Open AccessHuman Detection and Avoidance Control Systems of an Autonomous Vehicle
Author(s) -
Taufiq Nuzwir Nizar,
R. W. Tri Hartono,
D. Meidina
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/879/1/012103
Subject(s) - computer science , artificial intelligence , range (aeronautics) , computer vision , collision avoidance , autonomous system (mathematics) , real time computing , human error , simulation , engineering , computer security , aerospace engineering , reliability engineering , collision
A long-range and short-range navigation systems of an autonomous vehicle are the most important thing to develop because it is very complex and related to safety in the driving of an automatic vehicle. The purpose of this research is to develop a short-range navigation system for autonomous vehicles focused to detect and avoid humans which implemented on an autonomous vehicle prototype. Image Processing and deep learning algorithm used for human detection and ultrasonic sensor used for distance calculation. Decision making for human avoidance system using the Fuzzy algorithm based on the position of detected human and human distance. The implemented system has a success rate of 85.71% to avoid human which ideal distance more than 2 meters. The implemented prototype of an autonomous vehicle can be implemented in the real vehicle with some adjustments in the sensor and hardware system, however, the systems are expected to reduce traffic accidents caused by human error.