Download or read book Multi agent Collaborative Perception for Autonomous Driving Unsettled Aspects written by Guang Chen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAE EDGE Research Reports provide state-of-the-art and state-of-industry examinations of the most significant topics in mobility engineering. SAE EDGE contributors are experts from research, academia, and industry who have come together to explore and define the most critical advancements, challenges, and future direction in areas such as vehicle automation, unmanned aircraft, IoT and connectivity, cybersecurity, advanced propulsion, and advanced manufacturing.

Download or read book Comap A Synthetic Dataset for Collective Multi agent Perception of Autonomous Driving written by Y. Yuan and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Autonomous Driving Perception written by Rui Fan and published by Springer Nature. This book was released on 2023-10-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the captivating world of computer vision and deep learning for autonomous driving with our comprehensive and in-depth guide. Immerse yourself in an in-depth exploration of cutting-edge topics, carefully crafted to engage tertiary students and ignite the curiosity of researchers and professionals in the field. From fundamental principles to practical applications, this comprehensive guide offers a gentle introduction, expert evaluations of state-of-the-art methods, and inspiring research directions. With a broad range of topics covered, it is also an invaluable resource for university programs offering computer vision and deep learning courses. This book provides clear and simplified algorithm descriptions, making it easy for beginners to understand the complex concepts. We also include carefully selected problems and examples to help reinforce your learning. Don't miss out on this essential guide to computer vision and deep learning for autonomous driving.

Download or read book Multi sensor Fusion for Autonomous Driving written by Xinyu Zhang and published by Springer Nature. This book was released on with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Multi Agent Reinforcement Learning for Autonomous Driving written by Sushrut Bhalla and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning and back-propagation have been successfully used to perform centralized training with communication protocols among multiple agents in a cooperative Multi-Agent Deep Reinforcement Learning (MARL) environment. In this work, I present techniques for centralized training of MARL agents in large scale environments and compare my work against current state of the art techniques. This work uses model-free Deep Q-Network (DQN) as the baseline model and allows inter agent communication for cooperative policy learning. I present two novel, scalable and centralized MARL training techniques (MA-MeSN, MA-BoN), which are developed under the principle that the behavior policy and message/communication policies have different optimization criteria. Thus, this work presents models which separate the message learning module from the behavior policy learning module. As shown in the experiments, the separation of these modules helps in faster convergence in complex domains like autonomous driving simulators and achieves better results than the current techniques in literature. Subsequently, this work presents two novel techniques for achieving decentralized execution for the communication based cooperative policy. The first technique uses behavior cloning as a method of cloning an expert cooperative policy to a decentralized agent without message sharing. In the second method, the behavior policy is coupled with a memory module which is local to each model. This memory model is used by the independent agents to mimic the communication policies of other agents and thus generate an independent behavior policy. This decentralized approach has minimal effect on degradation of the overall cumulative reward achieved by the centralized policy. Using a fully decentralized approach allows us to address the challenges of noise and communication bottlenecks in real-time communication channels. In this work, I theoretically and empirically compare the centralized and decentralized training algorithms to current research in the field of MARL. As part of this thesis, I also developed a large scale multi-agent testing environment. It is a new OpenAI-Gym environment which can be used for large scale multi-agent research as it simulates multiple autonomous cars driving cooperatively on a highway in the presence of a bad actor. I compare the performance of the centralized algorithms to existing state-of-the-art algorithms, for ex, DIAL and IMS which are based on cumulative reward achieved per episode and other metrics. MA-MeSN and MA-BoN achieve a cumulative reward of at-least 263% higher than the reward achieved by the DIAL and IMS. I also present an ablation study of the scalability of MA-BoN and show that MA-MeSN and MA-BoN algorithms only exhibit a linear increase in inference time and number of trainable parameters compared to quadratic increase for DIAL.

