Master'sOpen Access

End-to-end, real time and robust behavioral prediction module with robot operating system for autonomous vehicles

2023
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Advisor: Dr. Öğr. Üyesi Çağatay Berke Erdaş

Abstract (EN)

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 forecast the probable future location of the objects around it with high performance so that the vehicle can plan itself 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, a robotic behavioral prediction module has been developed to enable the autonomous vehicle to plan more safely and successfully. Data has been collected by driving with an autonomous vehicle, and the developed module has been tested. The relevant module has been integrated into the ongoing autonomy project. The proposed method has been observed to operate accurately and fast within up to three seconds.

Author

Dr. Tolga Kayın

How to Cite

Tolga Kayın (Master Thesis). End-to-end, real time and robust behavioral prediction module with robot operating system for autonomous vehicles, 2023, Başkent University.

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