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IDENTIFIKASI JALAN SEBAGAI INPUT SISTEM KENDALI KEMUDI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN) PADA AUTONOMOUS ELECTRIC VEHICLE

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Developments in the field of computer vision and robotics continue to be encouraged, especially autonomous electric vehicles to overcome traffic accidents due to human error. Currently, the method used is not real-time. So, in this study, an autonomous electric vehicle to be able to follow a predetermined route by identifying the road using the Convolutional Neural Network (CNN) as an input to the steering control system. The training model applied in this test uses the Stochastic Gradient Descent 150 epoch optimizer because it has a smaller loss value of 0.6133 and has a higher accuracy rate of 0.7743 when compared to the training model using the Adam optimizer. Testing using the model is carried out in 2 tests, namely simulation testing and real-time testing. In simulation testing, from 15 trials conducted, the percentage of success was 93.333%, with only one class classification error and 100% success rate for testing data transmission from the system to the tool while in real-time testing, the autonomous electric vehicle managed to follow a predetermined route accurately. However, the autonomous electric vehicle has not succeeded in avoiding the object in front of it due to the lack of precise steering mechanics and also the lack of variation in training data from various conditions that may be passed by the autonomous electric vehicle.

Availability
Inventory Code Barcode Call Number Location Status
2107002871T51100T511002021Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T511002021
Publisher
Inderalaya : Jurusan Teknik Elektro, Fakultas Teknik Universitas Sriwijaya.,
Collation
xiv, 52 hlm,: ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
621.319 07
Content Type
Text
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
sistem transmisi
Jurusan Teknik Elektro
Specific Detail Info
-
Statement of Responsibility
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No other version available

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