Next Article in Journal
Parylene C-Based Flexible Electronics for pH Monitoring Applications
Next Article in Special Issue
Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors
Previous Article in Journal
Pseudomonas cremoricolorata Strain ND07 Produces N-acyl Homoserine Lactones as Quorum Sensing Molecules
Previous Article in Special Issue
Occupancy Grid Mapping in Urban Environments from a Moving On-Board Stereo-Vision System
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(7), 11605-11628;

Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones

Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China
Department of Computer and Information Science, Temple University, Philadelphia, PA 19122, USA
Author to whom correspondence should be addressed.
Received: 5 May 2014 / Revised: 19 June 2014 / Accepted: 19 June 2014 / Published: 30 June 2014
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Full-Text   |   PDF [1941 KB, uploaded 30 June 2014]


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. View Full-Text
Keywords: in-vehicle positioning; smartphone sensing; opportunistic sensing; signal processing in-vehicle positioning; smartphone sensing; opportunistic sensing; signal processing
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

He, Z.; Cao, J.; Liu, X.; Tang, S. Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones. Sensors 2014, 14, 11605-11628.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top