Download or read book Belief State Planning for Autonomous Driving Planning with Interaction Uncertain Prediction and Uncertain Perception written by Hubmann, Constantin and published by KIT Scientific Publishing. This book was released on 2021-09-13 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consider the prediction uncertainty (e.g. different intentions), perception uncertainty (e.g. occlusions) as well as the uncertain interactive behavior of the other agents explicitly. Simulating the most likely future scenarios allows to find an optimal policy online that enables non-conservative planning under uncertainty.

Download or read book Cooperative Multi Agent Systems in Automobiles written by Mirco Hering and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Decentralized Collaborative Perception for Autonomous Vehicles written by Maxime Chaveroche and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, we have been witnesses of accidents involving autonomous vehicles and their lack of sufficient information at the right time. One way to tackle this issue is to benefit from the perception of different view points, namely collaborative perception. We propose here a decentralized collaboration, i.e. peer-to-peer, in which the agents are active in their quest for full perception by asking for specific areas in their surroundings on which they would like to know more. Ultimately, we want to optimize a trade-off between the maximization of knowledge about moving objects and the minimization of the total information received from others, to limit communication costs and message processing time. To this end, we chose to use Dempster-Shafer Theory (DST) in order to identify different types of uncertainties. In particular, DST allows us to distinguish what has never been perceived (out of range or occluded area) -- which is mainly what collaborative perception tries to reduce -- from what is debated among different sources (conflict arising from fusion of sensors or other vehicles perceptions). More generally, DST takes into account the specificity of evidence, meaning that it provides information about the reliability of an agent's belief, which is crucial for safety. DST also features the advantage of easily dealing with data incest with its Cautious fusion rule, which is a problem inherent to the decentralized approach. However, DST comes with high spatial and computational complexities, especially for dealing with data incest in fusion, which limits its usage to random experiments with few possible outcomes. Thus, we first proposed an efficient exact method to compute the decompositions needed for this Cautious fusion, exploiting what we called focal points. Then, we generalized this method to any Möbius transform in any partially ordered set (including all transformations in DST), we found ways to efficiently compute these focal points and we proposed a generalization of the decomposition required by the Cautious fusion. This generalized decomposition allows one to use this Cautious fusion in more cases, in particular cases where an agent has gathered very specific evidence. This enhances both accuracy and computational stability in consecutive fusions. However, algorithms naively based on our formulas would have a higher worst-case complexity than the complexity of the optimal general algorithms commonly employed in DST -- which is already more than exponential. Therefore, we later proposed algorithms with complexities always better than the state of the art, and more general, leveraging properties of distributive lattices. After this work on the fusion process itself, we tackled the issue of redundancy and irrelevance in decentralized collaborative perception. For this, we proposed a way to learn a communication policy that reverses the usual communication paradigm by only requesting from other vehicles what is unknown to the ego-vehicle, instead of filtering on the sender side. We tested three different models to be taken as base for a Deep Reinforcement Learning (DRL) algorithm and compared them to a broadcasting policy and a random policy. More precisely, we slightly modified a state-of-the-art generative model named Temporal Difference VAE (TD-VAE) to make it sequential. We named this variant Sequential TD-VAE (STD-VAE). We also proposed Locally Predictable VAE (LP-VAE), inspired by STD-VAE, designed to enhance its prediction capabilities. We showed that LP-VAE produced better belief states for prediction than STDVAE, both as a standalone model and in the context of DRL. The last model we tested was a simple state-less model (Convolutional VAE). Experiments were conducted in the driving simulator CARLA, with vehicles exchanging parts of semantic grid maps. Policies learned based on LP-VAE featured the best trade-off, as long as future rewards were taken into account.

Download or read book Autonomous Driving written by Markus Maurer and published by Springer. This book was released on 2016-05-21 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all of these topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of “autonomous driving".

Download or read book Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.

Download or read book The Multi Agent Transport Simulation MATSim written by Andreas Horni and published by Ubiquity Press. This book was released on 2016-08-10 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status. The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations. The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core. The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis. Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references. We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.

