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View article: Mitigation Strategy for Navigation Errors in Strict Route Plans
Mitigation Strategy for Navigation Errors in Strict Route Plans Open
View article: Umit Ozguner [People in Control]
Umit Ozguner [People in Control] Open
Q. How did your education and early career lead to your initial and continuing interest in the control field?
View article: Table of Contents
Table of Contents Open
As the official means of communication for the IEEE Control Systems Society, IEEE Control Systems publishes interesting, useful, and informative material on all aspects of control system technology for the benefit of control educators, pra…
View article: Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling
Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling Open
Recent research in pedestrian simulation often aims to develop realistic behaviors in various situations, but it is challenging for existing algorithms to generate behaviors that identify weaknesses in automated vehicles' performance in ex…
View article: A Finite-Sampling, Operational Domain Specific, and Provably Unbiased Connected and Automated Vehicle Safety Metric
A Finite-Sampling, Operational Domain Specific, and Provably Unbiased Connected and Automated Vehicle Safety Metric Open
A connected and automated vehicle safety metric determines the performance of\na subject vehicle (SV) by analyzing the data involving the interactions among\nthe SV and other dynamic road users and environmental features. When the data\nse…
View article: A Note of Thanks
A Note of Thanks Open
Dear Authors and Readers, My time as Editor-in-Chief of IEEE TRANSACTIONS ON INTELLIGENT VEHICLES has come to an end. It was an honor to help start up the T-IV and be the Editor-in-Chief for the past 6 years. I want to thank all of you for…
View article: Physics-Based Simulation and Automation of a Load-Haul-Dump Operation for an Articulated Dump Truck
Physics-Based Simulation and Automation of a Load-Haul-Dump Operation for an Articulated Dump Truck Open
Many trucks are used for a class of activities involving a sequence of basic load-haul-dump operations. The repetitiveness of this operation has been an enabler for autonomous vehicle technology in efforts to increase safety and efficiency…
View article: Dynamic and Interpretable State Representation for Deep Reinforcement Learning in Automated Driving
Dynamic and Interpretable State Representation for Deep Reinforcement Learning in Automated Driving Open
Understanding the causal relationship between an autonomous vehicle's input state and its output action is important for safety mitigation and explainable automated driving. However, reinforcement learning approaches have the drawback of b…
View article: Entropy Based Metric to Assess the Accuracy of PNT Information⋆
Entropy Based Metric to Assess the Accuracy of PNT Information⋆ Open
Entropy measures uncertainty present within the data. Highly Automated Vehicles (HAVs) can navigate safely and efficiently if location information of occluded dynamic objects is available. It is assumed that dynamic objects have GPS receiv…
View article: IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Open
The IEEE TransacTions on inTelligenT Vehicles (T-IV) publishes peer-reviewed articles that provide innovative research concepts and application results, report significant theoretical findings and application case studies, and raise awaren…
View article: A Formal Characterization of Black-Box System Safety Performance With Scenario Sampling
A Formal Characterization of Black-Box System Safety Performance With Scenario Sampling Open
A typical scenario-based evaluation framework seeks to characterize a black-box system's safety performance (e.g., failure rate) through repeatedly sampling initialization configurations (scenario sampling) and executing a certain test pol…
View article: Towards Guaranteed Safety Assurance of Automated Driving Systems With Scenario Sampling: An Invariant Set Perspective
Towards Guaranteed Safety Assurance of Automated Driving Systems With Scenario Sampling: An Invariant Set Perspective Open
How many scenarios are sufficient to validate the safe Operational Design\nDomain (ODD) of an Automated Driving System (ADS) equipped vehicle? Is a more\nsignificant number of sampled scenarios guaranteeing a more accurate safety\nassessme…
View article: Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for Urban Autonomous Driving
Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for Urban Autonomous Driving Open
Avoiding unseen or partially occluded vulnerable road users (VRUs) is a major challenge for fully autonomous driving in urban scenes. However, occlusion-aware risk assessment systems have not been widely studied. Here, we propose a pedestr…
View article: IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Open
The IEEE TransacTions on inTelligenT Vehicles (T-IV) publishes peer-reviewed articles that provide innovative research concepts and application results, report significant theoretical findings and application case studies, and raise awaren…
View article: A Vision-Based Social Distancing and Critical Density Detection System for COVID-19
A Vision-Based Social Distancing and Critical Density Detection System for COVID-19 Open
Social distancing (SD) is an effective measure to prevent the spread of the infectious Coronavirus Disease 2019 (COVID-19). However, a lack of spatial awareness may cause unintentional violations of this new measure. Against this backdrop,…
View article: Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for\n Urban Autonomous Driving
Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for\n Urban Autonomous Driving Open
Avoiding unseen or partially occluded vulnerable road users (VRUs) is a major\nchallenge for fully autonomous driving in urban scenes. However,\nocclusion-aware risk assessment systems have not been widely studied. Here, we\npropose a pede…
View article: A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety
A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety Open
The scenario-based testing of operational vehicle safety presents a set of principal other vehicle (POV) trajectories that seek to force the subject vehicle (SV) into a certain safety-critical situation. Current scenarios are mostly (i) st…
View article: IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Open
others to the state of the art development and pr vehicles.
