Do you know what's going on? - Examining Situation Awareness for Different Communication Concepts of an E-Cargo Bike Autonomous Parking Function

Abstract

Offering the opportunity to comfortably carry heavy load, e-cargo bikes are an environmentally friendly alternative to motor vehicles. Especially in urban areas, where e-cargo bikes contribute to resolve challenges like noise pollution and limited space, there is an increasing number of sharing-systems that offer users the option of renting powerful e-cargo bikes without having to buy them. In this context, an automation of the e-cargo bike return process might further enhance the convenience and time-efficiency of the rental process. However, for such a highly automated function, a need for communication between the autonomously operating vehicle and the user may arise, for instance for providing feedback about the successful completion of parking. Users moreover need to develop an accurate awareness of the situation to prevent misinterpretations and to ensure a safe interaction with the autonomous function. In this regard, research on automated cars has found external Human-Machine Interfaces (eHMIs) to be a possible solution to communicate relevant information between traffic participants in situations where implicit driving cues from the vehicle’s trajectory are not sufficient. The aim of the current study was to investigate the effects of three different communication concepts for an autonomously parking cargo e-bike in a one-factorial between-design laboratory study. A total of N = 26 participants were randomly assigned to 3 experimental groups and watched videos presenting either (1) a visual communication concept (via light bands on the handlebar), (2) an auditory communication concept (via signal tones), or (3) a concept without additional signals (via movements of the e-cargo bike). The videos demonstrated typical return situations at the rental station, where the e-cargo bike should transmit information to the user via the different signals. According to an adapted version of the Situation Awareness Global Assessment Technique (SAGAT), the videos were freezed at certain points in the parking process. During each freezing, participants were interviewed regarding their Situation Awareness based on the three levels (perception, comprehension, and prediction). For each level of Situation Awareness, participants’ statements were compared with the expectation of the correct interpretation of the parking situation. Results of the qualitative analysis reflected a better understanding of the situation for the communication concepts containing explicit communication cues, particularly concerning the second (comprehension) and third (prediction) level of situation awareness. The visual and auditory communication concepts were correctly interpreted by the participants. For the first level of Situation Awareness including the perception of objects, signals and movements, results did not considerably differ between communication concepts. However, the communication concepts incorporating additional cues (visual, auditory) achieved better results in terms of comprehending the situation (level 2) and predicting future states (level 3) compared to the condition without eHMI. Overall, participants’ answers regarding the visual communication concept was mostly consistent with the expectations. In sum, results imply that eHMIs have the potential to enhance users’ Situation Awareness of the autonomous parking of e-cargo bikes, whereas cues from the vehicle’s movements alone might be not sufficient. The results of this study suggest potential design options for eHMIs for autonomous e-cargo bike parking and identify the need for further research.