Experience-Based Approach for Cognitive Vehicle Research

Experience-Based Approach for Cognitive Vehicle Research

Hironori Hiraishi
Copyright: © 2020 |Pages: 11
DOI: 10.4018/IJSSCI.2020100104
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Abstract

This study discusses an experience-based approach to cognitive vehicle research. The author recruited six subjects who have different individual driving experiences and skills. This paper made them drive their own cars on the same test course. This research collected the drivers' mental status and operations as the driving data using a simple brainwave sensor and the acceleration sensor of a smart phone. The authors analyzed the data and developed models using the cognitive qualitative analysis and modeling tool (QCAM) that the authors have developed. The authors experimentally verified how different the results of the analysis and modeling were. The experiment results identified a parameter that indicated the degree of experience and skill of each driver. Moreover, the models derived the rules that explain the experience of each driver. The experience-based approach enables an understanding of unconscious operations and situated cognition based on the drivers' experiences, and it also allows novice or senior drivers to record their driving experiences and watch them later to maintain their driving skills.
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2. The Cognitve Qualitative Analysis And Modeling Tool

The input data to QCAM are movie data and time sequence sensor data. After QCAM starts, the movie window appears, as shown in Figure 1 (upper left). We can play the movie by using the seven buttons at the bottom of the window, and we can seek through the movie by using the scroll bars. We can check the current time, frame number of the movie, and data number of the sensor data on the movie window.

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