Defining interactions: a conceptual framework for understanding interactive behaviour in human and automated road traffic

Rapid advances in technology for highly automated vehicles (HAVs) have raised concerns about coexistence of HAVs and human road users. Although there is a long tradition of research into human road user interactions, there is a lack of shared models and terminology to support cross-disciplinary research and development towards safe and acceptable interaction-capable HAVs. Here, we review the main themes and findings in previous theoretical and empirical interaction research, and find large variability in perspectives and terminologies. We unify these perspectives in a structured, cross-theoretical conceptual framework, describing what road traffic interactions are, how they arise, and how they get resolved. Two key contributions are: (1) a stringent definition of “interaction”, as “a situation where the behaviour of at least two road users can be interpreted as being influenced by the possibility that they are both intending to occupy the same region of space at the same time in the near future”, and (2) a taxonomy of the types of behaviours that road users exhibit in interactions. We hope that this conceptual framework will be useful in the development of improved empirical methodology, theoretical models, and technical requirements on vehicle automation

Methodologies to Understand the Road User Needs When Interacting with Automated Vehicles

Interactions among road users play an important role for road safety and fluent traffic. In order to design appropriate interaction strategies for automated vehicles, observational studies were conducted in Athens (Greece), Munich (Germany), Leeds (UK) and in Rockville, MD (USA). Naturalistic behaviour was studied, as it may expose interesting scenarios not encountered in controlled conditions. Video and LiDAR recordings were used to extract kinematic information of all road users involved in an interaction and to develop appropriate kinematic models that can be used to predict other’s behaviour or plan the behaviour of an automated vehicle. Manual on-site observations of interactions provided additional behavioural information that may not have been visible via the overhead camera or LiDAR recordings. Verbal protocols were also applied to get a more direct recording of the human thought process. Real-time verbal reports deliver a richness of information that is inaccessible by purely quantitative data but they may pose excessive cognitive workload and remain incomplete. A retrospective commentary was applied in complex traffic environment, which however carries an increased risk of omission, rationalization and reconstruction. This is why it was applied while the participants were watching videos from their eye gaze recording. The commentaries revealed signals and cues used in interactions and in drivers’ decision-making, that cannot be captured by objective methods. Multiple methods need to be combined, objective and qualitative ones, depending on the specific objectives of each future study

Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations

Automated vehicles (AV) are expected to be integrated into mixed traffic environments in the near future. As human road users have established elaborated interaction strategies to coordinate their actions among each other, one challenge that human factors experts and vehicle designers are facing today is how to design AVs in a way that they can safely and intuitively interact with other traffic participants. This paper presents design considerations that are intended to support AV designers in reducing the complexity of the design space. The design considerations are based on a literature review of common human–human interaction strategies. Four categories of information are derived for the design considerations: (1) information about vehicle driving mode; (2) information about AVs’ manoeuvres; (3) information about AVs’ perceptions of the environment; and (4) information about AVs’ cooperation capabilities. In this paper, we apply the four categories to analyse existing research studies of traffic participants’ needs during interactions with AVs and results of the CityMobil2 project. From the CityMobil2 project we present central results from face-to-face interviews, an onsite-survey and two focus groups. To further support the AV designers we describe and rate different design options to present the information of the four categories, including the design of the infrastructure, the vehicle shape, the vehicle manoeuvres and the external human–machine interface of the AV