Ultrasonic Multi-Sensor Detection Patterns On Autonomous Vehicles Using Data Stream Method

被引:0
作者
Budisusila, Eka Nuryanto [1 ]
Khosyi'in, Muhammad [1 ]
Prasetyowati, Sri Arttini Dwi [2 ]
Suprapto, Bhakti Yudho [3 ]
Nawawi, Zainuddin [3 ]
机构
[1] Univ Sriwijaya, Palembang Leave Univ Islam Sultan Agung, Elect Engn, Semarang, Indonesia
[2] Univ Islam Sultan Agung, Elect Engn, Semarang, Indonesia
[3] Univ Sriwijaya, Elect Engn, Palembang, Indonesia
来源
2021 8TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTERSCIENCE AND INFORMATICS (EECSI) 2021 | 2021年
关键词
Autonomous Vehicle; Ultrasonic Sensors; Multi-sensors; Detection Pattern; Data Stream; SYSTEM;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Autonomous vehicles need sensors to detect the surroundings of the vehicle, especially if there are obstructions that could harm the vehicle or the object itself. The goal is to avoid accidents by detecting as early as possible if there are obstacles. In this study, a series of ultrasonic sensors are used and placed in strategic positions around the vehicle. They are placed in front, in side and in rear of vehicle. When the sensor detects an object, each sensor provides information on the existence of the object in the form of a detection point. These points are still formed as detection points as the results of individual detection from each sensor. In order to integrate all the resulting points, it is necessary to establish a comprehensive detection pattern, to provide information about the safe distance of the vehicle from surrounding objects. The sensors are connected to a programmable microcontroller unit to monitor and control the transmitted signal and sensor detection results. The signal obtained by the microcontroller is fed to the computer unit through the serial port, which is then read using the Data Stream to be displayed on the monitor screen. With this method, the data will be reprocessed to display an integrated detection pattern from all sensors graphically. There are two kinds of graphical pattern formed, spider web pattern and bar pattern.
引用
收藏
页码:144 / 150
页数:7
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