Academic literature on the topic 'Autonomous vehicles (except systems infrastructures)'

Transport engineering has recently undergone several significant changes and innovations, one of which is the appearance and spread of autonomous vehicles; with this technology becoming more common and ordinary by the day, it is now necessary to implement some systems and contexts to facilitate autonomous vehicle operations. Consequently, a different perspective is now arising when dealing with road infrastructures, aiming to simplify and improve efficiency and maintenance of the existing roads, increase the life cycle of newly built ones, and minimize the economic and financial impact at the same time. Roadway pavements are one of the primary factors affecting vehicle operations; over time, this distinctive aspect has gone through various mechanical and physical changes due to the adoption of new materials or design methods. Consequently, to the spread of autonomous vehicles, scientific research has begun to study and develop systems to make road pavements and platforms not exclusively aimed at bearing loads, but rather at considering them as a means of communication and information exchange, if not even as a source of energy. This new approach introduces the so-called “Smart Roads,” i.e., road infrastructures capable of communicating with vehicles and self-monitoring fundamental perspectives concerning driverless vehicles and the roadway platform life cycle. This paper examines the characteristics of Smart Roads, considering their broad field of application and their potential advantages and drawbacks. This paper also pursues the objective of describing the global vision, the possible future direction of these innovations concerning the automotive and transport industries, and a particular focus on infrastructures and roadways.

The use of robotic systems, especially multi-rotor aerial vehicles, in the documentation of historical buildings and cultural heritage monuments has become common in recent years. However, the teleoperated robotic systems have significant limitations encouraging the ongoing development of autonomous unmanned aerial vehicles (UAVs). The autonomous robotic platforms provide a more accurate and safe measurement in distant and difficult to access areas than their teleoperated counterpart. Through the use of autonomous aerial robotic systems, access to such places by humans and building of external infrastructures like scaffolding for documentation purposes is no longer necessary. In this work, we aim to present a novel autonomous unmanned aerial vehicle designed for the documentation of hardly attainable areas of historical buildings. The prototype of this robot was tested in several historical monuments comprising scanned objects located in dark and hardly accessible areas in the upper parts of tall naves. This manuscript presents the results from two specific places: the Church of St. Anne and St. Jacob the Great in Stará Voda, and St. Maurice Church in Olomouc, both in the Czech Republic. Finally, we also compare the three-dimensional map obtained with the measurements made by the 3D laser scanner carried onboard UAV against the ones performed by a 3D terrestrial laser scanner.

Autonomous vehicles (AVs) can generate major changes in urban systems due to their ability to use road infrastructures more efficiently and shorten trip times. However, there is great uncertainty about these effects and about whether the use of these vehicles will continue to be private, in continuity with the current paradigm, or whether they will become shared (carsharing/ridesharing). In order to try to shed light on these matters, the use of a scenario-based methodology and the evaluation of the scenarios using a land use–transport interaction model (LUTI model TRANSPACE) is proposed. This model allows simulating the impacts that changes in the transport system can generate on the location of households and companies oriented to local demand and accessibility conditions. The obtained results allow us to state that, if AVs would generate a significant increase in the capacity of urban and interurban road infrastructures, the impacts on mobility and on the location of activities could be positive, with a decrease in the distances traveled, trip times, and no evidence of significant urban sprawl processes. However, if these increases in capacity are accompanied by a large augment in the demand for shared journeys by new users (young, elderly) or empty journeys, the positive effects could disappear. Thus, this scenario would imply an increase in trip times, reduced accessibilities, and longer average distances traveled, all of which could cause the unwanted effect of expelling activities from the consolidated urban center.

Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow.

Abstract In a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) standard requirements. Energy efficiency is an essential area of focus. In the production setup, the critical and real-time control systems need to be very efficient while implementing functions, namely, accurate sensing, fast processing and precise actuation. Automated Guided vehicles (AGVs) and Automated Guided Vehicles are an integral part of modern and intelligent manufacturing systems. Power consumption in such systems is directly proportional to the performance level achieved. However, there is a need to evolve strategies to reduce power consumption and attain optimal performance. Field Programmable Gate Array(FPGA) based controller solutions can provide competent performance at optimized power consumption. The proposed work discusses the requirements of I4.0 concerning energy efficiency infrastructures for the intelligent manufacturing setup. The need to develop efficient subsystems for sensing, decision-making and actuation based on FPGA is stressed. Thus the focus is on the FPGA based power-efficient models used for sensor fusion technique in Autonomous Mobile Robots. The fundamentals of sensor fusion technique and the need to fuse sensor data for improved decision making and actuation are emphasized.

