1,721,001 research outputs found
D4.4 A flexible driver-machine interface for real-time warning interventions Safe tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions
No full textD8.2 Exploitation Plans Safe tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions
No full textThe i-DREAMS project, a Research and Innovation Action, aims not only to advance state-ofthe-art of scientific knowledge but also to create exploitable outcomes for societal and
economic benefit. The goal of this exploitation plan deliverable is to develop a roadmap to
market for the technology platform developed within the project.
The deliverable describes the different activities to understand market needs, identify unique
contributions of i-DREAMS compared to existing market leaders, develop business cases, and
explore the legal, ethical and administrative aspects of how consortium partners will pursue
economic valorisation after the project concludes.
The telematics market is projected to have strong demand in the coming years, with increasing
attention on driver safety. The outstanding advantages of the i-DREAMS solution are its
comprehensive range of safety indicators and its holistic approach to monitoring driver
behaviors and determining if drivers are operating within safe boundaries. The i-DREAMS
platform integrates various factors, including driver background, real-time risk indicators, driver
state, driving task complexity, and coping capacity, into a comprehensive framework for
continuous assessment and intervention, both in-vehicle and post-trip. Potential customers
who could benefit from the i-DREAMS solutions include private drivers, professional
transportation companies (for cars, buses, and trucks), insurance companies that focus on
usage-based insurance, and coaching companies.
The activities undertaken in the deliverable involve market outlook analysis, competitor
analysis, benchmark analysis, business plan modeling, and legal and contractual analysis.
Finally, a demoproject was conducted to test the i-DREAMS solution in the market with real
users. The demoproject was aimed at validating the effectiveness of the i-DREAMS solution
and its potential to create value for customers. The outcomes of the demoproject are used to
refine the i-DREAMS solution and enhance its commercialization in the future
D4.4 A flexible driver-machine interface for real-time warning interventions Safe tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions
No full textThe effectiveness of an intelligent speed assistance system with real-time speeding interventions for truck drivers: a Belgian simulator study
No full textSpeeding is one of the leading risk factors in road safety. Not only is it one of the leading causes of accidents, it also has an extensive effect on the impact and consequences of accidents. This is especially the case for trucks, where the enforced speed limit is often dependent on local legislation and context rather than speed limit traffic signs. This study is part of the greater i-DREAMS project and aims to explore the effectiveness of an intelligent speed assistance system for truck drivers. To achieve this, a simulator experiment was performed with 34 professional truck drivers in Belgium. Participants first made a baseline drive followed by two drives, where they received visual information about the enforced speed limit, but also visual and auditory warnings when exceeding the speed limit. The drives included different road environments with different speed limits. The results reveal a significant reduction of relevant parameters (i.e. average speed, minimum speed, maximum speed, and percentage of distance above the speed limit) when drivers received information and warnings about speeding while driving on a rural 1x1 road with a speed limit of 70 km/h (60 km/h for trucks). Further research is needed to validate this effect on other road types.This research was funded by the European Union’s Horizon 2020 research innovation program as part of the project i-DREAMS (grant agreement No 814761)
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
D4.1 A set of flexible modules for sensor data collection, integration and real-time processing Safe tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions
No full textThe i-DREAMS project aims at setting up a framework for the definition, development, testing
and validation of a context-aware safety envelope for driving, called the ‘Safety Tolerance
Zone’ (STZ). To accomplish this task, vehicles will have to be equipped with a suite of
integrated technologies, applicable to modes of transport with different operational contexts,
namely cars, heavy vehicles (buses and trucks), and rail transport (trains and trams).
This deliverable describes the in-vehicle sensor technologies, that monitor the context, the
operator, the vehicle and estimates the task complexity and coping capacity, and the system
that will aggregate all the information and perform the real-time processing necessary to trigger
the interventions to keep drivers in a safe driving zone.
The central element of this platform is CardioGateway, an edge computing device with multiple
communication interfaces and computing power for real-time processing of the data. The
sensors that were selected are associated with each of monitoring the perspectives: a) driver
state, b) driving task complexity, and c) driving performance.
For the driver monitoring, two physiological sensor alternatives were considered: a steering
wheel cover that acquires the ECG (CardioWheel), or a wearable, that acquires the PPG
(PulseOn). For vehicle monitoring, and to allow compatibility between modes, CardioGW
acquires inertial information and GPS. For trucks and buses, it also reads the FMS CAN
information. The contextual information is obtained using Mobileye and a dash camera
(CardioDashcam).
The system includes a driver identification module to keep track of the identity of the drivers,
which is especially relevant on vehicles with multiple drivers. It uses the intervention device as
input, or in the case of professional vehicles, the FMS interface.
The data upload is performed via 4G or Wi-Fi internet connection, allowing the synchronization
of a local database with the cloud’s API.
Several mechanisms and tools have been implemented to help verify the correct installation
and functioning of the system, including a back-office platform and an Android application. The
application is also used to document the installation procedure allowing to store evidence that
the system was correctly installed and the vehicles were intact after the procedure
D4.1 A set of flexible modules for sensor data collection, integration and real-time processing Safe tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions
No full textThe i-DREAMS project aims at setting up a framework for the definition, development, testing
and validation of a context-aware safety envelope for driving, called the ‘Safety Tolerance
Zone’ (STZ). To accomplish this task, vehicles will have to be equipped with a suite of
integrated technologies, applicable to modes of transport with different operational contexts,
namely cars, heavy vehicles (buses and trucks), and rail transport (trains and trams).
This deliverable describes the in-vehicle sensor technologies, that monitor the context, the
operator, the vehicle and estimates the task complexity and coping capacity, and the system
that will aggregate all the information and perform the real-time processing necessary to trigger
the interventions to keep drivers in a safe driving zone.
The central element of this platform is CardioGateway, an edge computing device with multiple
communication interfaces and computing power for real-time processing of the data. The
sensors that were selected are associated with each of monitoring the perspectives: a) driver
state, b) driving task complexity, and c) driving performance.
For the driver monitoring, two physiological sensor alternatives were considered: a steering
wheel cover that acquires the ECG (CardioWheel), or a wearable, that acquires the PPG
(PulseOn). For vehicle monitoring, and to allow compatibility between modes, CardioGW
acquires inertial information and GPS. For trucks and buses, it also reads the FMS CAN
information. The contextual information is obtained using Mobileye and a dash camera
(CardioDashcam).
The system includes a driver identification module to keep track of the identity of the drivers,
which is especially relevant on vehicles with multiple drivers. It uses the intervention device as
input, or in the case of professional vehicles, the FMS interface.
The data upload is performed via 4G or Wi-Fi internet connection, allowing the synchronization
of a local database with the cloud’s API.
Several mechanisms and tools have been implemented to help verify the correct installation
and functioning of the system, including a back-office platform and an Android application. The
application is also used to document the installation procedure allowing to store evidence that
the system was correctly installed and the vehicles were intact after the procedure
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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