. Pedestrian safety interventions that aim at reducing pedestrian injuries may need to consider these effects. The pedestrians' behavioral modifications, such as enhancing the safety awareness, might be the most efficient means to reducing the likelihood of pedestrian violation, though environmental modifications also worked well in improving pedestrian safety.