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Future Autonomous Transportation: Challenges and Prospective Dimensions
Abstract
Transportation is an integral and fundamental part of human beings’ lives. On Earth, we need transportation in the form of cars, buses, trains, etc. We need aircraft in the air and ships at sea for long-distance transportation. We need space shuttles in space to travel beyond the air. The main desire of human beings is to complete tasks with less energy, effort, time, and more security. The whole paradigm of humanity’s lifestyle can be shifted by autonomous transport (AT), which is already deployed in different technologically advanced countries. The Autonomous Transport System (ATS) is more secure and reliable than the current system of conventional transportation. With the aid of machine learning (ML), artificial intelligence (AI), and blockchain technologies, ultra-fast processing computers can make autonomous vehicles smarter, safer, and more secure than ever before. Connecting vehicles can communicate with the infrastructure to alert the driver about events such as when a train is coming, when a driver cannot see or hear the approaching train, etc. ATS can have a tremendous effect on all we do. However, there are certain challenges involved with every technology, and once we overcome these problems, these ATS can make life simpler, smarter, and safer. Furthermore, we discuss the challenges and future directions for the ATS.
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The sixth-generation (6G) wireless communication network is expected to integrate the terrestrial, aerial, and maritime communications into a robust network which would be more reliable, fast, and can support a massive number of devices with ultra-low latency requirements. The researchers around the globe are proposing cutting edge technologies such as arti cial intelligence (AI)/machine learning (ML), quantum com- munication/quantum machine learning (QML), blockchain, tera-Hertz and millimeter waves communication, tactile Internet, non-orthogonal multiple access (NOMA), small cells communication, fog/edge computing, etc., as the key technologies in the realiza- tion of beyond 5G (B5G) and 6G communications. In this article, we provide a detailed overview of the 6G network dimensions with air interface and associated potential technologies. More speci cally, we highlight the use cases and applications of the proposed 6G networks in various dimensions. Furthermore, we also discuss the key performance indicators (KPI) for the B5G/6G network, challenges, and future research opportunities in this domain.
The staggering growth of the number of vehicles worldwide has become a critical challenge resulting in tragic incidents, environment pollution, congestion, etc. Therefore, one of the promising approaches is to design a smart vehicular system as it is beneficial to drive safely. Present vehicular system lacks data reliability, security, and easy deployment. Motivated by these issues, this paper addresses a drone-enabled intelligent vehicular system, which is secure, easy to deploy and reliable in quality. Nevertheless, an increase in the number of operating drones in the communication networks makes them more vulnerable towards the cyber-attacks, which can completely sabotage the communication infrastructure. To tackle these problems, we propose a blockchain-based registration and authentication system for the entities such as drones, smart vehicles (SVs) and roadside units (RSUs). This paper is mainly focused on the blockchain-based secure system design and the optimal placement of drones to improve the spectral efficiency of the overall network. In particular, we investigate the association of RSUs with the drones by considering multiple communication-related factors such as available bandwidth, maximum number of links a drone can support, and backhaul limitations. We show that the proposed model can easily be overlaid on the current vehicular network reaping benefits of secure and reliable communications.
In this paper, we investigate the downlink performance of a three-tier heterogeneous network (HetNet). The objective is to enhance the edge capacity of a macro cell by deploying unmanned aerial vehicles (UAVs) as flying base stations and small cells (SCs) for improving the capacity of indoor users in scenarios such as temporary hotspot regions or during disaster situations where the terrestrial network is either insufficient or out of service. UAVs are energy-constrained devices with a limited flight time, therefore, we formulate a two layer optimization scheme, where we first optimize the power consumption of each tier for enhancing the system energy efficiency (EE) under a minimum quality-of-service (QoS) requirement, which is followed by optimizing the average hover time of UAVs. We obtain the solution to these nonlinear constrained optimization problems by first utilizing the Lagrange multipliers method and then implementing a sub-gradient approach for obtaining convergence. The results show that through optimal power allocation, the system EE improves significantly in comparison to when maximum power is allocated to users (ground cellular users or connected vehicles). The hover time optimization results in increased flight time of UAVs thus providing service for longer durations.
