High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU
Collision avoidance and road safety applications require highly accurate vehicle localization techniques. Unfortunately, the existing localization techniques are not suitable for road safety applications as they rely on the error-prone Global Positioning System (GPS). Likewise, cooperative localizat...
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| Format: | Article |
| Language: | English |
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Wiley
2015-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/795036 |
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| _version_ | 1850219550257184768 |
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| author | Ahmed Khattab Yasmine A. Fahmy Ahmed Abdel Wahab |
| author_facet | Ahmed Khattab Yasmine A. Fahmy Ahmed Abdel Wahab |
| author_sort | Ahmed Khattab |
| collection | DOAJ |
| description | Collision avoidance and road safety applications require highly accurate vehicle localization techniques. Unfortunately, the existing localization techniques are not suitable for road safety applications as they rely on the error-prone Global Positioning System (GPS). Likewise, cooperative localization techniques that use intervehicle communications experience high errors due to hidden vehicles and the limited sensing/communication range. Recently, GPS-free localization based on vehicle communication with a low cost infrastructure installed on the roadsides has emerged as a more accurate alternative. However, existing techniques require the vehicle to communicate with two roadside units (RSUs) in order to achieve high localization accuracy. In contrast, this paper presents a GPS-free localization framework that uses two-way time of arrival to locate the vehicles based on communication with a single RSU. Furthermore, our framework uses the vehicle kinematics information obtained via the vehicle's onboard inertial navigation system (INS) to further improve the accuracy of the vehicle location using Kalman filters. Our results show that the localization error of the proposed framework is as low as 1.8 meters. The resulting localization accuracy is up to 65% and 47.5% better than GPS-based techniques used without/with INS, respectively. This accuracy gain becomes around 73.3% when compared to existing RSU-based techniques. |
| format | Article |
| id | doaj-art-79b0f7e6c18f4ddebc8693218eb58c87 |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-79b0f7e6c18f4ddebc8693218eb58c872025-08-20T02:07:20ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-05-011110.1155/2015/795036795036High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSUAhmed Khattab0Yasmine A. Fahmy1Ahmed Abdel Wahab2 Cairo University, Giza 12613, Egypt Cairo University, Giza 12613, Egypt Egyptian Civil Aviation Authority, Cairo 11776, EgyptCollision avoidance and road safety applications require highly accurate vehicle localization techniques. Unfortunately, the existing localization techniques are not suitable for road safety applications as they rely on the error-prone Global Positioning System (GPS). Likewise, cooperative localization techniques that use intervehicle communications experience high errors due to hidden vehicles and the limited sensing/communication range. Recently, GPS-free localization based on vehicle communication with a low cost infrastructure installed on the roadsides has emerged as a more accurate alternative. However, existing techniques require the vehicle to communicate with two roadside units (RSUs) in order to achieve high localization accuracy. In contrast, this paper presents a GPS-free localization framework that uses two-way time of arrival to locate the vehicles based on communication with a single RSU. Furthermore, our framework uses the vehicle kinematics information obtained via the vehicle's onboard inertial navigation system (INS) to further improve the accuracy of the vehicle location using Kalman filters. Our results show that the localization error of the proposed framework is as low as 1.8 meters. The resulting localization accuracy is up to 65% and 47.5% better than GPS-based techniques used without/with INS, respectively. This accuracy gain becomes around 73.3% when compared to existing RSU-based techniques.https://doi.org/10.1155/2015/795036 |
| spellingShingle | Ahmed Khattab Yasmine A. Fahmy Ahmed Abdel Wahab High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU International Journal of Distributed Sensor Networks |
| title | High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU |
| title_full | High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU |
| title_fullStr | High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU |
| title_full_unstemmed | High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU |
| title_short | High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU |
| title_sort | high accuracy gps free vehicle localization framework via an ins assisted single rsu |
| url | https://doi.org/10.1155/2015/795036 |
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