Multi-Agents Trajectory Prediction for Autonomous Vehicles with Multi-Modal Predictions.
| dc.contributor.advisor | Almusawi, Husam | |
| dc.contributor.author | Alghazawi, Mohammad | |
| dc.contributor.department | DE--Műszaki Kar | |
| dc.date.accessioned | 2025-09-04T16:40:11Z | |
| dc.date.available | 2025-09-04T16:40:11Z | |
| dc.date.created | 2024 | |
| dc.description.abstract | 1. A comprehensive model to predict the motion of multi-agents on the road. 2. The model is designed to capture social interactions between agents, without relying on the map information. 3. Each actor is encoded by a Temporal Convolutional Network (TCN) to capture temporal interactions. 4. Applies a graph convolution method and combines it with multi-head self-attention. 5. Apply multi-modal predictions to determine the probability of each individual mode. | |
| dc.description.course | Mechatronical Engineering | en |
| dc.description.degree | MSc/MA | |
| dc.format.extent | 76 | |
| dc.identifier.uri | https://hdl.handle.net/2437/397321 | |
| dc.language.iso | en | |
| dc.rights.access | Hozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében. | |
| dc.subject | Autonomous Driving, Motion Prediction, Temporal Convolutional Network (TCN), Multi-Agents, Multi-Modal. | |
| dc.subject.dspace | Engineering Sciences | |
| dc.title | Multi-Agents Trajectory Prediction for Autonomous Vehicles with Multi-Modal Predictions. |
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