Autonomous vehicles (AVs) are already operating on the streets of many countries around the globe. Contemporary concerns about AVs do not relate to the implementation of fundamental technologies, as they are already in use, but are rather increasingly centered on the way that such technologies will affect emerging transportation systems, our social environment, and the people living inside it. Many concerns also focus on whether such systems should be fully automated or still be partially controlled by humans. This work aims to address the new reality that is formed in autonomous shuttles mobility infrastructures as a result of the absence of the bus driver and the increased threat from terrorism in European cities. Typically, drivers are trained to handle incidents of passengers’ abnormal behavior, incidents of petty crimes, and other abnormal events, according to standard procedures adopted by the transport operator. Surveillance using camera sensors as well as smart software in the bus will maximize the feeling and the actual level of security. In this paper, an online, end-to-end solution is introduced based on deep learning techniques for the timely, accurate, robust, and automatic detection of various petty crime types. The proposed system can identify abnormal passenger behavior such as vandalism and accidents but can also enhance passenger security via petty crimes detection such as aggression, bag-snatching, and vandalism. The solution achieves excellent results across different use cases and environmental conditions.

The industrial development of the last few decades has prompted an increase in the number of vehicles by multiple folds. With the increased number of vehicles on the road, safety has become one of the primary concerns. Inter vehicular communication, specially Vehicle to Everything (V2X) communication can address these pressing issues including autonomous traffic systems and autonomous driving. The reliability and effectiveness of V2X communication greatly depends on communication architecture and the associated wireless technology. Addressing this challenge, a device-to-device (D2D)-based reliable, robust, and energy-efficient V2X communication architecture is proposed with LoRa wireless technology. The proposed system takes a D2D communication approach to reduce the latency by offering direct vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, rather than routing the data via the LoRa WAN server. Additionally, the proposed architecture offers modularity and compact design, making it ideal for legacy systems without requiring any additional hardware. Testing and analysis suggest the proposed system can communicate reliably with roadside infrastructures and other vehicles at speeds ranging from 15–50 km per hour (kmph). The data packet consists of 12 bytes of metadata and 28 bytes of payload. At 15 kmph, a vehicle sends one data packet every 25.9 m, and at 50 kmph, it sends the same data packet every 53.34 m with reliable transitions.

Abstract The complexity and dynamics in groupage traffic require flexible, efficient, and adaptive planning and control processes. The general problem of allocating orders to vehicles can be mapped into the Vehicle Routing Problem (VRP). However, in practical applications additional requirements complicate the dispatching processes and require a proactive and reactive system behavior. To enable automated dispatching processes, this article presents a multiagent system where the decision making is shifted to autonomous, interacting, intelligent agents. Beside the communication protocols and the agent architecture, the focus is on the individual decision making of the agents which meets the specific requirements in groupage traffic. To evaluate the approach we apply multiagent-based simulation and model several scenarios of real world infrastructures with orders provided by our industrial partner. Moreover, a case study is conducted which covers the autonomous groupage traffic in the current processes of our industrial parter. The results reveal that agent-based dispatching meets the sophisticated requirements of groupage traffic. Furthermore, the decision making supports the combination of pickup and delivery tours efficiently while satisfying logistic request priorities, time windows, and capacity constraints.

