Risk-Aware Neural Navigation for Interactive Driving
Safety has been a key goal for autonomous driving since its inception, and we believe recognizing and responding to risk is a key component of safety. In this work, we aim to answer the question, "How can explainable risk representations be used to produce accurate and safe trajectories?"....
Yazar: | Jiwani, Suzanna |
---|---|
Diğer Yazarlar: | Rus, Daniela |
Materyal Türü: | Tez |
Baskı/Yayın Bilgisi: |
Massachusetts Institute of Technology
2023
|
Online Erişim: | https://hdl.handle.net/1721.1/150311 |
Benzer Materyaller
-
Data driven interaction-aware trajectory prediction for urban driving
Yazar:: Hu, Zongyao
Baskı/Yayın Bilgisi: (2023) -
Online risk-aware conditional planning with qualitative autonomous driving applications
Yazar:: Deyo, Matthew Quinn
Baskı/Yayın Bilgisi: (2018) -
Human-aware navigation system for assistive wheelchair
Yazar:: Chan, Maximilian Jun Feng
Baskı/Yayın Bilgisi: (2023) -
Visibility-Aware Navigation Among Movable
Obstacles
Yazar:: Muguira Iturralde, Jose
Baskı/Yayın Bilgisi: (2023) -
Human-aware robot navigation for assistive wheelchair
Yazar:: Yeoh, Yong Shan
Baskı/Yayın Bilgisi: (2022)