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Autonomous Vehicles that Interact with Pedestrians: A Survey of Theory and Practice
Amir Rasouli,John K. Tsotsos +1 more
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TLDR
This paper surveys pedestrian behavior studies, both the classical works on pedestrian–driver interaction and the modern ones that involve autonomous vehicles, to discuss various methods of studying pedestrian behavior and analyze how the factors identified in the literature are interrelated.Abstract:
One of the major challenges that autonomous cars are facing today is driving in urban environments. To make it a reality, autonomous vehicles require the ability to communicate with other road users and understand their intentions. Such interactions are essential between the vehicles and pedestrians as the most vulnerable road users. Understanding pedestrian behavior, however, is not intuitive and depends on various factors such as demographics of the pedestrians, traffic dynamics, environmental conditions, etc. In this paper, we identify these factors by surveying pedestrian behavior studies, both the classical works on pedestrian-driver interaction and the modern ones that involve autonomous vehicles. To this end, we will discuss various methods of studying pedestrian behavior, and analyze how the factors identified in the literature are interrelated. We will also review the practical applications aimed at solving the interaction problem including design approaches for autonomous vehicles that communicate with pedestrians and visual perception and reasoning algorithms tailored to understanding pedestrian intention. Based on our findings, we will discuss the open problems and propose future research directions.read more
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Human motion trajectory prediction: a survey:
Andrey Rudenko,Andrey Rudenko,Luigi Palmieri,Michael Herman,Kris M. Kitani,Dariu M. Gavrila,Kai O. Arras +6 more
TL;DR: In this article, the ability of intelligent autonomous systems to perceive, understand, and anticipate human behavior becomes increasingly important in a growing number of intelligent systems in human environments, and the ability to do so is discussed.
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Human Trajectory Forecasting in Crowds: A Deep Learning Perspective
TL;DR: This work presents an in-depth analysis of existing deep learning based methods for modelling social interactions, and proposes a simple yet powerful method for effectively capturing these social interactions.
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Taming the eHMI jungle: A classification taxonomy to guide, compare, and assess the design principles of automated vehicles' external human-machine interfaces
Debargha Dey,Azra Habibovic,Andreas Löcken,Philipp Wintersberger,Bastian Pfleging,Andreas Riener,Marieke Martens,Jacques Terken +7 more
TL;DR: A unified taxonomy is presented that allows a systematic comparison of the eHMI across 18 dimensions, covering their physical characteristics and communication aspects from the perspective of human factors and human-machine interaction.
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The cultural barriers to a low-carbon future: A review of six mobility and energy transitions across 28 countries
TL;DR: In this article, a review focuses on how culture can complicate and impede attempts at promoting more efficient, more sustainable, and often more affordable forms of mobility as well as energy use in homes and buildings.
Proceedings ArticleDOI
The Case for Implicit External Human-Machine Interfaces for Autonomous Vehicles
TL;DR: Results from a field study with a Wizard-of-Oz driverless vehicle that tested pedestrians' reactions in everyday traffic suggest that pedestrians may not need explicit eHMI in routine interactions---the car's implicit eH MI (its motion) may suffice.
References
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You'll never walk alone: Modeling social behavior for multi-target tracking
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Proceedings ArticleDOI
Pedestrian detection: A benchmark
TL;DR: The Caltech Pedestrian Dataset is introduced, which is two orders of magnitude larger than existing datasets and proposes improved evaluation metrics, demonstrating that commonly used per-window measures are flawed and can fail to predict performance on full images.
Journal ArticleDOI
Visual attention while driving: sequences of eye fixations made by experienced and novice drivers
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Journal ArticleDOI
Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age
TL;DR: In this article, the authors surveyed almost 1000 participants on their perceptions, particularly with regards to safety and acceptance of autonomous vehicles, and found that autonomous cars were perceived as a "somewhat low risk" form of transport and, while concerns existed, there was little opposition to the prospect of their use on public roads.
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