Autonomous Transport Vehicles Research Articles

Safety and security co-analysis in transport systems: Current state and regulatory development

• The framework is proposed using security-driven and safety-oriented methods. • SSCA is constructed through both top-down and bottom-up perspectives. • The regulatory development of SSCA is analysed among different transport modes. • It strikes new research directions for digitalised and autonomous transport vehicles. Transportation is sensitive to risk. Given the fast development of digitalisation and automation of transport systems in the past decade, new types of security risks (e.g. cyberattacks) emerge within the context of transport safety research. To enable the integrated analysis of emerging security and classical safety-related risks in a holistic manner, safety and security co-analysis (SSCA) is highly demanded for accident prevention. SSCA in transport systems will benefit the risk analysis of complex cyber physical transport systems facing challenges from both hazards and threats. However, the nature of hazard and threat-based risks is fundamentally different, which leads to the various difficulties of analysing them on the same plane. They include the use of different risk parameters, the uncertainty levels of the risk input and the methodologies of risk inference. To address such concerns, this study firstly reviews the literature on SSCA and compares the employed methodologies and their applications within the context of transport systems. Taking into account the advantages of both security-driven and safety-oriented methods, a conceptual framework is proposed to imply the insights on SSCA for transportation through both top-down and bottom-up perspectives, followed by a quantitative illustrative case study. Then, the regulatory development and evolution of SSCA in transport in practice is analysed across different transport modes, which configures initiatives’ interrelations for a cross-fertilisation purpose. As a result, the findings reveal new research directions for the safety of digitalised and/or autonomous transport vehicles and aid in the formation of future transport safety study agendas.

Visual object detection for autonomous transport vehicles in smart factories

Autonomous transport vehicles (ATVs) are one of the most substantial components of smart factories of Industry 4.0. They are primarily considered to transfer the goods or perform some certain navigation tasks in the factory with self driving. The recent developments on computer vision studies allow the vehicles to visually perceive the environment and the objects in the environment. There are numerous applications especially for smart traffic networks in outdoor environments but there is lack of application and databases for autonomous transport vehicles in indoor industrial environments. There exist some essential safety and direction signs in smart factories and these signs have an important place in safety issues. Therefore, the detection of these signs by ATVs is crucial. In this study, a visual dataset which includes important indoor safety signs to simulate a factory environment is created. The dataset has been used to train different fast-responding popular deep learning object detection methods: faster R-CNN, YOLOv3, YOLOv4, SSD, and RetinaNet. These methods can be executed in real time to enhance the visual understanding of the ATV, which, in turn, helps the agent to navigate in a safe and reliable state in smart factories. The trained network models were compared in terms of accuracy on our created dataset, and YOLOv4 achieved the best performance among all the tested methods.

Model of a neural network adaptive system for a digital control loop of an electric drive

The problem of increasing the efficiency of power units of autonomous electric transport vehicles is considered. The task of creating a promising power system control device has been singled out. It is determined that in creating such devices, significant results can be obtained by using an intelligent module in the control loop of the electric drive. Goal. It is necessary to develop a power plant model with intelligent control, allowing to obtain data sets about currents, voltages and engine speeds in different modes of operation. The architecture of an intelligent control device, a PID controller based on a neural network, has been proposed; it has been proposed to exclude rotor angular velocity sensors from the classical feedback loop. The type and architecture of the neural network is defined. In the software environment MatLab the model of neuroemulator of the engine for formation of a training sample of a neural network by a method of Levenberg – Marquardt is developed. The trained neural network is implemented in the developed model of the electric motor control loop. The results of simulation of the intelligent control device showed a good convergence of the output influences generated by the neuroemulator with the actual parameters of the electric motor.

Autonomous transport vehicles versus the principles of data protection law: is compatibility really an impossibility?