The main field of our research is artificial intelligence already implemented in the experimental autonomous road vehicle. Artificial intelligence now is a really huge area of studies. This investigation is focused more on a development of intelligent systems. Such as expert systems, semantic text processing systems, semantic image understanding systems, robotics systems. Wi!Mi is a solution for developing mivar knowledge models. This tool belongs to the class of so-called ES shells - programs that allow significantly simplify and accelerate the ES development process. It uses a novel knowledge representation mechanism based on bipartite graphs and the significantly improved but simple inference engine, which is able to process large systems involving millions of variables in just a few seconds. A special representation model which is called mivar nets with linear computational complexity using if-then rules is used in Wi!Mi. The idea is that the subject domain is divided into objects and connections between them. Scientific investigation allows to implement new decision-making system called "RoboRazum" as a form of an embedded software platform with flexible capabilities to adapt to control by any robotic suites and systems. RoboRazum is a platform for designing autonomous robotic control systems. Provided solutions don't require powerful computational resources and could be used in small systems-on-chip like microcontrollers. That is why this solution is perfectly fit with conception of Internet of Things (IoT). Reasoned and fast logical decisions based on mivar technologies play important role for autonomous road vehicles.
Blockchain, widely known as one of the disruptive technologies emerged in recent years, is experiencing rapid development and has the full potential of revolutionizing the increasingly centralized intelligent transportation systems (ITS) in applications. Blockchain can be utilized to establish a secured, trusted and decentralized autonomous ITS ecosystem, creating better usage of the legacy ITS infrastructure and resources, especially effective for crowdsourcing technology. This paper conducts a preliminary study of Blockchain-based ITS (B 2 ITS). We outline an ITS-oriented, seven-layer conceptual model for blockchain, and on this basis address the key research issues in B 2 ITS. We consider that blockchain is one of the secured and trusted architectures for building the newly developed parallel transportation management systems (PtMS) , and thereby discuss the relationship between B 2 ITS and PtMS. Finally, we present a case study for blockchain-based realtime ride-sharing services. In our viewpoint, B 2 ITS represents the future trend of ITS research and practice, and this paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works.
Vehicular networks and the recent Internet of Vehicles (IoV) are continuously developing, aiming to solve the current and novel challenging needs in the domain of transportation systems. Edge computing offers a natural support for Internet of Vehicles, supporting fast response, context awareness, and minimization of the data transfer to the centralized data centers-all these being allowed by the edge computing availability close to mobile vehicles. Multi-access (Mobile) Edge Computing, fog computing, cloudlets, etc., are such candidates to support IoV; their architectures and technologies have overlapping characteristics but also differences in approach. A full convergence between them has not yet been achieved. Also, it is still not completely clarified which solution could be the best trade-off to be adopted in the Internet of vehicles context and for which use cases. This paper is not a complete survey, but attempts a preliminary evaluation of some of the currently proposed Mobile Edge Computing and fog computing solutions for vehicular networks.
In this paper, the possibility of using the autonomous vehicles with the contribution of Blockchain technology as part of a service is examined. As a first step a short Literature review of Autonomous Vehicles as well as Blockchain technology is provided. Blockchain is another newly established technology and its main purpose is to facilitate secure online transactions. Furthermore, through this paper it is explained that together Autonomous vehicles and Blockchain technology could provide the end user with cleaner, more economical and efficient transportation. In addition, a publicly owned system is described, where the two technologies combine, and the autonomous vehicle will provide the user the most convenient route based on real-time traffic information, while Blockchain will make the economic transaction easier since it could allow peer-to-peer carsharing and eliminate the need for banks. Moreover, in order to fully understand this system the rising concerns regarding these technologies are mentioned. This paper aims to examine such a possible service using autonomous vehicles and Blockchain technology, since they essentially could become the future of transportation.
Emerging info-communication and vehicle technologies (especially vehicle automation) facilitate evolvement of autonomous road freight transportation. The entire transport system and its operation undergo a major change. New service concepts are growing and the existing ones are being transformed. The changing is particularly significant in city logistics. However, there are debates about the ways of automation of processes targeting improvement of capacity utilisation and decrease of expenditures. The main research questions of the paper are therefore: what properties of the future autonomous freight transportation are presumed; what system structure is to be constructed and how the system is to be operated? After introducing the basic notions and reviews of the current systems and developments, the shifting from traditional freight transportation to autonomous system is investigated by several aspects. A system- and process-oriented analytical modelling method has been applied. The main system constituents and their connections are modelled. Finally, we elaborate the operational model of road freight transportation, which is applicable principally in metropolitan areas. In conclusion, the presented
results appoint the research and innovation trends towards the automation of freight transportation.
