Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones
Seat-level positioning of a smartphone in a vehicle can provide a fine-grained context for many interesting in-vehicle applications, including driver distraction prevention, driving behavior estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle position...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2014-06-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/7/11605 |
| _version_ | 1811186384623370240 |
|---|---|
| author | Zongjian He Jiannong Cao Xuefeng Liu Shaojie Tang |
| author_facet | Zongjian He Jiannong Cao Xuefeng Liu Shaojie Tang |
| author_sort | Zongjian He |
| collection | DOAJ |
| description | Seat-level positioning of a smartphone in a vehicle can provide a fine-grained context for many interesting in-vehicle applications, including driver distraction prevention, driving behavior estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle positioning relies on special infrastructures, such as the stereo, cigarette lighter adapter or OBD (on-board diagnostic) adapter. In this work, we propose iLoc, an infrastructure-free, in-vehicle, cooperative positioning system via smartphones. iLoc does not require any extra devices and uses only embedded sensors in smartphones to determine the phones’ seat-level locations in a car. In iLoc, in-vehicle smartphones automatically collect data during certain kinds of events and cooperatively determine the relative left/right and front/back locations. In addition, iLoc is tolerant to noisy data and possible sensor errors. We evaluate the performance of iLoc using experiments conducted in real driving scenarios. Results show that the positioning accuracy can reach 90% in the majority of cases and around 70% even in the worst-cases. |
| first_indexed | 2024-04-11T13:44:36Z |
| format | Article |
| id | doaj.art-e7e97d8d1fd44fbb9a240ea43845f24e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:44:36Z |
| publishDate | 2014-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e7e97d8d1fd44fbb9a240ea43845f24e2022-12-22T04:21:08ZengMDPI AGSensors1424-82202014-06-01147116051162810.3390/s140711605s140711605Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via SmartphonesZongjian He0Jiannong Cao1Xuefeng Liu2Shaojie Tang3Department of Computing, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Computing, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Computing, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Computer and Information Science, Temple University, Philadelphia, PA 19122, USASeat-level positioning of a smartphone in a vehicle can provide a fine-grained context for many interesting in-vehicle applications, including driver distraction prevention, driving behavior estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle positioning relies on special infrastructures, such as the stereo, cigarette lighter adapter or OBD (on-board diagnostic) adapter. In this work, we propose iLoc, an infrastructure-free, in-vehicle, cooperative positioning system via smartphones. iLoc does not require any extra devices and uses only embedded sensors in smartphones to determine the phones’ seat-level locations in a car. In iLoc, in-vehicle smartphones automatically collect data during certain kinds of events and cooperatively determine the relative left/right and front/back locations. In addition, iLoc is tolerant to noisy data and possible sensor errors. We evaluate the performance of iLoc using experiments conducted in real driving scenarios. Results show that the positioning accuracy can reach 90% in the majority of cases and around 70% even in the worst-cases.http://www.mdpi.com/1424-8220/14/7/11605in-vehicle positioningsmartphone sensingopportunistic sensingsignal processing |
| spellingShingle | Zongjian He Jiannong Cao Xuefeng Liu Shaojie Tang Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones Sensors in-vehicle positioning smartphone sensing opportunistic sensing signal processing |
| title | Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones |
| title_full | Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones |
| title_fullStr | Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones |
| title_full_unstemmed | Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones |
| title_short | Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones |
| title_sort | who sits where infrastructure free in vehicle cooperative positioning via smartphones |
| topic | in-vehicle positioning smartphone sensing opportunistic sensing signal processing |
| url | http://www.mdpi.com/1424-8220/14/7/11605 |
| work_keys_str_mv | AT zongjianhe whositswhereinfrastructurefreeinvehiclecooperativepositioningviasmartphones AT jiannongcao whositswhereinfrastructurefreeinvehiclecooperativepositioningviasmartphones AT xuefengliu whositswhereinfrastructurefreeinvehiclecooperativepositioningviasmartphones AT shaojietang whositswhereinfrastructurefreeinvehiclecooperativepositioningviasmartphones |