Spatial knowledge acquisition for cognitive maps in autonomous vehicles

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Abstract

Known as maplike representations of the environment, which humans build and store in mind overtime, cognitive maps are an essential element of spatial knowledge that benefit individuals from travel planning to wayfinding. Considering, on one hand, that active interaction with the environment leads to better spatial knowledge acquisition than passive exposure and, on the other, that fully autonomous vehicles will eliminate the need to driving cars, i.e., being only passengers and not drivers, it is of great importance to understand the impact of autonomous vehicles on human cognitive maps. In this paper, we conducted an online survey and analyzed responses from 204 participants to understand this impact. We found a significant interaction effect of the frequencies of driving and riding as passengers on the reported spatial knowledge. Further analysis indicated main effects of riding frequency for frequent drivers and driving frequency among non-frequent passengers. Variations in specific aspects of cognitive maps were also identified, all of which provided preliminary insights into the possible effect of autonomous vehicles on human spatial knowledge.

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APA

Qin, Y., & Karimi, H. A. (2020). Spatial knowledge acquisition for cognitive maps in autonomous vehicles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12187 LNAI, pp. 384–397). Springer. https://doi.org/10.1007/978-3-030-49183-3_30

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