... This article addresses the compatibility of autonomous vehicles (AV) with the principles of data protection law under the legal framework of the European Union/European Economic Area (EU/EEA). The importance of this article lies in the fact that most data protection law provisions stem from these principles. It is therefore impossible to speak of data protection law compliance without an initial compliance with these rudimentary principles. AV embody the most advanced stage of vehicle automation whereby the system is completely and independently responsible for all driving tasks everywhere and at all times without any form of human intervention.1 To function properly, AV rely heavily on big data,2 which includes both the personal and non-personal3 data of drivers, passengers, road users, pedestrians, and other relevant persons. This effectively means that for AV to function as desired, it must necessarily interact or engage with other AV, Internet of things (IOT),4 traffic signs, cloud services, and other connected devices. Considering the central role data plays in the mode of operations of AV, it is essential that personal data forms the basis of the discussions in this article. Where necessary, the nature of the data (whether personal or not) will be expressly mentioned and specified.5 In order to properly address the impact of the principles of data protection law on AV, this article examines some of the ways through which AV collect (personal) data and the principles of data protection law as they pertain to AV. The concluding parts of this article consider the relationship between the principles of data protection law and AV, the inherent data protection law compliance challenges as well as the recommendation of appropriate remediation actions that could help resolve identified challenges.

Survey on Wireless Technology Trade-Offs for the Industrial Internet of Things.

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment.

Millimeter-Wave Communication for a Last-Mile Autonomous Transport Vehicle

Low-speed autonomous transport of passengers and goods is expected to have a strong, positive impact on the reliability and ease of travelling. Various advanced functions of the involved vehicles rely on the wireless exchange of information with other vehicles and the roadside infrastructure, thereby benefitting from the low latency and high throughput characteristics that 5G technology has to offer. This work presents an investigation of 5G millimeter-wave communication links for a low-speed autonomous vehicle, focusing on the effects of the antenna positions on both the received signal quality and the link performance. It is observed that the excess loss for communication with roadside infrastructure in front of the vehicle is nearly half-power beam width independent, and the increase of the root mean square delay spread plays a minor role in the resulting signal quality, as the absolute times are considerably shorter than the typical duration of 5G New Radio symbols. Near certain threshold levels, a reduction of the received power affects the link performance through an increased error vector magnitude of the received signal, and subsequent decrease of the achieved data throughput.

AGV autonomous transport units in technological transport

The article discusses a number of aspects related to the application of surface autonomous technological transport vehicles. The attention of the authors is mainly focused on issues related to the location of the technological means of transport in the working space, planning the traffic trajectory for the implementation of the transport task, technical possibilities in mapping the working space and intelligent method of control of AGV vehicles focused on efficiency. The article synthetically collects key information on key aspects related to the efficient management of both individual AGVs and their entire teams.

Robust and Real-Time Detection and Tracking of Moving Objects with Minimum 2D LiDAR Information to Advance Autonomous Cargo Handling in Ports.

Detecting and tracking moving objects (DATMO) is an essential component for autonomous driving and transportation. In this paper, we present a computationally low-cost and robust DATMO system which uses as input only 2D laser rangefinder (LRF) information. Due to its low requirements both in sensor needs and computation, our DATMO algorithm is meant to be used in current Autonomous Guided Vehicles (AGVs) to improve their reliability for the cargo transportation tasks at port terminals, advancing towards the next generation of fully autonomous transportation vehicles. Our method follows a Detection plus Tracking paradigm. In the detection step we exploit the minimum information of 2D-LRFs by segmenting the elements of the scene in a model-free way and performing a fast object matching to pair segmented elements from two different scans. In this way, we easily recognize dynamic objects and thus reduce consistently by between two and five times the computational burden of the adjacent tracking method. We track the final dynamic objects with an improved Multiple-Hypothesis Tracking (MHT), to which special functions for filtering, confirming, holding, and deleting targets have been included. The full system is evaluated in simulated and real scenarios producing solid results. Specifically, a simulated port environment has been developed to gather realistic data of common autonomous transportation situations such as observing an intersection, joining vehicle platoons, and perceiving overtaking maneuvers. We use different sensor configurations to demonstrate the robustness and adaptability of our approach. We additionally evaluate our system with real data collected in a port terminal the Netherlands. We show that it is able to accomplish the vehicle following task successfully, obtaining a total system recall of more than 98% while running faster than 30 Hz.

