Cooperative Automation Research Articles

Enabling Analysis, Modeling, and Simulation for Cooperative Automated Vehicle Applications in Transportation Systems: The Pillar Diagram

Enabling Analysis, Modeling, and Simulation for Cooperative Automated Vehicle Applications in Transportation Systems: The Pillar Diagram

Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model

Connected and Autonomous Vehicles (CAVs) technology has the potential to transform the transportation system. Although these new technologies have many advantages, the implementation raises significant concerns regarding safety, security, and privacy. Anomalies in sensor data caused by errors or cyberattacks can cause severe accidents. To address the issue, this study proposed an innovative anomaly detection algorithm, namely the LSTM Autoencoder with Gaussian Mixture Model (LAGMM). This model supports anomalous CAV trajectory detection in the real-time leveraging communication capabilities of CAV sensors. The LSTM Autoencoder is applied to generate low-rank representations and reconstruct errors for each input data point, while the Gaussian Mixture Model (GMM) is employed for its strength in density estimation. The proposed model was jointly optimized for the LSTM Autoencoder and GMM simultaneously. The study utilizes realistic CAV data from a platooning experiment conducted for Cooperative Automated Research Mobility Applications (CARMAs). The experiment findings indicate that the proposed LAGMM approach enhances detection accuracy by 3% and precision by 6.4% compared to the existing state-of-the-art methods, suggesting a significant improvement in the field.

A Pathway Forward: The Evolution of Intelligent Vehicles Research on IEEE T-IV

This paper presents a bibliographic and collaboration pattern analysis of the IEEE T <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ransactions on</small> I <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ntelligent</small> V <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ehicles (T-IV)</small> . In this paper, a journal analysis framework is proposed. The most productive/influential authors, institutions, and countries/regions are identified. The research group structure is generated. Hot research topics and trends are discussed. Analysis results find that: i) The U.S. is now dominating the IV research field. It contributes 32% of papers in the IEEE T-IV; ii) Vehicle planning, vehicle perception, and energy management are the top-three hottest research topics from 2016 to 2021; iii) The Cooperative Automation (CA) is a research trend that includes vehicle group control, platoon control, intersection management, cooperation security, and cooperative perception; iv) The new “3224” processing policy is demonstrated to reduce processing durations by 90% and attracts nine times more manuscripts.

Eco-Platooning for Cooperative Automated Vehicles Under Mixed Traffic Flow

The mixed traffic flow, which comprises both cooperative automated vehicles (CAVs) and human-driven vehicles, is becoming more common in modern urban areas. CAVs can expand the capabilities such as that can be achieved with automation and vehicular communication individually. However, the energy-saving benefits may be one of the exceptions when three or more vehicles drive in a row under the mixed traffic scenarios. The undesired driving behaviors of human-driven vehicles can introduce a high level of randomness to traffic flow, which results in energy-inefficient driving profiles for CAVs with aggressive operations or even vehicle crashing. In this paper, we investigate an eco-platooning problem for CAVs under the mixed traffic flow. This is a challenging problem due to both of the platoon-wide energy-saving and driving security requirements. To address this problem, an ecological and string stable platooning scheme, called E-CACC, is provided. First, novel spacing policies are presented to enforce that all platoon members track energy-efficient driving profiles. Then, control laws are designed to ensure the tracking performances of the proposed spacing policies. Furthermore, the theoretical proof is provided to prove the platoon string stability of the proposed strategy. Finally, performance evaluation is conducted. Results have illustrated the energy efficiency of the proposed E-CACC scheme.

First Observations about Response Times and Connectivity in a Vehicles Platooning Experiment

A key question about cooperative vehicle longitudinal control is reactivity, which determines the future of road safety, and capacity. In adaptive cruise control (ACC), the controller adapts the speed of the vehicle to its immediate leader’s speed whereas, in the cooperative version (CACC), connectivity between the platoon equipped vehicles reduces their response times. The USDoT Cooperative Automated Research Mobility Applications (CARMA) platform provides data for platooning experiments involving ACC and CACC vehicles. We measure ACC response times (mean = 2.78 seconds) larger than for human-driven cars. We study response times inside CACC platoons showing that connectivity is not always effective.