Smart Transportation applications by nature are examples of Vehicular Ad-hoc Network (VANETs) applications where mobile vehicles, roadside units and transportation infrastructure interplay with one another to provide value added services. While there are abundant researches that focused on the communication aspect of such Mobile Ad-hoc Networks, there are few research bodies that target the development of VANET applications. Among the popular VANET applications, a dominant direction is to leverage Cloud infrastructure to execute and deliver applications and services. Recent studies showed that Cloud Computing is not sufficient for many VANET applications due to the mobility of vehicles and the latency sensitive requirements they impose. To this end, Fog Computing has been proposed to leverage computation infrastructure that is closer to the network edge to compliment Cloud Computing in providing latency-sensitive applications and services. However, applications development in Fog environment is much more challenging than in the Cloud due to the distributed nature of Fog systems. In this paper, we investigate how Smart Transportation applications are developed following Fog Computing approach, their challenges and possible mitigation from the state of the arts.
Emerging infocommunication and vehicle technologies (e.g. autonomous vehicle) facilitate evolvement of autonomous public transportation in urban areas. It involves launching new service concepts (e.g. telematics-based shared demand responsive transportation), transformation of existing modes and automatization of passenger handling functions. However, there are debates about which processes how to be automatized. The aim is to replace human personnel by machines so as to improve service quality
and decrease expenditures. The research questions were, how the functions are to be automatized and what the consequences are on both the machine and the human side. All the passenger handling functions, the existing and altering ones as well as the new functions have been investigated in process and system oriented approach. We have considered the most relevant technological novelties and their application opportunities, and then the required abilities (skills) of travelers. We have revealed correspondences among functions and human abilities. The shifting of intensities of human abilities (cognitive capability) have been estimated. Personnel groups with altering or new functions have been introduced and the functions of the replaced driver have been assigned to the groups or the machine components. Both the gains and the occurrent drawbacks have been assessed. The presented results appoint the research and innovation trends and directly facilitate the developments (e.g. design of smart devices and services as human-machine interface).
This study investigates the challenges and opportunities pertaining to transportation policies that may arise as a result of emerging Autonomous Vehicle (AV) technologies. AV technologies can decrease the transportation cost and increase accessibility to low income households and persons with mobility issues. This emerging technology also has far-reaching applications and implications beyond all current expectations. This paper provides a comprehensive review of the relevant literature and explores a broad spectrum of issues from safety to machine ethics. An indispensable part of a prospective AV development is communication over cars and infrastructure (connected-vehicles). A major knowledge gap exists in AV technology with respect to routing behaviors. Connected-vehicle technology provides a great opportunity to implement an efficient and intelligent routing system. To this end, we propose a conceptual navigation model based on a fleet of AVs that are centrally dispatched over a network seeking system optimization. This study contributes to the literature on two fronts: (i) it attempts to shed light on future opportunities as well as possible hurdles associated with AV technology; and (ii) it conceptualizes a navigation model for the AV which leads to highly efficient traffic circulations.
Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to our transportation system. This new technology has the potential to impact vehicle safety, congestion, and travel behavior. All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2000 to per year per AV, and may eventually approach nearly $4000 when comprehensive crash costs are accounted for. Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be unaffordable. Licensing and testing standards in the U.S. are being developed at the state level, rather than nationally, which may lead to inconsistencies across states. Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm. The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain. To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy.
The status in the development of the new class of micro air vehicles (MAVs) and some emerging trends in the technology that can lead to more efficient small-scale flying machines, are discussed. These vehicles have been defined to have no length dimension greater than 6 in. with gross takeoff weights of approximately 200g or less. The new capabilities projected for the next generation of MAV designs include silent flight as fuel cells and battery technology supplant internal combustion engines, 60% gains in endurance caused by increasingly efficient turbine engines, and self-repairing, damage compensating, more survivable. The emerging technology is the combination of multifunctional structures and propulsion technology.
