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Cognitive Route Search Technique for Self-Driving Vehicles

Cognitive Route Search Technique for Self-Driving Vehicles

Hironori Hiraishi, Fumio Mizoguchi
Copyright: © 2018 |Volume: 12 |Issue: 1 |Pages: 13
ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781522543022|DOI: 10.4018/IJCINI.2018010103
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MLA

Hiraishi, Hironori, and Fumio Mizoguchi. "Cognitive Route Search Technique for Self-Driving Vehicles." IJCINI vol.12, no.1 2018: pp.29-41. http://doi.org/10.4018/IJCINI.2018010103

APA

Hiraishi, H. & Mizoguchi, F. (2018). Cognitive Route Search Technique for Self-Driving Vehicles. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 12(1), 29-41. http://doi.org/10.4018/IJCINI.2018010103

Chicago

Hiraishi, Hironori, and Fumio Mizoguchi. "Cognitive Route Search Technique for Self-Driving Vehicles," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 12, no.1: 29-41. http://doi.org/10.4018/IJCINI.2018010103

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Abstract

This article introduces Time-Constrained Heuristic Search (TCS) as a route search technique that incorporates a cognitive aspect in self-driving vehicles. TCS is a search method using which we can set the time limit to generate a route in advance. The most important feature of TCS is that the node expansion in the latter portion of the journey near the destination tends to be minimized to ensure that the search finishes within the prescribed time limit. TCS conducts a search during the initial portion of the journey that is related to the route the vehicle will move on in the immediate future, but does not take into account the latter portion of the route to a great extent. So, TCS can be regarded as the search technique that selects an option to generate immediate benefit. This characteristic is well-known as the present-oriented bias or the prospect theory in cognitive psychology. Hence, the authors can infer that TCS provides an ability of cognitive judgment to self-driving vehicles.

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