Opportunities and Challenges in Cooperative Road Vehicle Automation

This paper provides an introduction to the opportunities for improving the performance of road transportation automation systems by use of vehicle-vehicle and vehicle-infrastructure communication and cooperation. Four different types of cooperative driving automation are defined and examples of the functionality enabled by each are described. Although the benefits of cooperative automation are significant, there are also significant challenges to its widespread deployment, which are also described. The risks of over-reliance on communication for cooperative automation implementations are also discussed to provide a balanced view of appropriate levels of cooperation.

Creating Effective Automation to Maintain Explicit User Engagement

ABSTRACTLoss of user engagement with automation in increasingly complex environments, such as driving a car, can have increasingly unexpected and consequential impacts. This paper presents a three-step process for designing cooperative automation into existing systems to maximize system performance with the constraint of maintaining user engagement. The first step identifies beneficial areas for automation through user testing, focusing on areas where human capabilities constrain performance. Next, an automation is created to perform a portion of the task leading to the constraint. User tests at this point compare different automation types to choose an automation that improves on human-only performance. Lastly, the automation trigger is adjusted to allow the human to maintain engagement with the system at a level desired to avoid the risks associated with loss of user engagement. This process is demonstrated through three human-in-the-loop experiments which illustrate the trade-space between maintaining human engagement and improving system performance.

A theoretical framework for designing human-centered automotive automation systems

Increasingly sophisticated and robust automotive automation systems are being developed to be applied in all aspects of driving. Benefits, such as improving safety, task performance, and workload have been reported. However, several critical accidents involving automation assistance have also been reported. Although automation systems may work appropriately, human factors such as drivers errors, overtrust in and overreliance on automation due to lack of understanding of automation functionalities and limitations as well as distrust caused by automation surprises may trigger inappropriate human–automation interactions that lead to negative consequences. Several important methodologies and efforts for improving human–automation interactions follow the concept of human-centered automation, which claims that the human must have the final authority over the system, have been called. Given that the human-centered automation has been proposed as a more cooperative automation approach to reduce the likelihood of human–machine misunderstanding. This study argues that, especially in critical situations, the way control is handed over between agents can improve human–automation interactions even when the system has the final decision-making authority. As ways of improving human–automation interactions, the study proposes adaptive sharing of control that allows dynamic control distribution between human and system within the same level of automation while the human retains the final authority, and adaptive trading of control in which the control and authority shift between human and system dynamically while changing levels of automation. Authority and control transitions strategies are discussed, compared and clarified in terms of levels and types of automation. Finally, design aspects for determining how and when the control and authority can be shifted between human and automation are proposed with recommendations for future designs.

Principles of Automation for Patient Safety in Intensive Care: Learning From Aviation

The transition away from written documentation and analog methods has opened up the possibility of leveraging data science and analytic techniques to improve health care. In the implementation of data science techniques and methodologies, high-acuity patients in the ICU can particularly benefit. The Principles of Automation for Patient Safety in Intensive Care (PASPIC) framework draws on Billings's principles of human-centered aviation (HCA) automation and helps in identifying the advantages, pitfalls, and unintended consequences of automation in health care. Billings's HCA principles are based on the premise that human operators must remain "in command," so that they are continuously informed and actively involved in all aspects of system operations. In addition, automated systems need to be predictable, simple to train, to learn, and to operate, and must be able to monitor the human operators, and every intelligent system element must know the intent of other intelligent system elements. In applying Billings's HCA principles to the ICU setting, PAPSIC has three key characteristics: (1) integration and better interoperability, (2) multidimensional analysis, and (3) enhanced situation awareness. PAPSIC suggests that health care professionals reduce overreliance on automation and implement "cooperative automation" and that vendors reduce mode errors and embrace interoperability. Much can be learned from the aviation industry in automating the ICU. Because it combines "smart" technology with the necessary controls to withstand unintended consequences, PAPSIC could help ensure more informed decision making in the ICU and better patient care.

