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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dong-Kyoung Kye Seong-Woo Kim Seung-Woo Seo |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea (Dong-Kyoung Kye; Seong-Woo Kim; Seung-Woo Seo) |
| Abstract | As automated vehicles begin operating on complex urban roads, precise decision making for automated driving has been increasingly important for safe automated driving. In particular, decision making at unsignalized intersections is one of the most challenging problems of automated urban driving. This paper presents intention-aware automated driving at unsignalized intersections. The intention of the traffic participant is modeled as a Dynamic Bayesian Network (DBN). Given the inference result, an intention-aware decision-making problem is modeled as a Partially Observable Markov Decision Process (POMDP), which is regarded as one of the most widely used models for sequential decision-making problems under uncertain environments. We implemented the proposed system in a passenger car, and the effectiveness of the proposed algorithm is evaluated through experiments at unsignalized intersections on our university campus road. |
| Starting Page | 522 |
| Ending Page | 525 |
| File Size | 1021228 |
| Page Count | 4 |
| File Format | |
| ISSN | 20937121 |
| e-ISBN | 9788993215083 |
| DOI | 10.1109/ICCAS.2015.7364974 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-13 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Control, Robotics and Systems - ICROS |
| Subject Keyword | Decision making Automated vehicle Dynamic Bayesian Network(DBN) |
| Content Type | Text |
| Resource Type | Article |
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