View article: Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention
Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention Open
Predicting vulnerable road user behavior is an essential prerequisite for deploying Automated Driving Systems (ADS) in the real-world. Pedestrian crossing intention should be recognized in real-time, especially for urban driving. Recent wo…
View article: IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Open
The IEEE TRANSACTIONS ON INTELLIGENT VEHICLES (T-IV) publishes peer-reviewed articles that provide innovative research concepts and application results, report signifi cant theoretical fi ndings and application case studies, and raise awar…
View article: Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control
Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control Open
This paper introduces a sliding-mode-based extremum-seeking algorithm aimed at generating optimal set-points of wind turbines in wind farms. A distributed extremum-seeking control is directed to fully utilize the captured wind energy by ta…
View article: On the Generalizability of Motion Models for Road Users in Heterogeneous Shared Traffic Spaces
On the Generalizability of Motion Models for Road Users in Heterogeneous Shared Traffic Spaces Open
Modeling mixed-traffic motion and interactions is crucial to assess safety, efficiency, and feasibility of future urban areas. The lack of traffic regulations, diverse transport modes, and the dynamic nature of mixed-traffic zones like sha…
View article: Sub-Goal Social Force Model for Collective Pedestrian Motion Under Vehicle Influence
Sub-Goal Social Force Model for Collective Pedestrian Motion Under Vehicle Influence Open
In mixed traffic scenarios, a certain number of pedestrians might coexist in a small area while interacting with vehicles. In this situation, every pedestrian must simultaneously react to the surrounding pedestrians and vehicles. Analytica…
View article: IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Open
The IEEE TRANSACTIONS ON INTELLIGENT VEHICLES (T-IV) publishes peer-reviewed articles that provide innovative research concepts and application results, report signifi cant theoretical fi ndings and application case studies, and raise awar…
View article: Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using Fusion
Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using Fusion Open
Learned pointcloud representations do not generalize well with an increase in distance to the sensor. For example, at a range greater than 60 meters, the sparsity of lidar pointclouds reaches to a point where even humans cannot discern obj…
View article: Optical Flow based Visual Potential Field for Autonomous Driving
Optical Flow based Visual Potential Field for Autonomous Driving Open
Monocular vision-based navigation for automated driving is a challenging task due to the lack of enough information to compute temporal relationships among objects on the road. Optical flow is an option to obtain temporal information from …
View article: Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving
Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving Open
Automated driving in urban settings is challenging. Human participant behavior is difficult to model, and conventional, rule-based Automated Driving Systems (ADSs) tend to fail when they face unmodeled dynamics. On the other hand, the more…
View article: A Modeled Approach for Online Adversarial Test of Operational Vehicle\n Safety (extended version)
A Modeled Approach for Online Adversarial Test of Operational Vehicle\n Safety (extended version) Open
The scenario-based testing of operational vehicle safety presents a set of\nprincipal other vehicle (POV) trajectories that seek to force the subject\nvehicle (SV) into a certain safety-critical situation. Current scenarios are\nmostly (i)…
View article: A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety (extended version)
A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety (extended version) Open
The scenario-based testing of operational vehicle safety presents a set of principal other vehicle (POV) trajectories that seek to force the subject vehicle (SV) into a certain safety-critical situation. Current scenarios are mostly (i) st…
View article: A Vision-based Social Distancing and Critical Density Detection System for COVID-19
A Vision-based Social Distancing and Critical Density Detection System for COVID-19 Open
Social distancing has been proven as an effective measure against the spread of the infectious COronaVIrus Disease 2019 (COVID-19). However, individuals are not used to tracking the required 6-feet (2-meters) distance between themselves an…