Name
Title | ||
|---|---|---|
Expandable-Partially Observable Markov Decision-Process Framework for Modeling and Analysis of Autonomous Vehicle Behavior |
Abstract | ||
|---|---|---|
When modeling decision-making in autonomous vehicles (AVs), only a fraction of the required information is usually available at the start due to the presence of uncertainty in the knowledge of the state of the system and the environment. This article presents a probabilistic modeling framework based on a combination of partially observable Markov decision-process (POMDP) models and heuristics. In ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/JSYST.2020.3010473 | IEEE Systems Journal |
Keywords | DocType | Volume |
Planning,Uncertainty,Context modeling,Heuristic algorithms,Decision making,Approximation algorithms,Computational modeling | Journal | 15 |
Issue | ISSN | Citations |
3 | 1932-8184 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Parisa Pouya | 1 | 0 | 0.34 |
| Azad M. Madni | 2 | 188 | 34.57 |