Pedestrian Models for Autonomous Driving Part I: Low-Level Models, from Sensing to Tracking

Abstract—Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, inter- active motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part I of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychology models, from the perspective of an AV designer. This self-contained Part I covers the lower levels of this stack, from sensing, through detection and recognition, up to tracking of pedestrians. Technologies at these levels are found to be mature and available as foundations for use in high-level systems, such as behaviour modelling, prediction and interaction control

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

Abstract—Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, inter- active motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part II of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychological models, from the perspective of an AV designer. This self-contained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians’ likely destinations and paths, to game-theoretic models of interactions between pedestrians and autonomous vehicles. This survey clearly shows that, although there are good models for optimal walking behaviour, high-level psychological and social modelling of pedestrian behaviour still remains an open research question that requires many conceptual issues to be clarified. Early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control

D1.1 Definition of interACT use cases and scenarios

interACT studies current human‐machine interactions in mixed traffic and will increase the chances of safe deployment of AVs by developing novel software and HMI hardware components for reliable and user‐centric communication among an AV, its on‐board user and other road users. It is expected that by reaching its goals, this project will facilitate the gradual integration of AVs in future transport networks. The present document is the D1.1 “Definition of interACT scenarios” which is prepared as the first document within WP1 of the interACT project. The document presents the selection process for scenarios, a framework for the use case description and the selected interACT use cases and example scenarios. Use cases are a functional description of the behaviour of the AV in a traffic situation (see 3.3). Scenarios are a description of sequences of actions and events performed by different actors over a certain amount of time (see 3.2). As the natural traffic environment consists of a manifold variety of traffic scenes, it is essential for the interACT technical project work to reduce the complexity of the traffic environment to a manageable number of relevant use cases and scenarios that an AV could be confronted with. Therefore, WP1 started with an agreement on and definition of relevant interACT use cases and scenarios among all industrial and academic consortium members. The interACT use cases and scenarios have been selected using a step‐wise process of intensive discussions within the consortium. Starting with some open brain‐storming discussions the use cases were aggregated and rated by the partners against several criteria (such as relevance for safety, need for interaction behavior etc.) to agree on the most relevant ones. The present document illustrates the selection process of the addressed use cases, including the results of a workshop and the consortium ratings. Moreover, a method for describing and documenting of use cases is presented in the deliverable. This method is meant to structure the discussion within the consortium but is also a very promising tool for fostering the exchange of knowledge with stakeholders of the interACT consortium, such as academic and industrial partners (Chapter 5). In the main part of the document the selected use cases and example scenarios are described. The consortium defined four “must‐have” use cases that are of highest relevance. These use cases are to be covered by research and technical developments in all technical WPs and evaluated and demonstrated in the interACT demonstrator vehicles and simulators at the end of the project. These are the following “must‐have” use cases: interACT D1.1 Definition of interACT scenarios Version 1.0 Date 31/08/17 Page | 8 React to crossing non‐motorised traffic participants (TP) at crossings without traffic light React to an ambiguous situation at an unsignalised intersection React to non‐motorised TP at a parking space React to vehicles at a parking space In addition, two “optional” use cases were selected: React to vehicles in turning situations React to crossing non‐motorised TP at signalised crossings The “optional” use cases aim to inspire further research within the project and the exchange of knowledge with international research partners to foster for example cross‐cultural comparisons. This deliverable sets the basis for all further work in WP1 and all other technical WPs of the interACT project