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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. ...
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Results of AIDE-SPs

Sub-Project 1 (SP1):
Behavioural Effects and Driver-Vehicle-Environment Modelling


Sub-Project 2 (SP2):
Evaluation and Assessment Methodology

Sub-Project 3 (SP3):
Design and Development of and Adaptive Integrated Driver-vehicle Interface


Sub-Project 4 (SP4):
Horizontal Activities

IST

IST-1-507674-IP

Sixth Framework Programme (FP6)

Sixth Framework Programme (FP6)



2.1.2 Review and Taxonomy of IVIS/ADAS 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.
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2.1.3 Considerations on Test Scenarios
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.).
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2.1.4 Specification of AIDE methodology
This deliverable defines the final AIDE methodology for evaluation and assessment of In-Vehicle Information (IVI) and Advanced Driving Assistance (ADA) Systems (IVIS/ADAS).
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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. ...
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2.2.2_1 Visual Demand Measurement 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 userís guide.
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2.2.2_2 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). BAStīs development of EOT was based on the original occlusion technique using occlusion goggles.
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2.2.3 Development of advanced secondary task methodology
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.
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2.2.5 Driving performance assessment methods and metrics
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.
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2.2.6 Subjective assessment methods for workload
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 ...
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2.2.7 Empirical comparison of methods for off-line workload measurement
This deliverable reports the results of an empirical comparison of the offline driver workload and distraction assessment methods developed in AIDE Task 2.2.2 to 2.2.6.
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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:
  1. 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
  2. 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.
  3. 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.




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.
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2.3.2 Risk trade-offs between driving behaviour and driver state
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.
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2.3.3 Combining workload and behavioural effects into overall risk reduction estimate
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.
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2.4.1 Evaluation of the AIDE demonstrators
The three demonstrators developed in AIDE (City Car (SEAT), Luxury Car (CRF) and Heavy Truck (VTEC)) were evaluated in WP2.4. The evaluation was carried out by ...
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List of Deliverables

Del. no. Deliverables name Lead
participant
Dissemination level Delivery date
2.1.1 Review of existing tools and methods CRF PU 08/2004
2.1.2 Review and taxonomy of IVIS/ADAS applications CRF PP + PU summary 08/2004
2.1.3 Considerations on Test Scenarios CRF PU 11/2005
2.1.4 Specification of AIDE methodology BMW PP + PU summary 04/2008
2.2.1 Review of existing Techniques VTEC PU 10/2004
2.2.2_1 Visual Demand Measurement tool development VTEC CO + PU summary 08/2005
2.2.2_2 Driver visual distraction assessment by Enhanced Occlusion Technique (EOT) BASt CO + PU summary 08/2005
2.2.3 Development of advanced secondary task methodology UNIV- LEEDS PU 12/2005
2.2.5 Driving performance assessment methods and metrics VTI PU 12/2005
2.2.6 Subjective assessment methods for workload INRETS PU 12/2005
2.2.7 Empirical comparison of methods for off-line workload measurement DAIMLER PP + PU summary 12/2006
2.3.1 Obtaining the functions describing the relations between behaviour and risk UNIV- LEEDS PU 06/2006
2.3.2 Risk trade-offs between driving behaviour and driver state TNO PU 06/2006
2.3.3 Combining workload and behavioural effects into overall risk reduction estimate HIT PU 12/2006
2.4.1 Evaluation of the AIDE demonstrators VTI PP + PU summary 05/2008


Dissemination level:  Please indicate the dissemination level using one of the following codes:
            PU = Public
            PP = Restricted to other programme participants (including the Commission Services)
            CO = Confidential, only for members of the consortium (including the Commission Services)