AbstractRecently, cooperative autonomous underwater vehicles (AUVs) have been deployed in application areas such as surveillance and protection of maritime infrastructures for inspection and monitoring purposes. These cooperative methodologies require wireless transmission of data between the different AUVs operating in the underwater environment. Communication over ranges exceeding 100 m exclusively relies on underwater acoustic communication. However, the propagating acoustic waves suffer from several challenges due to the presence of path loss, multi-path propagation, the slow and variant propagation speed, background noise, and Doppler distortion. Since the power supply of the AUVs is limited, communication must be very energy efficient and energy constraints have to be known to be able to plan the mission of AUVs. Due to the difficulties of real experiments, the modeling and simulation of the energy consumption and underwater acoustic communication play an essential role in studying and developing these systems. We provide a modular simulation model for the energy consumption and acoustic underwater communication of AUVs implemented in the network simulator OMNeT++ using the INET framework. More specifically, we extend several INET modules in such a way as to reflect the characteristics of AUVs and underwater communication. We study and analyze the AUVs’ energy consumption and dependence of the message quality on different properties such as those mentioned above.

In recent years, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication brings more and more attention from industry (e.g., Google and Uber) and government (e.g., United States Department of Transportation). These Vehicle-to-Everything (V2X) technologies are widely adopted in future autonomous vehicles. However, security issues have not been fully addressed in V2V and V2I systems, especially in key distribution and key management. The physical layer key generation, which exploits wireless channel reciprocity and randomness to generate secure keys, provides a feasible solution for secure V2V/V2I communication. It is lightweight, flexible, and dynamic. In this paper, the physical layer key generation is brought to the V2I and V2V scenarios. A LoRa-based physical key generation scheme is designed for securing V2V/V2I communications. The communication is based on Long Range (LoRa) protocol, which is able to measure Received Signal Strength Indicator (RSSI) in long-distance as consensus information to generate secure keys. The multi-bit quantization algorithm, with an improved Cascade key agreement protocol, generates secure binary bit keys. The proposed schemes improved the key generation rate, as well as to avoid information leakage during transmission. The proposed physical layer key generation scheme was implemented in a V2V/V2I network system prototype. The extensive experiments in V2I and V2V environments evaluate the efficiency of the proposed key generation scheme. The experiments in real outdoor environments have been conducted. Its key generation rate could exceed 10 bit/s on our V2V/V2I network system prototype and achieve 20 bit/s in some of our experiments. For binary key sequences, all of them pass the suite of statistical tests from National Institute of Standards and Technology (NIST).

The issue of Command and Control (C2) is generally associated with the management infrastructure of large scale systems for warfare, public utilities and public transportation, and is concerned with ensuring that the distributed human elements of command and control can be fully integrated into a coherent, total system. Intelligent Autonomous Systems (IASs) are a class of complex systems that perform tasks autonomously in uncertain, dynamic environments, the management of which can be viewed from the perspective of embedded command and control systems. This thesis establishes a vision for the modular construction of intelligent autonomous embedded C2 systems, which defines a complex integration problem characterised by distributed intelligence, world knowledge and control, concurrent processing on heterogeneous platforms, and real-time performance requirements. It concludes that by adopting an appropriate systems infrastructure model, based on Object Technology, it is possible to view the construction of embedded C2 systems as the integration of a temporally assembled collection of reusable components. To support this metaphor it is necessary to construct a common reference model, or standards framework, for the representation and specification of modular C2 systems. This framework must support the coherent long term development and evolution in system capability, ensuring that systems are extensible, robust and perform correctly. In this research, which draws together the themes of other published research in object oriented systems and robotics, classical AI models for intelligent systems architectures are used to specify the overall system structure, with open systems technologies supporting the interoperation of elements within the architecture. All elements of this system are modelled in terms of objects, with well defined, implementation independent interfaces. This approach enables the system to be specified in terms of an object model, and the development process to be framed in terms of object technology, defining a new approach to IAS development. The implementation of an On-board Command and Control System for an Autonomous Underwater Vehicle is used to validate these concepts. The further application of emergent industrial standards in distributed object oriented systems means that this kind of component-based integration is scaleable, providing a near-term solution to generic command and control problems, including Computer Integrated Manufacturing and large scale autonomous systems, where individual autonomous systems, such as robots, form elements of a complete, total intelligent system, for application to areas such as fully automated factories and cooperating intelligent autonomous vehicles for construction sites.