Download or read book Autonomic Road Transport Support Systems written by Thomas Leo McCluskey and published by Birkhäuser. This book was released on 2016-05-03 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work on Autonomic Road Transport Support (ARTS) presented here aims at meeting the challenge of engineering autonomic behavior in Intelligent Transportation Systems (ITS) by fusing research from the disciplines of traffic engineering and autonomic computing. Ideas and techniques from leading edge artificial intelligence research have been adapted for ITS over the last 30 years. Examples include adaptive control embedded in real time traffic control systems, heuristic algorithms (e.g. in SAT-NAV systems), image processing and computer vision (e.g. in automated surveillance interpretation). Autonomic computing which is inspired from the biological example of the body’s autonomic nervous system is a more recent development. It allows for a more efficient management of heterogeneous distributed computing systems. In the area of computing, autonomic systems are endowed with a number of properties that are generally referred to as self-X properties, including self-configuration, self-healing, self-optimization, self-protection and more generally self-management. Some isolated examples of autonomic properties such as self-adaptation have found their way into ITS technology and have already proved beneficial. This edited volume provides a comprehensive introduction to Autonomic Road Transport Support (ARTS) and describes the development of ARTS systems. It starts out with the visions, opportunities and challenges, then presents the foundations of ARTS and the platforms and methods used and it closes with experiences from real-world applications and prototypes of emerging applications. This makes it suitable for researchers and practitioners in the fields of autonomic computing, traffic and transport management and engineering, AI, and software engineering. Graduate students will benefit from state-of-the-art description, the study of novel methods and the case studies provided.

Download or read book Multi Agent Based Production Planning and Control written by Jie Zhang and published by John Wiley & Sons. This book was released on 2017-08-28 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.

Download or read book Agency Perception and Moral Values Related to Autonomous Weapons written by Ilse Verdiesen and published by BRILL. This book was released on 2021-10-18 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: The deployment of Autonomous Weapons gives rise to ongoing debate in society and at the United Nations, in the context of the Convention on Certain Conventional Weapons. Yet little empirical research has been done on this topic. This volume fills that gap by offering an empirical study based on military personnel and civilians working at the Dutch Ministry of Defence. It yields insight into how Autonomous Weapons are perceived by the military and general public; and which moral values are considered important in relation to their deployment. The research approach used is the Value-Sensitive Design (VSD) method that allows for the consideration of human values throughout the design process of technology. The outcome indicates that military personnel and civilians attribute more agency (the capacity to think and plan) to an Autonomous Weapon than to a Human Operated Drone. In addition, it is clear that common ground exists between military and societal groups in their perception of the values of human dignity and anxiety. These two values arise often in the discourse, and addressing them is essential when considering the ethics of the deployment of Autonomous Weapons. The text of this volume is also offered in parallel French and German translation.

Download or read book Trust in Human Robot Interaction written by Chang S. Nam and published by Academic Press. This book was released on 2020-11-17 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trust in Human-Robot Interaction addresses the gamut of factors that influence trust of robotic systems. The book presents the theory, fundamentals, techniques and diverse applications of the behavioral, cognitive and neural mechanisms of trust in human-robot interaction, covering topics like individual differences, transparency, communication, physical design, privacy and ethics. Presents a repository of the open questions and challenges in trust in HRI Includes contributions from many disciplines participating in HRI research, including psychology, neuroscience, sociology, engineering and computer science Examines human information processing as a foundation for understanding HRI Details the methods and techniques used to test and quantify trust in HRI

Download or read book Applications of Mobile Robots written by and published by BoD – Books on Demand. This book was released on 2019-03-20 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes a selection of research work in the mobile robotics area, where several interesting topics are presented. In this way we find a review of multi-agents, different techniques applied to the navigation systems, artificial intelligence algorithms, which include deep learning applications, systems where a Kalman filter estimator is extended for visual odometry, and finally the design of an on-chip system for the execution of cognitive agents. Additionally, the development of different ideas in mobile robot applications are included and hopefully will be useful and enriching for readers.

Download or read book Smart Transport for Cities and Nations written by Christian Claudel and published by . This book was released on 2018-06-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: