Welcome to the National Transport Library Catalogue

Normal view MARC view

Evaluation of path planning and collision avoidance algorithms for autonomous surface vehicles

By: Series: Doctoral theses at NTNU ; 2022:227Publication details: Trondheim : Norges teknisk-naturvitenskapelige universitet. NTNU, 2022Description: 139 sISBN:
  • 9788232653133
Subject(s): Online resources: Notes: Härtill 5 uppsatser Dissertation note: Diss. (sammanfattning) Trondheim : Norges teknisk-naturvitenskapelige universitet, 2022 Abstract: Recently, there has been an increased focus on developing an autonomous shipping technology that is safe, trustworthy, and efficient. Some enablers of this technology are strategies to advance sustainability and reducing CO2 emissions. This is achieved by making ships more efficient, increasing safety and reducing the number of accidents caused by human errors on water, and reducing operational costs. However, there are still many challenges to face before autonomous technology on the water becomes a part of our daily life. A safe and reliable path planning and collision avoidance method is an important component in autonomous shipping and plays a key role in incorporating this technology into our daily lives. Although numerous path planning algorithms for autonomous vessels have been developed, each with its own benefits and limitation, there is no one ultimate path planning and collision avoidance algorithm that is suitable for every vessel, in all water regions and in all scenarios. There is also no unified way of evaluating and comparing these algorithms to find the most suitable one for the chosen use case. In this context, the main purpose of this research is to propose a strategy for a unified evaluation and comparison of path planning and collision avoidance algorithms. To achieve this goal, it is essential to first gain an understanding of path planning and collision avoidance as a part of the autonomous surface vehicle’s guidance, navigation, and control system. There are two main application cases. First, it could be used as an offline benchmarking tool to evaluate and compare the algorithms. Second, it could be used online on an actual vessel to select the safest and most efficient path in the planning phase based on the current situation.
Item type: Dissertation
No physical items for this record

Härtill 5 uppsatser

Diss. (sammanfattning) Trondheim : Norges teknisk-naturvitenskapelige universitet, 2022

Recently, there has been an increased focus on developing an autonomous shipping technology that is safe, trustworthy, and efficient. Some enablers of this technology are strategies to advance sustainability and reducing CO2 emissions. This is achieved by making ships more efficient, increasing safety and reducing the number of accidents caused by human errors on water, and reducing operational costs. However, there are still many challenges to face before autonomous technology on the water becomes a part of our daily life. A safe and reliable path planning and collision avoidance method is an important component in autonomous shipping and plays a key role in incorporating this technology into our daily lives. Although numerous path planning algorithms for autonomous vessels have been developed, each with its own benefits and limitation, there is no one ultimate path planning and collision avoidance algorithm that is suitable for every vessel, in all water regions and in all scenarios. There is also no unified way of evaluating and comparing these algorithms to find the most suitable one for the chosen use case. In this context, the main purpose of this research is to propose a strategy for a unified evaluation and comparison of path planning and collision avoidance algorithms. To achieve this goal, it is essential to first gain an understanding of path planning and collision avoidance as a part of the autonomous surface vehicle’s guidance, navigation, and control system. There are two main application cases. First, it could be used as an offline benchmarking tool to evaluate and compare the algorithms. Second, it could be used online on an actual vessel to select the safest and most efficient path in the planning phase based on the current situation.