92,276 research outputs found
Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web
Current âInternet of Thingsâ concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3Câs Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where driversâ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun
Ecological IVIS design : using EID to develop a novel in-vehicle information system
New in-vehicle information systems (IVIS) are emerging which purport to encourage more environment friendly or âgreenâ driving. Meanwhile, wider concerns about road safety and in-car distractions remain. The âFoot-LITEâ project is an effort to balance these issues, aimed at achieving safer and greener driving through real-time driving information, presented via an in-vehicle interface which facilitates the desired behaviours while avoiding negative consequences. One way of achieving this is to use ecological interface design (EID) techniques. This article presents part of the formative human-centred design process for developing the in-car display through a series of rapid prototyping studies comparing EID against conventional interface design principles. We focus primarily on the visual display, although some development of an ecological auditory display is also presented. The results of feedback from potential users as well as subject matter experts are discussed with respect to implications for future interface design in this field
Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance
Due to the current developments towards autonomous driving and vehicle active
safety, there is an increasing necessity for algorithms that are able to
perform complex criticality predictions in real-time. Being able to process
multi-object traffic scenarios aids the implementation of a variety of
automotive applications such as driver assistance systems for collision
prevention and mitigation as well as fall-back systems for autonomous vehicles.
We present a fully model-based algorithm with a parallelizable architecture.
The proposed algorithm can evaluate the criticality of complex, multi-modal
(vehicles and pedestrians) traffic scenarios by simulating millions of
trajectory combinations and detecting collisions between objects. The algorithm
is able to estimate upcoming criticality at very early stages, demonstrating
its potential for vehicle safety-systems and autonomous driving applications.
An implementation on an embedded system in a test vehicle proves in a
prototypical manner the compatibility of the algorithm with the hardware
possibilities of modern cars. For a complex traffic scenario with 11 dynamic
objects, more than 86 million pose combinations are evaluated in 21 ms on the
GPU of a Drive PX~2
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Techno-surveillance of the roads: High impact and low interest
Copyright © 2010 Palgrave Macmillan. This is a post-peer-review, pre-copyedit version of an article published in Crime Prevention and Community Safety. The definitive publisher-authenticated version Crime Prevention and Community Safety 10(1): 1-18 is available online at the link below.Road crashes and road crime are huge international problems produced by global societyâs increasing dependence on motorised transport. To help reduce these crash and crime statistics, roads technology is rapidly developing to prevent the former and deter the latter. This technology largely works by vehicle surveillance, and as with surveillance technology used in other arenas of crime prevention, drawbacks and dangers go along with the safety and security enhancing aspects.
This paper reviews some key emerging roads technologies, the theoretical concerns raised by them and how, through various theoretical frameworks, they could be explored by the discipline of criminology. It urges that the surveillance aspects of road crime prevention and the study of vehicle-related crime more generally would benefit from criminological consideration and be theoretically rewarding. Moreover, in view of the centrality of the roads in contemporary life and the extent of global harm caused there, it contends that criminology should engage with this terrain
Proposal of a risk model for vehicular traffic: A Boltzmann-type kinetic approach
This paper deals with a Boltzmann-type kinetic model describing the interplay
between vehicle dynamics and safety aspects in vehicular traffic. Sticking to
the idea that the macroscopic characteristics of traffic flow, including the
distribution of the driving risk along a road, are ultimately generated by
one-to-one interactions among drivers, the model links the personal (i.e.,
individual) risk to the changes of speeds of single vehicles and implements a
probabilistic description of such microscopic interactions in a Boltzmann-type
collisional operator. By means of suitable statistical moments of the kinetic
distribution function, it is finally possible to recover macroscopic
relationships between the average risk and the road congestion, which show an
interesting and reasonable correlation with the well-known free and congested
phases of the flow of vehicles.Comment: 23 pages, 3 figures, Commun. Math. Sci., 201
Model Predictive Control Based Trajectory Generation for Autonomous Vehicles - An Architectural Approach
Research in the field of automated driving has created promising results in
the last years. Some research groups have shown perception systems which are
able to capture even complicated urban scenarios in great detail. Yet, what is
often missing are general-purpose path- or trajectory planners which are not
designed for a specific purpose. In this paper we look at path- and trajectory
planning from an architectural point of view and show how model predictive
frameworks can contribute to generalized path- and trajectory generation
approaches for generating safe trajectories even in cases of system failures.Comment: Presented at IEEE Intelligent Vehicles Symposium 2017, Los Angeles,
CA, US
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