Self-driving vehicles do not simply translate algorithmic definitions of their interaction with the environment into material actions. In the implementation of microdecisions, temporality itself becomes an element of the success of operations. Taking the fascination for a non-human and distributed capability of decision-making as a starting point, the paper explores how the temporality of microdecisions is integrated into technical systems that interact with their surroundings. On the basis of a media archaeology of these temporalities, it develops a heuristic of autonomous technologies that explores the role of micro-decisions. With self-driving cars, terms such as agency (based on algorithms), temporality (in different intervals of intervention), decision (in reference to alternative scenarios), and autonomy achieve new meanings worthy of a re-interpretation.

In the field of transport, the reduction in the number of accidents caused by human error is often put forward as an argument in favor for the deployment of autonomous vehicle (Fagnant, & Kockelman, 2015). However, as long as autonomous vehicles are not capable of handling all driving situations, the human operator remains in the control loop and cooperates with the autonomous system (SAE levels 2, 3, and 4 - scale from 0 to 5 where 5 corresponding to the fully autonomous vehicle). The development of supervision systems could be a means to improve safety in these systems, as it has been the case in other transportation modes such as aviation and railways. Indeed, the supervision of autonomous vehicles (e.g.: shuttle fleet) would enable to secure the operation by anticipating incidents (e.g.: support the driver-system relationship, as an air traffic controller would do for pilots), while guaranteeing the reliability (management of system failures) and regularity of the transportation network. However, for Hoc (2000), automation is nevertheless at the origin of a certain number of deleterious effects on the human operator, such as a loss of expertise and adaptability or a lack or excess of confidence in the system, which can lead to errors. Also, human operators can misuse or abuse the automation technology. (Parasuraman and Riley, 1997). Moreover, in this human-machine cooperation, many effects have been observed such as automation bias and complacency phenomena, which can also lead to accidents (Parasuraman & Manzey, 2010).In the perspective of the literature review, we wish to bring keys elements to the designers to create a safe automated driving system. We anticipate this need through the analysis of work activity and creativity. However, autonomous vehicles not representing a mature technology or having applications in the current society. That requires a projection into a future environment and study of the resulting human factors. Prospective ergonomics (Brangier & Robert, 2014) permits to leads us to deploy that. To anticipate the major functions necessary for the future supervision activity, the approach of the “possible future activity” is applied (Daniellou, 1992). This approach studies the reference situations. We identified many sectors of activity with strong similarities with our system such as aviation, railways, bus or nuclear. Until now, four situations were integrated: the supervision of buses and tramways, the civil air traffic control, and the military air traffic control and the autonomous drone in logistics. These reference situations allowed us to identify their strength and weakness around 7 major components of the supervision (safety, infrastructure, hardware, degree of automation, software, organization of the system and human factor). This step builds prerequisites for the creation of the future supervision system. To integrate and adapt them, the next step will be the realization of creativity workshops which will revolve around expert-staff with the objective of proposing a set of specifications for the designers of the main functions to allow the integration of the human factor from the first phases of implementation in this system.

