In-Lane Localization and Ego-Lane Identification Method Based on Highway Lane Endpoints
المؤلفون المشاركون
Choi, Kyoungtaek
Suhr, Jae Kyu
Jung, Ho Gi
المصدر
Journal of Advanced Transportation
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-01
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
The low-cost global navigation satellite systems combined with an inertial navigation system (GNSS/INS) used most frequently for vehicle localization show errors up to 10 m, approximately, even in open-sky environments such as highways.
To reduce this error on highways, this paper proposes a localization method based on lane endpoints.
Since a lane endpoint frequently appears on a road and can be detected in close proximity even by a low-cost monocular camera, it is a very useful landmark for precise localization.
However, the lane width is generally less than 3.5 m, and the localization error from the GNSS is about 10 m.
Therefore, if an ego-lane is not identified, the lane endpoints detected in an ego-lane can be falsely corresponded to the lane endpoints in the other lane of a map.
This paper proposes an in-lane localization method that uses lane endpoints, the relation between a camera and a road, and the estimated vehicle’s orientation from a map.
In addition, this paper proposes an ego-lane identification method that generates a hypothesis about an ego vehicle position per lane by using the proposed in-lane localization method and verifies each hypothesis by the projection of lane endpoints and an additional landmark such as a road sign.
The average error of the proposed in-lane localization method is 0.248 m on highways.
The success rate of the proposed ego-lane identification method is 99.28% by one trial and reaches 100% by fusing the results.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Choi, Kyoungtaek& Suhr, Jae Kyu& Jung, Ho Gi. 2020. In-Lane Localization and Ego-Lane Identification Method Based on Highway Lane Endpoints. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1176147
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Choi, Kyoungtaek…[et al.]. In-Lane Localization and Ego-Lane Identification Method Based on Highway Lane Endpoints. Journal of Advanced Transportation No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1176147
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Choi, Kyoungtaek& Suhr, Jae Kyu& Jung, Ho Gi. In-Lane Localization and Ego-Lane Identification Method Based on Highway Lane Endpoints. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1176147
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1176147
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر