Current Issue
Romanian Journal of Information Technology and Automatic Control / Vol. 34, No. 4, 2024
Optimising itinerary generation for autonomous tour guides by integrating real time data into genetic algorithms
Cristian SANDU, Luminița DUMITRIU, Ioan ȘUȘNEA
Research in the field of autonomous vehicles has made good progress in the last years, but mass adoption is unlikely to happen very soon due to, in most part, important ethical and security concerns. The authors consider that niche uses of autonomous vehicles are more likely to be researched and developed, since they can substantially make an immediate difference in specific applications. In this paper we analyse and propose a novel genetic algorithm-based dynamic itinerary generation mechanism for use in autonomous tour guides, with the goal of achieving the highest amount of itinerary point visits in the given timeframe. It does that by taking into account the available time and the tour points that are defined as most important by the tourist, through a ranking system and by integrating real time data, such as traffic conditions. By autonomous tour guide we refer to any vehicle capable of autonomously carrying a tourist or group of tourists. The algorithm proves to be reliable and fast enough to allow for dynamic reconfiguration of the itinerary.
Keywords:
Genetic Algorithms, Autonomous Tour Guides, Autonomous Vehicles, Smart Tourism, Route Planning, Artificial Intelligence.
CITE THIS PAPER AS:
Cristian SANDU,
Luminița DUMITRIU,
Ioan ȘUȘNEA,
"Optimising itinerary generation for autonomous tour guides by integrating real time data into genetic algorithms",
Romanian Journal of Information Technology and Automatic Control,
ISSN 1220-1758,
vol. 34(4),
pp. 115-126,
2024.
https://doi.org/10.33436/v34i4y202409