With the surge in the demand for online services and multimedia applications, the traffic on the underlying network infrastructure has escalated (multi-folded) in recent years. To meet the strict latency requirements, Software-defined Networking (SDN) provides flexible network control (and possible intelligence) that can act as an enabler for application-oriented service industry. However, the crippling gap between the business needs and the network delivery potential necessitates the underlying network to constantly (and consistently) adapt, protect, and inform across all strands of the service-oriented landscape. Intent-based network has emerged as a recent solution to the cover the above gap by capturing business intent and thereafter activating and assuring it networkwide. Motivated from these facts, in this article, an Intent-based network control framework has been designed over the SDN architecture for data dissemination in the vehicular edge computing ecosystem. In this framework, a tensor-based mechanism is used to reduce the dimensionality of the incoming elephant-like traffic and then classifying the specific-attribute data traffic according to the defined priority requirement of the underlying applications. Here, the network policies are configured using the intent-based controller according to the application requirement and then forwarded to the SDN controller to enable intelligent data dissemination (through an optimal route) at the data plane. Convolution Neural Network is used to train the flow table to allocate the route dynamically for the classified traffic queues. The proposed framework has been evaluated through extensive simulations and the results supports the claims in terms of the quality of service requirements.
There has been an increasing trend of moving computing activities closer to the edge of the network, particularly in smart city applications (e.g., vehicle-to-everything -- V2X). Such a paradigm allows the end user's requests to be handled / processed by nodes at the edge of the network; thus, reducing latency, and preserving privacy of user data / activities. However, there are a number of challenges in such an edge computing ecosystem. Examples include (1) the potential for improper utilization of resources at the edge nodes, (2) operational challenges in cache management and data integrity due to data migration between edge nodes, particularly when dealing with vehicular mobility in a V2X application, and (3) high energy consumption due to continuous link breakage and subsequent reestablishment of link(s). Therefore in this paper, we design a blockchain-based secure data processing framework for an edge envisioned V2X environment (hereafter referred to as \textit{BloCkEd}). Specifically, a multi-layered edge-enabled V2X system model for \textit{BloCkEd} is presented, which includes the formulation of a multi-objective optimization problem. In addition, \textit{BloCkEd} comprises an optimal container-based data processing scheme, and a blockchain-based data integrity management scheme, designed to minimize link breakage and reducing latency. Using Chandigarh City, India, as the scenario, we implement and evaluate the proposed approach in terms of its latency, energy consumption, and service level agreement compliance.
Mobility is the backbone of urban life and a vital economic factor in the development of the world. Rapid urbanization and the growth of mega-cities are bringing dramatic changes in the capabilities of vehicles. Innovative solutions like autonomy, electrification, and connectivity are on the horizon. How, then, we can provide ubiquitous connectivity to legacy and autonomous vehicles? This article seeks to answer this question by combining recent leaps of innovation in network virtualization with remarkable feats of wireless communications. To do so, this article proposes a novel paradigm called the Internet of Autonomous Vehicles (IoAV). We begin painting the picture of IoAV by discussing the salient features and applications of IoAV, followed by a detailed discussion on the key enabling technologies. Next, we describe the proposed layered architecture of IoAV and uncover some critical functions of each layer. This is followed by the performance evaluation of IoAV, which shows significant advantages of the proposed architecture in terms of transmission time and energy consumption. Finally, to best capture the benefits of IoAV, we enumerate some social and technological challenges, and explain how some unresolved issues can disrupt the widespread use of autonomous vehicles in the future.
Automated vehicles (AVs) already navigate US highways and those of many other nations around the world. Current questions about AVs do not now revolve around whether such technologies should or should not be implemented; they are already with us. Rather, such questions are more and more focused on how such technologies will impact evolving transportation systems, our social world, and the individuals who live within it and whether such systems ought to be fully automated or remain under some form of direct human control. More importantly, how will mobility itself change as these independent operational vehicles first share and then dominate our roadways? How will the public be kept apprised of their evolving capacities, and what will be the impact of science and the communication of scientific advances across the varying forms of social media on these developments? We look here to address these issues and to provide some suggestions for the problems that are currently emerging.
Cloud computing has emerged as a popular technologies which provide on-demand services to the end users. Such services are hosted by massive geo-distributed data centers(DCs). Nowadays, connected vehicles in a smart city can also avail cloud services through Internet using cellular technologies. But, the advent of 5G technology has posed challenges for DCs such as-low latency and higher data rate requirements. To handle these challenges, edge-DCs(EDCs) can be deployed across a smart city to provide low latency services to the connected vehicles. In lieu of this, in this paper, EDCSuS: Sustainable EDC as a service framework in software defined vehicular environment is proposed. In EDCSuS, firstly, a software defined controller handles the incoming requests and suggest an optimal flow path. Secondly, a multi-leader multi-follower Stackelberg game is presented for resource allocation. Thirdly, to improve the resource utilization, a cooperative resource sharing scheme is designed, thereby minimizing the energy consumption of servers in the EDCs. Lastly, a caching scheme is presented to avert excessive energy consumption for retracing the lost link due to vehicular mobility. The efficacy of the proposed scheme has been evaluated using extensive simulations with respect to various parameters. The results obtained prove the effectiveness of EDCSuS.
