Human factors studies are becoming more and more crucial in the automotive sector due to the need to evaluate the driver.s reactions to the increasingly sophisticated driving-assistant technologies. Driving simulators allow performing this kind of study in a controlled and safe environment. However, the driving simulation.s Level of Detail (LOD) can affect the users. perception of driving scenarios and make an experimental campaign.s outcomes unreliable. This paper proposes a study investigating possible correlations between driver.s behaviors and emotions, and simulated driving scenarios. Four scenarios replicating the same real area were built with four LODs from LOD0 (only the road is drawn) to LOD3 (all buildings with real textures for facades and roofs are inserted together with items visible from the road). 32 participants drove in all the four scenarios on a fixed-base driving simulator; their performance relating to the vehicle control (i.e., speed, trajectory, brake and gas pedal use, and steering wheel), their physiological data (electrodermal activity, and eye movements), their subjective perceptions, opinions and emotional state were measured. The results showed that drivers. behavior changes in a very complex way. Geometrical features of the route and environmental elements constrain much more driving behavior than LOD does Emotions are not affected by LODs. Generally, different signals showed different correlations with the LOD level, suggesting that future studies should consider their measures while modeling the virtual scenario. It is hypothesized that scenario realism is more relevant during leisurely environmental interaction, whilst simulator fidelity is crucial in task-driven interactions.
Combining on-site and off-site analysis: towards a new paradigm for cultural heritage surveys
In recent decades, cultural heritage survey practices have significantly evolved due to the increasing use of digitization tools providing quick and easy access to faithful copies of study objects. While these digital data have clear advantages, especially in terms of geometric characterization, they also introduce a paradigm shift by outsourcing ex situ most of the analysis activities. This break between real and virtual working environments now raises new issues, both in terms of data dispersion and knowledge correlation in multidisciplinary teams. Benefiting from the fields of information systems and augmented reality, we proposed an integrated approach allowing the fusion of geometric, visual and semantic features in a single platform. Today, this proof of concept leads to new perspectives for the production of semantically enriched digital data. In this paper, we intend to explore the different possibilities in terms of implementation and their benefits for cultural heritage survey.
Versioning Virtual Reconstruction Hypotheses: Revealing Counterfactual Trajectories of the Fallen Voussoirs of Notre-Dame de Paris using Reasoning and 2D/3D Visualization
Virtual reconstruction should move beyond merely presenting 3D models by documenting the scientific context and reasoning underlying the reconstruction process. For instance, the collapsed arch in the nave of Notre-Dame de Paris serves as a case study to make explicit the reconstruction argumentation encapsulated in relation to the spatial configuration of the arch and the voussoirs. The experiment is twofold: (1) setting up of the 3D dataset where the hypotheses are modeled as versions using logic programming, and (2) evaluating the scientific narrative of reconstruction through both a custom 2D-3D visualization and competency questions on the enriched 3D data. Formalization, reasoning, and visualization are combined to explore the nonlinear scientific hypotheses and narrative of the reconstruction. The results explicitly show both the factual information on the physical and digital objects, as well as the counterfactual propositions allowing the reasoning at play in the reconstruction. The hypotheses are visualized as counterfactual trajectories creating an open dynamic visualization that makes possible the spatialized querying of conflicting interpretations and embedded memory in place.