Background Automated shuttles are tested in many places worldwide. They are typically electrical minibuses operating at SAE level 3 (i.e. with an operator on-board). Low speed, stereotypical driving and compliance with traffic rules characterize their driving. Their software models are able to solve pre-defined traffic situations. However, in situations they have not been trained for, the shuttles might react in unexpected ways. Both predictable and non-predictable reactions of shuttles have impact on human behavior towards them and may affect traffic safety. As safety is a major concern for society and for implementation of automated vehicles, it is essential to understand the safety consequences of human-shuttle interactions. Method This study utilizes video clips of human-shuttle interactions in regular, mixed traffic. Videos were captured in the Oslo region within several TØI projects, at locations such as a shared space, residential areas or signalized intersections. The analyses were conducted in several steps. First, video clips were categorized by a road safety researcher (based on variables such as location and type of involved traffic participants and their maneuvers). Second, a team of experts with diverse backgrounds (such as traffic psychology, game theory, traffic conflict studies, accident analyses, behavioral observations) evaluated the interactions and discussed human behavior towards the shuttles. Utilizing various perspectives of the team members enabled us to better identify the contributory factors to humans’ responses to automated shuttles and to evaluate potential safety issues. Results This study is currently on-going. We identified two major categories of human responses. The first category is characterized by misusing the shuttles’ operational characteristics, e.g., drivers and cyclists overtaking slow shuttles in a risky matter or not giving way to the shuttles. The second category is connected to misinterpreting/not trusting shuttles’ reactions which can result for example in drivers wrongly giving way to the shuttles. Conclusions The preliminary results suggest that an introduction of automated shuttles into urban traffic leads to several types of behavioral adaptations, which can affect the traffic safety. Misusing of shuttles’ operational characteristics and misinterpreting of shuttles’ reactions contribute to the occurrence of these adaptations.

Automated shuttles are already seeing deployment in many places across the world and have the potential to transform public mobility to be safer and more accessible. During the current transition phase from fully manual vehicles toward higher degrees of automation and resulting mixed traffic, there is a heightened need for additional communication or external indicators to comprehend automated vehicle actions for other road users. In this work, we present and discuss the results from seven studies (three preparatory and four main studies) conducted in three European countries aimed at investigating and providing a variety of such external communication solutions to facilitate the exchange of information between automated shuttles and other motorized and non-motorized road users.

Introduction: Increasing numbers of deployment projects of automated shuttles have been taking place worldwide. Safety is one of the main concerns for their successful implementation. Therefore, it is vital to gain the knowledge about interactions between these shuttles and other traffic participants. Method: Given the lack of behavioural observational studies under regular traffic conditions, the presented study applies external video recordings to explore encounters between the shuttles approaching a T-intersection and other traffic participants. The encounters of interest included a vulnerable road user in the bicycle lane, a pedestrian on the zebra crossing and a road user overtaking the shuttle. The shuttles were identified from the video by RUBA software. We analysed the encounters using T-Analyst software together with the manual observation of traffic participants' behaviour. Results: From 220 h of video, 318 unique manoeuvres of the shuttle were observed and 83 encounters with other traffic participants were identified and explored. Several types of risks and behavioural patterns were identified, such as road users misusing the defensive style of the shuttles or cyclists in the bicycle lane not being sure about the shuttle’s intention. Frequent hard stops of the shuttles might be dangerous for the passengers inside and can increase the risk of rear end accidents. Conclusions: The findings provide a valuable insight into the interactions between automated shuttles and other traffic participants under regular traffic conditions on one location in Oslo, Norway. The study showed that introducing automated shuttles into regular traffic can lead to the emergence of new types of interactions between the shuttles and other traffic participants.