Abstract

Artificial life (ALife) uses biological knowledge and techniques to help solve different engineering, management, control and computational problems. Natural systems teach us that very simple individual organisms can form systems capable of performing highly complex tasks by dynamically interacting with each other. The main goal of this paper is to show how we can use ALife concepts (inspired by some principles of natural swarm intelligence) when solving complex problems in traffic and transportation. The bee system that represents the new approach in the field of swarm intelligence is described. It is also shown in the paper that ALife approach can be successful to "attack" transportation problems characterized by uncertainty. The fuzzy ant system (FAS) described in the paper represents an attempt to handle the uncertainty that sometimes exists in some complex transportation problems. The potential applications of the bee system and the fuzzy ant system in the field of traffic and transportation engineering are discussed.

Keywords

Artificial lifeComputer scienceSwarm intelligenceField (mathematics)Artificial intelligenceFuzzy logicSwarm roboticsComplex systemSwarm behaviourAdvanced Traffic Management SystemIntelligent transportation systemAnt colonyIntelligent decision support systemAnt colony optimization algorithmsMachine learningEngineeringTransport engineeringMathematics

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Year
2003
Type
article
Citations
131
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Pavle Lučić, Dušan Teodorović (2003). Transportation modeling: an artificial life approach. . https://doi.org/10.1109/tai.2002.1180807

Identifiers

DOI
10.1109/tai.2002.1180807