Modelling the Level of Trust in a Cooperative Automated Vehicle Control System

Vehicle-to-vehicle communication is a key technology for achieving increased perception for automated vehicles, where the communication enables virtual sensing by means of sensors in other vehicles. In addition, this technology also allows detection and recognition of objects that are out-of-sight. This paper presents a trust system that allows a cooperative and automated vehicle to make more reliable and safe decisions. The system evaluates the current situation and generates a trust index indicating the level of trust in the environment, the ego vehicle, and the surrounding vehicles. This research goes beyond secure communication and concerns the verification of the received data on a system level. The results show that the proposed method is capable of correctly identifying various traffic situations and how the trust index is used while manoeuvring in a platoon merge scenario.

The Experience of DRIVERTIVE-DRIVERless cooperaTIve VEhicle-Team in the 2016 GCDC

The second edition of the grand cooperative driving challenge (GCDC2016) was held in The Netherlands in May 2016. Ten international teams participated in the two competition scenarios designed for GCDC2016: platoon merging and intersection. This paper describes the design and development of DRIVERTIVE, a DRIVERless cooperaTIve VEhicle, which aims to advance cooperative automation. The purpose of this paper is to give a general overview of the different designs used to adapt a factory vehicle, with no access to low-level control systems, into a fully-automated cooperative vehicle fit to compete in GCDC2016. The approach taken was pragmatic: different pre-existing techniques for control, state estimation, data fusion, communication, and data degradation were combined and experimentally validated in real-world scenarios, together with other vehicles with different implementations. Our main conclusion is that cooperative autonomous driving is feasible among very different implementations of the communication protocols and using completely different autonomous vehicles.

Development of Platform-Independent System for Cooperative Automated Driving Evaluated in GCDC 2016

Cooperative automated driving is a promising development in reducing energy consumption and emissions, increasing road safety, and improving traffic flow. The Grand Cooperative Driving Challenge (GCDC) 2016 was an implementation oriented project with the aim to accelerate research and development in the field. This paper describes the development of the two vehicle systems with which KTH participated in GCDC 2016. It presents a reference system architecture for collaborative automated driving as well as its instantiation on two conceptually different vehicles: a Scania truck and the research concept vehicle, built at KTH. We describe the common system architecture, as well as the implementation of a selection of shared and individual system functionalities, such as V2X communication, localization, state estimation, and longitudinal and lateral control. We also present a novel approach to trajectory tracking control for a four-wheel steering vehicle using model predictive control and a novel method for achieving fair data age distribution in vehicular communications.

Utilizing Model-Based Communication and Control for Cooperative Automated Vehicle Applications

Connected vehicle applications rely on wireless communication for achieving real-time situational awareness and enabling automated actions or driver warnings. Given the constraints of the communication systems, it is critical to employ communication strategies and approaches that allow robust situational awareness. In this work, we utilize the recently introduced concept of model-based communication and design a new strategy based on small- and large-scale modeling of vehicle movement dynamics. Our approach is to describe the small-scale structure of the remote vehicle movement (e.g., braking, accelerating) by a set of dynamic models (ARX models) and represent the large-scale structure (e.g., free following, turning) by coupling these ARX models together into a Markov chain. The effect of this design is investigated for the case of cooperative adaptive cruise control application. Assuming model-based communication approach is used with the coupled model, a novel stochastic model predictive method is proposed to achieve cruise control goals. We use actual highway driving maneuvers to compare the proposed methodology with the conventional design of cooperative adaptive cruise control.

Physiological closed-loop control of mechanical ventilation and extracorporeal membrane oxygenation.

A new concept is presented for cooperative automation of mechanical ventilation and extracorporeal membrane oxygenation (ECMO) therapy for treatment of acute respiratory distress syndrome (ARDS). While mechanical ventilation is continuously optimized to promote lung protection, extracorporeal gas transfer rates are simultaneously adjusted to control oxygen supply and carbon dioxide removal using a robust patient-in-the-loop control system. In addition, the cooperative therapy management uses higher-level algorithms to adjust both therapeutic approaches. The controller synthesis is derived based on the introduced objectives, the experimental setup and the uncertain models. Finally, the autonomous ARDS therapy system capabilities are demonstrated and discussed based on in vivo data from animal experiments.

