Visual control of steering in curve driving

A Survey of Autonomous Vehicle Behaviors: Trajectory Planning Algorithms, Sensed Collision Risks, and User Expectations

Autonomous vehicles are rapidly advancing and have the potential to revolutionize transportation in the future. This paper primarily focuses on vehicle motion trajectory planning algorithms, examining the methods for estimating collision risks based on sensed environmental information and approaches for achieving user-aligned trajectory planning results. It investigates the different categories of planning algorithms within the scope of local trajectory planning applications for autonomous driving, discussing and differentiating their properties in detail through a review of the recent studies. The risk estimation methods are classified and introduced based on their descriptions of the sensed collision risks in traffic environments and their integration with trajectory planning algorithms. Additionally, various user experience-oriented methods, which utilize human data to enhance the trajectory planning performance and generate human-like trajectories, are explored. The paper provides comparative analyses of these algorithms and methods from different perspectives, revealing the interconnections between these topics. The current challenges and future prospects of the trajectory planning tasks in autonomous vehicles are also discussed.

Perception-Motion Coupling in Active Telepresence: Human Behavior and Teleoperation Interface Design

Teleoperation enables complex robot platforms to perform tasks beyond the scope of the current state-of-the-art robot autonomy by imparting human intelligence and critical thinking to these operations. For seamless control of robot platforms, it is essential to facilitate optimal situational awareness of the workspace for the operator through active telepresence cameras. However, the control of these active telepresence cameras adds an additional degree of complexity to the task of teleoperation. In this paper we present our results from the user study that investigates: 1) how the teleoperator learns or adapts to performing the tasks via active cameras modeled after camera placements on the TRINA humanoid robot; 2) the perception-action coupling operators implement to control active telepresence cameras, and 3) the camera preferences for performing the tasks. These findings from the human motion analysis and post-study survey will help us determine desired design features for robot teleoperation interfaces and assistive autonomy.

Introduction to special issue on "Prediction in Perception and Action"

The wide diversity of articles in this issue reveals an explosion of evidence for the mechanisms of prediction in the visual system. When thought of as visual priors, predictive mechanisms can be seen as tightly interwoven with incoming sensory data. Prediction is thus a fundamental and essential aspect not only of visual perception but of the actions that are guided by perception.