The acceptability of connected and autonomous vehicles is a complex process involving several factors including individual, social, cognitive and perceptive factors, among others. The SUaaVE project has built a model for evaluating emotions in order to integrate the user's emotions and sensations into the behavior of an autonomous vehicle. The basis of this model is a set of rules that determine the emotion that a person is feeling, based on environmental data and data from the individual themself.
Analyzing new on-board and driving assistance systems requires complex and costly tests. The possibility of analyzing the complexity and driver risks associated to the use of these systems from the early stages of the development is key to guarantee safety and lower development costs.
With this purpose, a cognitive model (boxes diagram that represents the thinking process of a person in certain tasks or activities) of a vehicle driver has been developed. The model includes the three different levels of decision required for properly driving: strategic, navigation and control. The model has been implemented as a Discrete Event Model and includes a model of Declarative Memory and a Model for Advanced Workload Analysis. Nowadays, a modified scenario of the Lane Change Test (LCT) has been already implemented and it is about to be validated with real users. In the coming months, the Model should will be able to drive itself the LCT in the simulation platform at Instituto de Biomecánica (IBV), emulating the behavior of real users.
Using Digital Human Models in automotive sector is very popular, especially for impact simulation or to determine reaches and spaces for the driver and the passengers.
Instituto de Biomecánica (IBV) has come up with the initial approach to develope three dimensional digital human models in the driving posture in the framework of a larger project sponsored by the JARI laboratory (Japanese Automotive Research Institute) of Japan, whose objective is to carry out research into the mechanics of whiplash in women, by developing, validating, and using finite element models (FEM) of the human body.
The main contribution of the project has been the development of a methodology to obtain complete and simplified meshes of the human body in the driving posture. It has also been developed a procedure to scan people in the driving posture using a scanner that is specifically configured for the standing posture. The methodology developed opens up a new very promising way to develop extremely lifelike virtual mannequins that represent population groups that have common morphological characteristics.
The complexity of new vehicles, which provide the driver with a high amount of information and the ability of autonomous driving at certain moments or stretches, requires new tools to assess the impact of technology on the driver in very early stages of the development. The objective of the work being developed within the framework of the DIVEO project (project in cooperation IVACE 2016) will make it possible to develop a series of virtual drivers that will be very useful in the analysis of the effect on safety and the driving mode of the new systems that are progressively being incorporated into new car models. The driver cognitive models being developed are software tools that allow for future extensions and modifications, and which enable the analysis of systems that are at an embryonic state.