Autonomous Ground Vehicles—Concepts and a Path to the Future

Luettel, Thorsten; Himmelsbach, Michael; Wuensche, Hans-Joachim

doi:10.1109/jproc.2012.2189803

Cited by 291 publications

(131 citation statements)

References 25 publications

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“…Some of the foundational technologies for these systems are already deployed as part of Advanced driver assistance systems (ADASs) while others are still under development [34]. Of particular note is the possibility for interconnected vehicles, an Internet of Vehicles or a Vehicular Cloud [35].…”

Section: B Autonomous Vehiclesmentioning

confidence: 99%

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

McKee

Clement

Almutairi

et al. 2017

2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS)

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Abstract-The next era of computing is the evolution of the Internet of Things (IoT) and Smart Cities with development of the Internet of Simulation (IoS). The existing technologies of Cloud, Edge, and Fog computing as well as HPC being applied to the domains of Big Data and deep learning are not adequate to handle the scale and complexity of the systems required to facilitate a fully integrated and automated smart city. This integration of existing systems will create an explosion of data streams at a scale not yet experienced. The additional data can be combined with simulations as services (SIMaaS) to provide a shared model of reality across all integrated systems, things, devices, and individuals within the city. There are also numerous challenges in managing the security and safety of the integrated systems. This paper presents an overview of the existing stateof-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. Additionally the key challenges relating to Big Data, a model of reality, augmentation of systems, computation, and security are examined.

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Section: B Autonomous Vehiclesmentioning

confidence: 99%

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

McKee

Clement

Almutairi

et al. 2017

2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS)

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“…Mobile robotic platforms are also of interest in the smart city, the most prominent being driverless vehicles [44], [45], as well as the emerging domain of autonomous passengercarrying aerial vehicles [46]. Though often independent systems, the possibility of interconnecting vehicles together into an Internet of Vehicles or a Vehicular Cloud [47] could allow for the sharing of sensor data and even allow the city systems to perform holistic traffic management.…”

Section: Re-factoring City Architecturementioning

confidence: 99%

Service-Oriented Reference Architecture for Smart Cities

Clement

McKee

2017

2017 IEEE Symposium on Service-Oriented System Engineering (SOSE)

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Abstract-The trend towards turning existing cities into smart cities is growing. Facilitated by advances in computing such as Cloud services and Internet of Things (IoT), smart cities propose to bring integrated, autonomous systems together to improve quality of life for their inhabitants. Systems such as autonomous vehicles, smart grids and intelligent traffic management are in the initial stages of development. However, as of yet there, is no holistic architecture on which to integrate these systems into a smart city. Additionally, the existing systems and infrastructure of cities is extensive and critical to their operation. We cannot simply replace these systems with smarter versions, instead the system intelligence must augment the existing systems. In this paper we propose a service oriented reference architecture for smart cities which can tackle these problems and identify some related open research questions. The abstract architecture encapsulates the way in which different aspects of the service oriented approach span through the layers of existing city infrastructure. Additionally, the extensible provision of services by individual systems allows for the organic growth of the smart city as required.

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“…Nowadays, many acquisition systems carry out a sensor fusion approach, which uses different sensing methods to increase the accuracy of the process. This sensor fusion can be performed at different abstraction levels, for example, sensor raw-data level or features level (for example, detection of the obstacle contour) [7,2]. Sensor fusion can be also applied for indoor navigation [8].…”

Section: Introductionmentioning

confidence: 99%

Environment mapping using a 3D laser scanner for unmanned ground vehicles

Rejas

Sanchez

Glez-de-Rivera

et al. 2015

Microprocessors and Microsystems

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Esta es la versión de autor del artículo publicado en: This is an author produced version of a paper published in: AbstractUnmanned ground vehicles need accurate sensors to detect obstacles and map their surroundings. Laserbased distance sensors offers precise results, but 3D off-the-shelf sensors may be too expensive. This paper presents a 3D sensing system using a 2D laser sensor with a rotation system. Point cloud density analyses are presented in order to achieve the optimal rotation speed depending on the vehicle speed, distance to obstacles, etc. The proposed system is able to generate real-time point clouds, detect obstacles and produce maps, with high accuracy and a reasonable price (less than 5, 000 USD).

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Autonomous Ground Vehicles—Concepts and a Path to the Future

Cited by 291 publications

References 25 publications

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

Service-Oriented Reference Architecture for Smart Cities

Environment mapping using a 3D laser scanner for unmanned ground vehicles

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