Despite a slow pace, Nuclear Power is undergoing a global renaissance. Small modular reactors (SMR) and microreactors are in various design and commissioning phases. These are designed to be built in factories and installed onsite, providing a means to rapidly deploy nuclear power while controlling for uncertain capital expenditures and cost overruns. The OECD (2016) is projecting that by 2035 we could have 21 GWe of new nuclear electricity capacity installed globally with 3.5 GWe in the United States.Simultaneously, renewables such as wind and solar are growing exponentially and battery electric vehicles are gaining traction in the energy sector. If vehicles transition to battery electric vehicles (BEV) our electricity consumption would roughly double. The energy grid as a whole is evolving as numerous point source generators come online and smarter grids enable better resource management and dynamic pricing. The result will be a distributed energy market where individuals and utilities both buy and sell resources in a fast-paced, brokered market. Or perhaps more accurately, autonomous agents will buy and sell resources on behalf of utilities, individuals, and intermediaries.The pertinent question then becomes how do we have human oversight of resources to maintain safe, secure, and reliable operation?A reasonable approach is to examine assets as three general classes. The first class comprises commodity consumer-oriented devices such as home solar, battery storage, and BEVs represented distributed nano-scale devices. The capital expenditures of any single device or installation are relatively small, and the potential consequences of a single installation failing are relatively small. Minimal regulatory oversight is required for individual installations. The second class comprises distributed micro-scale devices like nuclear micro-reactors and small modular reactors. These will have substantial automation compared to existing Generation II reactors. They could incorporate remote operations and monitoring at the fleet scale, with the ability to shut down systems locally. Disruptions would have costly impacts to an organization or municipality.Lastly, at the other end of the spectrum are high-value assets with the potential for low-probability high consequence events. These would include gigawatt-scale nuclear/solar/hydro plants that might also have flexible operations to support onsite data centers, hydrogen production, or cryptomining. These assets would be high-value targets and distruptions would have the potential for severe economic, environmental, and functional consequences at large geographic scales. When we start thinking about human oversight, participation, and decision making, the first class is consumer-oriented. Consumers will be enabled to become prosumers (producers and consumers) sell excess or optimize energy usage and storage based on dynamic rates.The third class of high-value assets resembles how critical infrastructure is managed today. These high-value assets are conservative and slow to evolve through the adoption of automation and operational changes. They would still need to maintain high degrees of human vigilance compared to the other systems for regulatory adherence and maintaining cyber-physical security and reliability.The second class still has high regulatory requirements. However, it is a bit of a clean slate to conceptualize operations and monitoring from first principles with high levels of automation and mixed-initiative monitoring and control (AI/human teaming). In this paper we explore those possibilities.New SMR and microreactors incorporate passive safety and modern engineering modeling and analysis that wasn't available during the design and commisioning of Generation II reactors. The result is reactors that have significantly reduced risks of catastrophic melt-down events like Fukishima. This dramatically expands the possibilities for how they can be monitored and controlled. When we ponder what modern nuclear control rooms should look like we envision multiple operators monitoring dozens of screens to maintain situational awareness and readiness to respond at a moments notice. However, this is unlikely and perhaps even undersired. Once reactors, in particular microreactors, have the demonstrated capability of operating hands-free with minimal oversight it becomes misguided to install humans to maintain constant vigilance (e.g. Level 4 to 5 self-driving). The key performance indicator should be system performance not situational awareness. Having "operators" permanently installed in a control room when no action is required 99.9% of the time becomes a superficial level of vigilance. Take system administration as a corollary. System administrator's primary responsibility is to maintain the availability of infrastructure, but their primary tasking is not to sit idly by and actively monitor.

Recent advancements of electric vertical take-off and landing (eVTOL) aircraft have generated significant interest within and beyond the traditional aviation industry, and many novel applications have been identified and are in development. One promising application for these innovative systems is in firefighting, with eVTOL aircraft complementing current firefighting capabilities to help save lives and reduce fire-induced damages. With increased global occurrences and scales of wildfires—not to mention the issues firefighters face during urban and rural firefighting operations daily—eVTOL technology could offer timely, on-demand, and potentially cost-effective aerial mobility capabilities to counter these challenges. Early detection and suppression of wildfires could prevent many fires from becoming large-scale disasters. eVTOL aircraft may not have the capacity of larger aerial assets for firefighting, but targeted suppression, potentially in swarm operations, could be valuable. Most importantly, on-demand aerial extraction of firefighters can be a crucial benefit during wildfire control operations. Aerial firefighter dispatch from local fire stations or vertiports can result in more effective operations, and targeted aerial fire suppression and civilian extraction from high-rise buildings could enhance capabilities significantly. There are some challenges that need to be addressed before the identified capabilities and benefits are realized at scale, including the development of firefighting-specific eVTOL vehicles; sense and avoid capabilities in complex, smoke-inhibited environments; autonomous and remote operating capabilities; charging system compatibility and availability; operator and controller training; dynamic airspace management; and vehicle/fleet logistics and support. Acceptance from both the first-responder community and the general public is also critical for the successful implementation of these new capabilities. The purpose of this report is to identify the benefits and challenges of implementation, as well as some of the potential solutions. Based on the rapid development progress of eVTOL aircraft and infrastructures with proactive community engagement, it is envisioned that these challenges can be addressed soon. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.