Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 선우명호 | - |
dc.date.accessioned | 2019-12-08T19:50:09Z | - |
dc.date.available | 2019-12-08T19:50:09Z | - |
dc.date.issued | 2018-08 | - |
dc.identifier.citation | ROBOTICS AND AUTONOMOUS SYSTEMS, v. 106, page. 179-191 | en_US |
dc.identifier.issn | 0921-8890 | - |
dc.identifier.issn | 1872-793X | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0921889017308746?via%3Dihub | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/119766 | - |
dc.description.abstract | A perception system based on vehicle detection sensors, which are mounted on an ego vehicle, has restricted visibility because of blockage by obstacles. Estimating the risk of collision with moving vehicles in an occluded area is difficult because their locations and speeds cannot be detected. To address the occlusion problem, this paper proposes a probabilistic collision risk assessment method for a potential collision vehicle in an occluded area. The proposed method estimates the collision risk in three steps: occlusion boundary modeling of perception, motion prediction of the potential collision vehicles, and probabilistic collision risk assessment. The first step models the occlusion boundary to classify the free space and the unknown region. In the second step, the moving path of each potential collision vehicle is predicted considering its future behavior. The final step estimates the collision probability with a potential collision vehicle based on the speed distribution of the vehicles on the road. We evaluate the proposed probabilistic collision risk assessment method in several occlusion scenarios with real traffic, including an alleyway, a merging lane, and blockage by a bulky vehicle. (C) 2018 Elsevier B.V. All rights reserved. | en_US |
dc.description.sponsorship | This work was financially supported by the BK21 plus program (22A20130000045) under the Ministry of Education, Republic of Korea, the Industrial Strategy Technology Development Program (No. 10039673,10060068, 10042633, 10079961,10080284), the International Collaborative Research and Development Program (N0001992) under the Ministry of Trade, Industry and Energy (MOTIE Korea), and National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (No. 2011-0017495). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | ELSEVIER SCIENCE BV | en_US |
dc.subject | Roadway geometry model | en_US |
dc.subject | Occluded vehicle | en_US |
dc.subject | Vehicle maneuver | en_US |
dc.subject | Collision risk assessment | en_US |
dc.subject | Probabilistic speed modeling | en_US |
dc.title | Collision risk assessment of occluded vehicle based on the motion predictions using the precise road map | en_US |
dc.type | Article | en_US |
dc.relation.volume | 106 | - |
dc.identifier.doi | 10.1016/j.robot.2018.05.005 | - |
dc.relation.page | 179-191 | - |
dc.relation.journal | ROBOTICS AND AUTONOMOUS SYSTEMS | - |
dc.contributor.googleauthor | Lee, Minchul | - |
dc.contributor.googleauthor | Sunwoo, Myoungho | - |
dc.contributor.googleauthor | Jo, Kichun | - |
dc.relation.code | 2018012025 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF AUTOMOTIVE ENGINEERING | - |
dc.identifier.pid | msunwoo | - |
dc.identifier.orcid | https://orcid.org/0000-0002-3505-6675 | - |
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