A Generic Multi-Layer Architecture Based on ROS-JADE Integration for Autonomous Transport Vehicles.

The design and operation of manufacturing systems is evolving to adapt to different challenges. One of the most important is the reconfiguration of the manufacturing process in response to context changes (e.g., faulty equipment or urgent orders, among others). In this sense, the Autonomous Transport Vehicle (ATV) plays a key role in building more flexible and decentralized manufacturing systems. Nowadays, robotic frameworks (RFs) are used for developing robotic systems such as ATVs, but they focus on the control of the robotic system itself. However, social abilities are required for performing intelligent interaction (peer-to-peer negotiation and decision-making) among the different and heterogeneous Cyber Physical Production Systems (such as machines, transport systems and other equipment present in the factory) to achieve manufacturing reconfiguration. This work contributes a generic multi-layer architecture that integrates a RF with a Multi-Agent System (MAS) to provide social abilities to ATVs. This architecture has been implemented on ROS and JADE, the most widespread RF and MAS framework, respectively. We believe this to be the first work that addresses the intelligent interaction of transportation systems for flexible manufacturing environments in a holistic form.

THE INFLUENCE OF SELF-DRIVING TRANSPORT VEHICLES ON THE FIELD OF LOGISTICS

The demands for transport are presently at quite high level. There are few transport branches which are used now, but in fact the road transport is the one used most. Transport actions are ought to deliver goods from point A to point B, and thus they influence the goals of logistics referred as 5R. Providing the right resource, in right place, on the right time, in right cost and in right quality, depend mostly on transport services. Using of the autonomous technology in transport allow to achieve better results in the field of logistics services. The purpose of this article was to present the benefits of autonomous transport and its influence on the logistics. Theoretical considerations were summarized with conclusions, which may become during the deliberation about the usage of autonomous transport vehicles.

Current Trends of Road-traffic Infrastructure Development

Abstract Recently many countries place stakes on such technologies as autonomous transportation vehicles and cooperative intelligent transportation systems. The prototypes have been built and undergo various tests in different countries worldwide, including Russia. However, this phenomenon is nothing else than the next stage of intelligent transportation systems (ITS) development, which has been aimed at complete change not only the idea of ITS, but the very process of conveyance of cargoes and passengers and a process of control of transportation vehicles.

Experimental Autonomous Road Vehicle with Logical Artificial Intelligence

This article describes some technical issues regarding the adaptation of a production car to a platform for the development and testing of autonomous driving technologies. A universal approach to performing the reverse engineering of electric power steering (EPS) for the purpose of external control is also presented. The primary objective of the related study was to solve the problem associated with the precise prediction of the dynamic trajectory of an autonomous vehicle. This was accomplished by deriving a new equation for determining the lateral tire forces and adjusting some of the vehicle parameters under road test conductions. A Mivar expert system was also integrated into the control system of the experimental autonomous vehicle. The expert system was made more flexible and effective for the present application by the introduction of hybrid artificial intelligence with logical reasoning. The innovation offers a solution to the major problem of liability in the event of an autonomous transport vehicle being involved in a collision.

