LONG-TERM PREDICTION OF SURROUNDING AGENTS’ MOTION IN AN URBAN ENVIRONMENT FOR SELF-DRIVING VEHICLES

Název práce: Long-term prediction of surrounding agents’ motion in an urban environment for self-driving vehicles
Autor(ka) práce: Biesiedin, Bohdan
Typ práce: Diploma thesis
Vedoucí práce: Potančok, Martin
Oponenti práce: Vencovský, Filip
Jazyk práce: English
Abstrakt:
In the scope of this research, an investigation of the area of self-driving vehicles was done. As a result of the investigation a model which implements long-term prediction of surrounding agents motion in urban environment for self-driving vehicle was implemented. The proposed model is capable of capturing and recognizing the surrounding agents, tracking their motion, memorizing the history of their motion and making prediction about the future movements and maneuvers. The output of the proposed model is a set of trajectories for each of the surrounding vehicles. At the beginning of the research, an investigation of the history and current state of the field was conducted. In the scope of the investigation, appropriate papers, books and articles were studied. In addition, a number of experts in the field of autonomous vehicles and motion prediction were interviewed in order to get more insights about the current state of art and approaches in the field. The results of the first part of research were used in order to design and construct a model which fulfils the main aim of the work. In order to have a clear view on what should be done and how the final solution should look like at the result of the design process, a set of system and functional requirements were proposed and further realized in the design process. The main components of the model were developed and described in the practical part of the work. Flowcharts were used in order to depict algorithms of main components of the model. In conclusion, developed model is performing well for the tested time ranges and bypasses the system created on the basis of the standard model in predicting the trajectories of agents. It can be used as it is in the result of the work or modified for a particular use case and integrated into a control system.
Klíčová slova: Neural Networks; Autonomy; GPS; LIDAR; RADAR; AI; Trajectory; Machine Learning; Agents; Urban Environment; Motion Prediction; Algorithm; Self-Driving Cars; Autonomous Driving; Prediction
Název práce: LONG-TERM PREDICTION OF SURROUNDING AGENTS’ MOTION IN AN URBAN ENVIRONMENT FOR SELF-DRIVING VEHICLES
Autor(ka) práce: Biesiedin, Bohdan
Typ práce: Diplomová práce
Vedoucí práce: Potančok, Martin
Oponenti práce: Vencovský, Filip
Jazyk práce: English
Abstrakt:
In the scope of this research, an investigation of the area of self-driving vehicles was done. As a result of the investigation a model which implements long-term prediction of surrounding agents motion in urban environment for self-driving vehicle was implemented. The proposed model is capable of capturing and recognizing the surrounding agents, tracking their motion, memorizing the history of their motion and making prediction about the future movements and maneuvers. The output of the proposed model is a set of trajectories for each of the surrounding vehicles. At the beginning of the research, an investigation of the history and current state of the field was conducted. In the scope of the investigation, appropriate papers, books and articles were studied. In addition, a number of experts in the field of autonomous vehicles and motion prediction were interviewed in order to get more insights about the current state of art and approaches in the field. The results of the first part of research were used in order to design and construct a model which fulfils the main aim of the work. In order to have a clear view on what should be done and how the final solution should look like at the result of the design process, a set of system and functional requirements were proposed and further realized in the design process. The main components of the model were developed and described in the practical part of the work. Flowcharts were used in order to depict algorithms of main components of the model. In conclusion, developed model is performing well for the tested time ranges and bypasses the system created on the basis of the standard model in predicting the trajectories of agents. It can be used as it is in the result of the work or modified for a particular use case and integrated into a control system.
Klíčová slova: Self-Driving Cars; Autonomy; GPS; LIDAR; RADAR; Autonomous Driving; Neural Networks; Prediction; AI; Trajectory; Machine Learning; Agents; Urban Environment; Motion Prediction; Algorithm

Informace o studiu

Studijní program / obor: Aplikovaná informatika/Information Systems Management
Typ studijního programu: Magisterský studijní program
Přidělovaná hodnost: Ing.
Instituce přidělující hodnost: Vysoká škola ekonomická v Praze
Fakulta: Fakulta informatiky a statistiky
Katedra: Katedra informačních technologií

Informace o odevzdání a obhajobě

Datum zadání práce: 3. 11. 2019
Datum podání práce: 6. 12. 2020
Datum obhajoby: 13. 1. 2021
Identifikátor v systému InSIS: https://insis.vse.cz/zp/71533/podrobnosti

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