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2.1.1 Review of existing tools and methods The present deliverable represents the first phase of AIDE Subproject 2. The principal goal of the Subproject is to develop a cost efficient and industrially applicable methodology for quantifying behavioural effects of IVIS and ADAS functions, and their relation to road safety. ... download deliverable [pdf file 657 kB]
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2.1.2 Review and of IVIS/ADA taxonomy applications This deliverable aims to perform a review and taxonomy of IVIS/ADAS applications under the AIDE SP2. The survey and taxonomy includes applications available in the market, prototypes, state of the art or under development. download summary [pdf file 74 kB] |
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2.1.3 Scenario Descriptions The main objective of this document is to present a review of issues relevant to the field of testing environments (scenarios, simulators and/or driving environments, cohorts, use cases, etc.). download deliverable [pdf file 651 kB] |
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2.2.1 Review of existing Techniques This report presents a review of existing methods and tools which are relevant to the offline assessment of driver workload and distraction during use of IVIS and ADAS. The deliverable should be seen as a complement to D2.1.1 produced in AIDE WP2.1 where D2.1.1 cover a wider range of assessment methods for both safety and usability evaluations of IVIS while D2.2.1 focuses on a more detailed review of existing general offline measurement techniques. ... download deliverable [pdf file 846 kB]
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2.2.2 Visual Demand Measurement (VDM) tool development The current report aims to give the reader a description of the development of the Visual Demand Measurement (VDM) tool as well as a specification of the actual tool followed by a user’s guide. The report should be seen as an addition to the actual software which is the main outcome from this task. download summary [pdf file 478 kB] |

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2.2.2b Driver visual distraction assessment by
Enhanced Occlusion Technique (EOT) This report presents the results of an experiment conducted at BASt, which was designed to examine the suitability of the Enhanced Occlusion Technique (EOT). BASt´s development of EOT was based on the original occlusion technique using occlusion goggles. download summary [pdf file 70 kB] |

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2.2.3 Potential of advanced secondary task methodology for driver assessment This report presents the results of three experiments conducted at Volvo Technology, PSA and Leeds University, which were designed to examine the suitability of a series of detection tasks for the safety assessment of IVIS and ADAS. download deliverable [pdf file 684 kB] |

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2.2.5 Using performance indicators for driver state assessment This deliverable is based on the work performed in T2.2.5. It is a continuation of the work initiated and reported in D2.2.1 (Johansson et al., 2004) on driver performance methods and metrics. download deliverable [pdf file 4.7 mB] |

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2.2.6 Subjective workload assessment methods This report presents a state of the art on subjective methods used to evaluate workload and results of three experiments the purpose of which is to evaluate the sensitivity, the advantages, the drawbacks and the limits of three existing tools ... download deliverable [pdf file 3.4 mB] |

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2.3 Estimating the risk reduction potential of integrated adaptive HMI
Driver state, driver behavior, and accident risk: how to get a hold on them? A major issue in SP 2 is how we can 'translate' the effects that we usually measure in behavioral studies evaluating driver support systems into estimates of (reductions in) accident risk. Thus, we should be able to answer questions like:- What does it imply for accident risk if a driver reduces his speed by 2 km/h, while at the same time increasing the variability at which he maintains his speed by 3 km/h?
- Is it more risky to drive fully alert at 120 km/h than in a drowsy state at 80 km/h?
The second question, in particular, is hard to answer because it involves a trade-off between an invisible condition (driver state) and some observable behavior, which together supposedly produce a certain accident risk. Nevertheless, the recent Deliverable D 2.3.2, by Janssen, Brouwer and Huang, has tried to solve exactly this problem. After considering the available evidence the following rules-of-thumb are proposed:- If a certain workload is added to an existing baseline by an extra task a driver has to do:
- double the existing risk if that extra workload is at a medium level; and
- triple the risk if that extra workload is high
- If a driver's level of awareness (i.e., alertness) changes because of the interaction with a system:
- double the existing risk if awareness drops from 'excellent ' to 'poor', and halve it the other way round.
- These driver state effects are then to be added or subtracted from the effects associated with the purely behavioral changes, so as to produce a final estimate. These behavior-risk functions have been collected in another Deliverable (D 2.3.1, by Jamson et al.)
This is the way we propose to deal with driver state/driver behaviour interactions and their ultimate effect on accident risk in the AIDE evaluation methodology.
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2.3.1 Obtaining the functions describing the relations between behaviour and risk This report attempts to identify the relationships between driving behaviour and accident risk. First, a review of existing research knowledge will be provided as it is necessary to identify driving parameters that can formulate a risk assessment. download deliverable [pdf file 805 kB]
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2.3.2 Describing the trade-offs between behavior and risk This Deliverable deals with the problem of how to get to an estimate of accident risk that incorporates both driver state (e.g., his momentary workload level or level of alertness) and his driving performance as expressed in commonly used parameters like speed and lane positioning accuracy. download summary [pdf file 151 kB]
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2.3.3 Estimation of overall risk effects The aim of Task 2.3.3 of AIDE project is to translate the combined behavioural effects into risk (reduction) estimates associated with IVIS and ADAS systems. download deliverable [pdf file 189 kB]
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List of Deliverables
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