A hierarchical framework to analyze shared control conflicts between human and machine

Abstract: Shared Control, where the machine and the human share tasks and control the situation together, and its extension cooperative automation are promising approaches to overcome automation-induced problems, such as lack of situation awareness and degradation of skill. However, the design of Shared Controllers and/or cooperative human-machine systems should be done in a very careful manner. One of the major issues is conflicts between the human and the machine: how to detect these conflicts, and how to resolve them, if necessary? A complicating factor is that when the human is right, conflicts are undesirable (resulting in nuisance, degraded performance, etc), but when the machine is right, conflicts are desirable (warning the operator, or proper assistance or overruling). Research has pointed out several types and causes of conflicts, but offers no coherent framework for design and evaluation guidelines. In this paper, we propose such a theoretical framework in order to structure and relate different types of conflicts. The framework is inspired by a hierarchical task analysis, and identifies five possible sources of conflicts: intent, information gathering, information processing, decision-making and action implementation. Examples of conflicts in several application domains such as automobile, telerobotics, and surgery are discussed to illustrate the applicability of this framework.

Beyond Reliance and Compliance

Increasingly autonomous machines may lead to issues in human-automation systems that go beyond the typical concerns of reliance and compliance. This study used an interaction-oriented approach that considers interdependence in coordinating and cooperating on a joint task. A shared-resource microworld environment was developed to assess how changes in environmental demands and agent behavior affect cooperation and system performance. Seventy-two participants were recruited to perform a scheduling task that required coordination with a cooperative and a relatively uncooperative automated agent. Cooperative automation enhanced performance because it provided more resources to the person and because the person provided more resources to the automation. Considering interdependence theory and the associated structure, signal, strategy, and sequence of human-automation interaction can guide design for appropriate trust and cooperation.

A Cooperative Automation Concept for User-oriented Support of Air Target Identification

For over 40 years science in a variety of domains has conducted an impressive amount of research in the field of assistance and automation concepts, which apply human factors and needs in the design stage of cooperative and cognitive technical systems. Cooperative automation is an approach that tries to keep the user in the control loop by means of a continuous interaction during task execution. Cooperative automation aims to support the harmonization of the actor's activities (user and automation) in a human-machine-system. To enable this, both the internal (processing and computation) and external (communications and interfaces) design of the automation has to be compatible with human competence. This contribution addresses the key features of cooperative automation. These features have been used for creating a design space, which can be used as method repository in order to develop assistance systems based on the cognitive capabilities of the human. The key elements are represented as dimensions of the design space. Corresponding theories and methods are discussed. The design process for a cognitive and cooperative assistance system based on the dimensions of the design space are described. The developed Cognitive and Cooperative Assistance System (COGAS), has been implemented in the domain of air target identification on German naval ships. An evaluation of COGAS has been conducted with naval operators in order to verify its operability and to optimize and extend the COGAS functionality. The results show that COGAS improves the operator's performance in terms of increasing the amount of correct decisions and accelerating the identification process without increasing the operator's stress level. In addition it was found that COGAS helps to enhance the situational awareness due to the workload optimization.

Idaho: Library automation and connectivity

The development of cooperative library automation and connectivity in Idaho has been influenced by its geographical size, demographics, and technological development. Idaho has some 83,557 square miles with a population of about 1.2 million. The distances between population centers have been a detrimental factor to the development of automated library cooperation within the library community. A final demographic consideration is that from a commerce standpoint there are three Idahos. Northern Idaho looks toward Spokane, Washington, as the center of its service area. Eastern Idaho's trade center is Salt Lake City, Utah. Mountains and deserts divide these areas from the third major trade area, southwestern Idaho, which is centered in Boise.

Automated Periodical Systems at Dundee University Library

A description is given of the development and present state of the in-house periodicals housekeeping file and binding systems. An automated public catalogue of periodicals was first made possible by the Library's participation in the Scottish Libraries Co-operative Automation Project. Later the catalogue was transferred to the Geac system.

CAG STEERING GROUP: ACHIEVEMENTS TO DATE

The Cooperative Automation Group has recently been involved in discussions coordinated by the OAL to consider the UK's involvement in the European Commission's programme to promote library cooperation through the application of new information technologies. In the course of these discussions it was felt helpful to prepare a document outlining those areas of CAG's work which were germane to the Commission's programme and a slightly amended version of this paper is reproduced here so as to present to a wider audience the continuing activities of CAG.