Updated methodology for advance technology acquisition
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The deliverable will focus on advanced acquisition that collect enough information to address multiple and acquired by partners during the project to supply useful data sets for other work packages.It will also provide detailed on common partner installations that will acquire data during the project.Task involved: 2.3
Stratification of population according to driving styles
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The Deliverable consists of the description of types of driver reaction patterns based on the observation and analysis of a driver survey conducted in T1.2. It contains a description of the collected data and analysis method as well as brief profiles of the driving types.Task involved: T1.2.
Criteria definition for the selection of Safety Tests
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Here the scope of deliverable is to identify a set of scenarios that can be used to validate a humanized driving approach form the safety point of vuiew. An expected outcome is a document containing scenario selection criteria, scenario description and rationalsTask related T5.1.
Report on dissemination, communication activities, and materials (I)
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Summary of the D&C activities including and assessment of the outcomes.Task involved: T6.3.
Influencing the parameters that determine driving and outputs of the model
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This deliverable will contain the state of the art on the factors (i.e. situational, personal) that influence driving and how they will be taken into account for the development of the DBM.Task involved: 1.3
Use cases for the identification of the model
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This deliverable will present the methodology to select use cases and their associated scenarios for building DBM. It will contain the selected use cases and scenarios. Task involved: 1.1
Identification of the vehicle parameters concerning the driver modelling approach
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This deliverable will consider major modeling factors such as speed, distance from the vehicle in front, and reaction time according to the distance to the vehicle in front should be considered in various road driving conditions. In particular, it is necessary to ensure safety when changing lanes for automated driving. Nonetheless, the main indicators will be identified and adjusted to prevent a collision on within signalized intersection, whether the acceleration or deceleration can be safely adjusted like a human driver. Key indicators include whether it is possible to safely prevent collisions when changing lanes. Related task: T1.4.
Updated methodology for basic simulation environment
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The deliverable will focus on simulation acquisition that mixed a sufficient set of signals defined in the D2.1 and acquired by partners during the project, to supply mandated data sets for other project tasks.It will also provide detailed on common partner installations that will acquire data during the project.Task involved: 2.2
Definition of the model framework and its individual modules
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Framework defining the driver model and integration of the perceptual, risk Awareness, decision-making affective and motor modules and definition of the outputs in relation with the vehicle response concerning drivers’ perception and reaction. This deliverable will be developed during the first 6 months of T1.5 and it will be the basis for model specifications in coordination with T1.1,T1.2,T1.3 and T1.4.Related tasks: T1.1,T1.2,T1.3, T1.4. and T1.5.
Updated methodology for real field of tests
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The aim of this deliverable is to describe the defined methodology to perform FOTs with the target of collecting the different requirements necessary for each aspect of the human driver modelling. The used acquisition equipment, defined users´ profiles or extracted signals to get the required information will be a clear indicator of the target fulfilling.The content will be based on the FOTs performed in task T2.4.Task related: T2.4.
