Statistical Approach to Quantifying Interceptability of Interaction Scenarios for Testing Autonomous Surface Vessels

This paper presents a probabilistic approach to quantifying interceptability of an interaction scenario designed to test collision avoidance of autonomous navigation algorithms. Interceptability is one of many measures to determine the complexity or difficulty of an interaction scenario. This approach uses a combined probability model of capability and intent to create a predicted position probability map for the system under test. Then, intercept-ability is quantified by determining the overlap between the system under test probability map and the intruder’s capability model. The approach is general; however, a demonstration is provided using kinematic capability models and an odometry-based intent model

Synthesizing Maritime Interaction Scenarios for Testing Autonomy

This paper presents a method to deterministically synthesize maritime traffic interactions that can be presented to a system under test regardless of the state of the system under test. A background to the problem is given and the method is briefly outlined. Results indicate that the approach can enable more robust evaluation of maritime autonomous algorithms

LiDAR Buoy Detection for Autonomous Marine Vessel Using Pointnet Classification

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game Engine (herein referred to as Unity) simulation data was used for the training and testing of a Pointnet neural network model while the labeled real-world maritime environment point cloud data was used for the model validation. Fitting the Pointnet model on the simulation data, after some data alignment with the LiDAR images allowed for accurate classification of buoys on the real-world data with the 93% of accuracy. A traditional image processing approach using 2D occupancy maps to detect the buoys by shape was used as well and is outlined in the paper

Simulation-Based Environment for the Eye-Tracking Control of Tele-Operated Mobile Robots

Eye tracking has traditionally been used to measure the visual attention of users while performing a task or to aide disabled persons in performing hands-free interactions. The increased accuracy and reduced cost of eye-tracking equipment today makes it feasible to utilize this technology for explicit control tasks, especially in cases where there is confluence between the visual task and control. This paper describes the design of a virtual simulation environment in order to assess the feasibility of using eye-tracking to control the movement and payload of a ground robot during a visual search task. The resulting simulation-based test environment includes a kinematic model of a ground tele-operated robot within a virtual debris-filled, industrial environment with intact and damaged barrels. The operator can steer the robot while independently operating an onboard pan-tilt (PT) camera used to search for damaged containers. The environment supports three methods of control: manual, in which the operator utilizes two joysticks, one for speed/steering and one for camera control, hybrid in which the operator utilizes a joystick for speed/steering control and eye-tracking for camera control, and hands-free in which the operator utilizes gaze for both steering/speed control and camera operation

Design Of Simulator Scenarios To Study Effectiveness Of Electronic Stability Control Systems

The mission of the National Advanced Driving Simulator is to conduct highway safety research that will reduce annual loss of life on U.S. roadways. The simulator is well suited in its ability to replicate vehicle dynamics - and associated motion and visual cues - realistically to conduct complex experiments. It is unique in its ability to study vehicle control and loss-of-control situations in a safe and controlled environment. These capabilities make it an appropriate device to study the effectiveness of electronic stability control (ESC) systems, in which proper handling during loss of vehicle control is critical to assess system efficacy. The focus of the study is on challenges associated with creating repeatable yet unexpected scenario events in which loss of control is imminent for most drivers. Scenario events designed for a large-scale experiment to study ESC systems are detailed, data derived from these scenarios are discussed, and findings of scenario effectiveness are presented. A discussion of what constitutes loss of control and how to measure its effect effectively is provided

An Epidemiological Model of Rift Valley Fever with Spatial Dynamics

As a category A agent in the Center for Disease Control bioterrorism list, Rift Valley fever (RVF) is considered a major threat to the United States (USA). Should the pathogen be intentionally or unintentionally introduced to the continental USA, there is tremendous potential for economic damages due to loss of livestock, trade restrictions, and subsequent food supply chain disruptions. We have incorporated the effects of space into a mathematical model of RVF in order to study the dynamics of the pathogen spread as affected by the movement of humans, livestock, and mosquitoes. The model accounts for the horizontal transmission of Rift Valley fever virus (RVFV) between two mosquito and one livestock species, and mother-to-offspring transmission of virus in one of the mosquito species. Space effects are introduced by dividing geographic space into smaller patches and considering the patch-to-patch movement of species. For each patch, a system of ordinary differential equations models fractions of populations susceptible to, incubating, infectious with, or immune to RVFV. The main contribution of this work is a methodology for analyzing the likelihood of pathogen establishment should an introduction occur into an area devoid of RVF. Examples are provided for general and specific cases to illustrate the methodology