平面图(考古学)
计算机科学
职位(财务)
组分(热力学)
城市化
人口
人工智能
模拟
实时计算
运输工程
工程类
业务
生态学
地理
物理
人口学
考古
财务
社会学
生物
热力学
作者
Tolga Kayın,Çağatay Berke Erdaş
出处
期刊:Communications Faculty of Sciences University of Ankara. Series A2-A3: physics, engineerigng physics, electronic engineering and astronomy
[Ankara Avrupa Calismalari Dergisi]
日期:2024-02-28
卷期号:66 (1): 1-25
标识
DOI:10.33769/aupse.1292652
摘要
In the world where urbanization and population density are increasing, transportation methods are also diversifying and the use of unmanned vehicles is becoming widespread. In order for unmanned vehicles to perform their tasks autonomously, they need to be able to perceive their own position, the environment and predict the possible movements/routes of environmental factors, similar to living things. In autonomous vehicles, it is extremely important for the safety of the vehicle and the surrounding factors to be able to predict the future position of the objects around it with high performance so that the vehicle can plan correctly. Due to the stated reasons, the behavioral prediction module is a very important component for autonomous vehicles, especially in moving environments. In this study, fast and successful robotic behavioral prediction module has been developed to enable the autonomous vehicle to plan more safely and successfully.
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