Technology for improved drivers’ safety: Testing a multimodal HMI

Abstract

Using driving automation technology to shift from reactive to anticipatory HMI could enable drivers to improve safety. To this end, a system helping drivers to anticipate risks was developed. In a previous study, cross-analysis between accident databases, driving instructor expertise and on-road observation led to prioritize seven types of risk. A system based on sensors and prediction algorithms was then developed to recognize and objectify risk levels. The present study was the first user-test of the system. Twelve participants were asked to drive as usual and evaluate timing, relevance, utility, and usefulness of warnings to improve risk awareness. They were also required to report risks that they considered missed by the system. Participants drove in an area involving risks related to infrastructure and traffic configurations: (1) a pedestrian crossing frequently hidden by buses stopped at the station (BUS), (2) an unexpected sharp curve, possibly hiding an obstacle (CURVE), and (3) a pedestrian crossing with reduced visibility on sidewalks and high pedestrian traffic (CROSSING). Informative icons were displayed when approaching respectively CURVE and CROSSING to indicate the type of risk (i.e., permanent risks linked to the infrastructure). They were associated with a soft tone to ensure they were perceived and, thus, evaluated by drivers. A LED bar, activated at the bottom of the windshield, indicated the location of potential hazard in CURVE and BUS (i.e., transitory risks linked to traffic). Due to the high probability of meeting pedestrians in BUS, the LED bar was associated with an urgent sound. The results showed that both LED bar and sound were highly relevant in BUS situation, as drivers recognized that overtaking the bus was a frequent and very dangerous practice. In CURVE, drivers considered that an informative icon and sound were useful or, at least, not annoying since they experienced the severity of the turn. However, the LED bar appeared not very relevant because drivers were already warned by the informative icon and thought that encountering an obstacle on their lane was not certain. They rather considered that the main risks were lane departure or oncoming traffic. In CROSSING, the informative icon was not understood because the presence of a pedestrian crossing seemed obvious, or because the driver was already coping with potential pedestrians. Finally, drivers expected that the system would report pedestrians walking on the road, or close to cross, because they could represent an obvious risk of collision in case of distraction. We conclude that the LED bar is only effective for guiding attention on risk related to the traffic. Informative icon related to infrastructure seems understandable only when risk is experienced by drivers. Reporting collision risk with pedestrian, when possible, is a desired function for improving safety. The study supports changes in multimodal HMI strategy to improve system efficiency, especially to carefully design HMI signals to be associated to perceived risks or, afterwards, to missed risks.

Keywords: Risk, Perceived Safety, Contextual Hmi, Multimodal Hmi, On-Road System Evaluation

DOI: 10.54941/ahfe1005360