Connected and automated vehicle (CAV) is a transformative technology that has great potential to change our daily life. Therefore, CAV related research has been advanced significantly in recent years. This paper does a comprehensive review on five selected subjects that lie in the heart of CAV research: (i) inter-CAV communications; (ii) security of CAVs; (iii) intersection control for CAVs; (iv) collision-free navigation of CAVs; and (v) pedestrian detection and protection. It is believed that these topics are essential to ensure the success of CAVs and need to be better understood. For inter-CAV communications, this paper focuses on both Dedicated Short Range Communications (DSRC) and the future 5G cellular technologies; for security of CAVs, this paper discusses both passive and active attacks and the existing solutions; for intersection control, this paper summarizes the pros and cons of both centralized and decentralized approaches; for collision avoidance, this paper concentrates on four subareas: maneuverability, vehicle networking, control confliction, and motorcycles; for pedestrian detection, this paper covers sensor, radar, and computer vision based approaches. Under each topic, this paper not only shows the state-of-the-art, but also unveils potential future research directions. By establishing connections among these subjects, this paper shows how they interact with each other and how they can be integrated into a seamless user experience. It is believed that the literature covered and conclusions drawn in this paper are very helpful to CAV researchers, application engineers, and policy makers.
There could be no smart city without a reliable and efficient transportation system. This necessity makes the ITS a key component of any smart city concept. While legacy ITS technologies are deployed worldwide in smart cities, enabling the next generation of ITS relies on effective integration of connected and autonomous vehicles, the two technologies that are under wide field testing in many cities around the world. Even though these two emerging technologies are crucial in enabling fully automated transportation systems, there is still a significant need to automate other road and transportation components. To this end, due to their mobility, autonomous operation, and communication/processing capabilities, UAVs are envisaged in many ITS application domains. This article describes the possible ITS applications that can use UAVs, and highlights the potential and challenges for UAV-enabled ITS for next-generation smart cities.
We survey the recent work on micro unmanned aerial vehicles (UAVs), a fast-growing field in robotics, outlining the opportunities for research and applications, along with the scientific and technological challenges. Micro-UAVs can operate in three-dimensional environments, explore and map multi-story buildings, manipulate and transport objects, and even perform such tasks as assembly. While fixed-base industrial robots were the main focus in the first two decades of robotics, and mobile robots enabled most of the significant advances during the next two decades, it is likely that UAVs, and particularly micro-UAVs, will provide a major impetus for the next phase of education, research, and development.
This paper explores the technical feasibility of five Advanced Driver Assistance System (ADAS) functions to contribute to road traffic safety, to reach stated European (EU) and national road traffic safety targets. These functions – enhanced navigation, speed assistance, collision avoidance, intersection support and lane keeping – were selected from previous research as adequate substitutes for infrastructure related measures. State-of-the-art enabling technologies (like positioning, radar, laser, vision and communication) and their potential are analysed from a technical perspective, and possible obstacles for large-scale dedicated ADAS implementation for road traffic safety are discussed.
This paper reports the development and at-sea deployment of a set of algorithms that have enabled the autonomous underwater vehicle ABE to conduct near-bottom surveys in the deep sea. Algorithms for long baseline acoustic positioning, terrain-following, and automated nested surveys are reported.
This paper describes a vision-based system for inspections of
underwater structures, e.g., pipelines, cables, etc., by an autonomous
underwater vehicle (AUV). Usually underwater inspections are performed
by remote operated vehicles (ROVs) driven by human operators placed in a
support vessel. However, this task is often challenging, especially in
conditions of poor visibility or in presence of strong currents. The
system proposed allows the AUV to accomplish the task in autonomy.
Moreover, the use of a three-dimensional (3-D) model of the environment
and of an extended Kalman filter (EKF) allows the guidance and the
control of the vehicle in real time. Experiments done on real underwater
images have demonstrated the validity of the proposed method and its
efficiency in the case of critical and complex situations
Literature review on the social challenges of autonomous transport
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