Skripsi

OPTIMISASI PERENCANAAN RUTE KENDARAAN LISTRIK OTONOM MENGGUNAKAN ALGORITMA ANT COLONY OPTIMIZATION DI KAMPUS UNSRI INDRALAYA

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Penilaian

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Autonomous vehicles are an innovation of vehicles that are able to operate themselves without human intervention. One of the most important aspects of research in the field of autonomous vehicles is route planning. This research aims to build the closest route planning system using ant colony optimization algorithm. This research begins by collecting coordinate data through the google maps application. Next, the simulation route design is carried out and the distance between nodes is calculated using the euclidean distance equation. The average difference from the calculation with the euclidean distance equation compared to the google maps API is 0.97 meters while with the google maps application is 1.60 meters. Testing the ACO algorithm applied in the grid base includes testing with different iterations and with the same iteration. From testing with different iterations, it can be seen that at low iterations the ACO algorithm has not been able to determine the optimal route in some cases of the destination route. While in testing with the same iteration it can be seen that the average result of the difference in distance from the ACO algorithm for all possible routes that can be formed is 5.82 meters. The conclusion of this research is that the ACO algorithm can be implemented and works well as the closest route determinant in autonomous electric vehicles.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407004368	T151068	T1510682024	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1510682024

Publisher

Indralaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya., 2024

Collation

xvii, 128 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.670 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Elektro
Path Planning

Specific Detail Info

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Statement of Responsibility

KA

Other version/related

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