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93
Challenges in Autonomous Vehicle Testing and Validation
"... Abstract Software testing is all too often simply a bug hunt rather than a wellconsidered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V proce ..."
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model for autonomous vehicles: driver out of the loop, complex requirements, non-deterministic algorithms, inductive learning algorithms, and failoperational systems. General solution approaches that seem promising across these different challenge areas include: phased deployment using successively
MACHINE LEARNING SOLUTIONS FOR TRANSPORTATION NETWORKS
, 2008
"... This dissertation was presented by Tomas Singliar.
This thesis brings a collection of novel models and methods that result from a new look at practical problems
in transportation through the prism of newly available sensor data. There are four main contributions:
First, we design a generative proba ..."
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highways enables us to bring supervised learning approaches to incident detection. We show that a support
vector machine learner can outperform manually calibrated solutions. A major hurdle to performance of
supervised learners is the quality of data which contains systematic biases varying from site
Materials for an exploratory theory of the network society.
- The British Journal of Sociology
, 2000
"... ABSTRACT This article aims at proposing some elements for a grounded theor y of the network society. The network society is the social structure characteristic of the Information Age, as tentatively identi ed by empirical, cross-cultural investigation. It permeates most societies in the world, in v ..."
Abstract
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Cited by 122 (0 self)
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-temporal con gurations constitute cultures. They are enacted, reproduced, and ultimately transformed by social actors, rooted in the social structure, yet freely engaging in con ictive social practices, with unpredictable outcomes. A fundamental feature of social structure in the Information Age is its
Computer Vision, Machine Learning, Image Processing, Vehicular Navigation
"... Autonomous vehicle system is a demanding application in our daily lives. With increasing number of road accidents, loss to life and property has increased the demand of autonomous technology in vehicles. The interaction between the driver and system should aid the driving process without interfering ..."
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interfering with safety and ease of vehicle operation. The system must be optimum so that it can come into existence in Real-World. This research focuses on the development of the assistance system where a machine vision system is used as a detector for the automated steering system to extract information.
AC 2007-2226: AN AUTONOMOUS APPROACH TO SAFE MACHINE TOOL OPERATION AND EDUCATION
"... An autonomous approach to safe machine tool operation and education On considering international competitiveness and economic sustainability, the dynamics and complexities of the workplace are more challenging now than ever before. Consequently, a methodical approach to how students learn and constr ..."
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An autonomous approach to safe machine tool operation and education On considering international competitiveness and economic sustainability, the dynamics and complexities of the workplace are more challenging now than ever before. Consequently, a methodical approach to how students learn
A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving
- In Proc. of Conf. on Uncertainty in AI (UAI
, 2006
"... Accurate perception is a principal challenge of autonomous off-road driving. Perceptive technologies generally focus on obstacle avoidance. However, at high speed, terrain roughness is also important to control shock the vehicle experiences. The accuracy required to detect rough terrain is significa ..."
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Cited by 32 (3 self)
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Accurate perception is a principal challenge of autonomous off-road driving. Perceptive technologies generally focus on obstacle avoidance. However, at high speed, terrain roughness is also important to control shock the vehicle experiences. The accuracy required to detect rough terrain
Learning Autonomous Driving Styles and Maneuvers from Expert Demonstration
"... Abstract One of the many challenges in building robust and reliable autonomous systems is the large number of parameters and settings such systems often entail. The traditional approach to this task is simply to have system experts hand tune various parameter settings, and then validate them through ..."
Abstract
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Cited by 1 (0 self)
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through simulation, offline playback, and field testing. However, this approach is tedious and time consuming for the expert, and typically produces subpar performance that does not generalize. Machine learning offers a solution to this problem in the form of learning from demonstration. Rather than ask
Autonomous Learning Objects in a Peer to Peer Cross Institutional Educational Framework
"... Current practice in developing courseware for online learning, differs little from traditional means. When implementing online learning, institutes look for practitioners who can create content. However, the lack of adaptable, computer parseable information exchanges leads to a duplication of effort ..."
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of effort. The solution is twofold, properly describe the ontology of learning objects, expose metadata and content in a service-oriented approach. Learning management can take many leaves from web standards bodies that aid in machine readable content structures. This is more an investigation of relevant
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
, 2003
"... With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed, heterogeneous and autonomous data repositories. In many applications, practical constraints require such systems t ..."
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With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed, heterogeneous and autonomous data repositories. In many applications, practical constraints require such systems
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
- In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS
, 2007
"... Abstract — In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to previous approaches, our method does not require sophisticated handtuned models, but rather learns the policy online ..."
Abstract
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Cited by 13 (4 self)
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-dimensional state-action space that needs to be explored in order to identify the values of all state-action pairs. In this paper, we propose a solution to learning continuous control policies based on the Gaussian process model. In practical experiments carried out on a real robot we demonstrate that the system
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