An accurate and efficient navigation system for omnidirectional robots in industrial environments

Enhanced logistics is widely regarded as a key technology to increase flexibility and cost efficiency of today's factories. For example, fully autonomous transport vehicles aim to gradually replace conveyor belts, guided vehicles, and manual labor. In this context, especially omnidirectional robots are appealing thanks to their advanced maneuvering capabilities. In industrial applications, however, accuracy as well as safety and efficiency are key requirements for successful navigation systems. In this paper, we present an accurate navigation system for omnidirectional robots. Our system includes dedicated modules for mapping, localization, trajectory generation and robot control. It has been designed for accurate execution by devising smooth, curvature continuous trajectories, by planning appropriate velocities and by accounting for platform and safety constraints. In this way, it completely utilizes the maneuvering capabilities of omnidirectional robots and optimizes trajectories with respect to time of travel. We present extensive experimental evaluations in simulation and in changing real-world environments to demonstrate the robustness and accuracy of our system.

Adaptability checking in complex systems

A hierarchical approach for modelling the adaptability features of complex systems is introduced. It is based on a structural level S, describing the adaptation dynamics of the system, and a behavioural level B accounting for the description of the admissible dynamics of the system. Moreover, a unified system, called S[B], is defined by coupling S and B. The adaptation semantics is such that the S level imposes structural constraints on the B level, which has to adapt whenever it no longer can satisfy them. In this context, we introduce weak and strong adaptability, i.e. the ability of a system to adapt for some evolution paths or for all possible evolutions, respectively. We provide a relational characterisation for these two notions and we show that adaptability checking, i.e. deciding if a system is weakly or strongly adaptable, can be reduced to a CTL model checking problem. We apply the model and the theoretical results to the case study of a motion controller of autonomous transport vehicles.

Autonomous Transport Vehicles: Where We Are and What Is Missing

In this article, we address the problem of realizing a complete efficient system for automated management of fleets of autonomous ground vehicles in industrial sites. We elicit from current industrial practice and the scientific state of the art the key challenges related to autonomous transport vehicles in industrial environments and relate them to enabling techniques in perception, task allocation, motion planning, coordination, collision prediction, and control. We propose a modular approach based on least commitment, which integrates all modules through a uniform constraint-based paradigm. We describe an instantiation of this system and present a summary of the results, showing evidence of increased flexibility at the control level to adapt to contingencies.

Analysis of the Kinematics of an Eight-Wheeled Mobile Platform

This paper presents the modeling problem connected with the autonomous transport vehicle designed at Hochschule Ravensburg-Weingarten. The forward and inverse kinematics problem of eight-wheeled autonomous transport vehicle have been formulated and solved, additionally examples of simulation results representing the changes of individual motion parameters have been presented. Contact phenomenon between foundation and drive wheel has been taken into account in the kinematics model. Motion trajectory and velocity of the selected point belonging to the platform have been intended while the inverse kinematics problem has been solved. The forward kinematics problem has been worked out in order to verify correctness of the studied kinematics model. The presented simulation results point out compatibility of the worked out kinematics model of investigated object. The worked out models allow carrying out analysis of object motion through simulation investigations on the basis of proposed computational model.

Mechatronics Systems of Autonomous Transport Vehicle

The purpose of this paper is to present the development and realization of the elaborate mechatronic systems, having its main application in the logistic industry. The innovative, patented steering system is its unique feature. The steerage is based on the torque difference between the drive wheels. This solution allows for the unlimited maneuverability during the motion of the vehicle.

Versatile autonomous transportation vehicle for highly flexible use in industrial applications

In this paper an automated guided vehicle (AGV) for low payload is presented. By the use of low cost onboard sensors instead of expensive laser measurement devices the investment effort is reduced significantly. Ceiling cameras constantly track all static and moving obstacles. This information in combination with the vehicles local sensor data is leading to an optimized position estimations of both vehicles and obstacles.Every AGV is able to autonomously execute pending transportation tasks. That is why the presented indoor transportation solution provides a highly efficient way to realize an automated one-piece-flow concept in applications with varying environmental conditions.

Autonomous Transportation Vehicle Using Image Processing (Part 1)

Autonomous Transportation Vehicle Using Image Processing (Part 1)

Autonomous Transportation Vehicle Using Image Processing (part 3)

Autonomous Transportation Vehicle Using Image Processing (part 3)