TY - JOUR
T1 - An intelligent driver location system for smart parking
AU - Lan, Kun Chan
AU - Shih, Wen Yuah
N1 - Funding Information:
This work was supported by the National Science Council of Taiwan under Grants NSC 101-2220-E-006-010 and NSC 101-2221-E-006-098-MY3.
PY - 2014/4
Y1 - 2014/4
N2 - It is often frustrating for drivers to find parking spaces, and parking itself is costly in almost every major city in the world. Here we propose a crowdsourcing solution by exploiting sensors in smart-phones to collect real-time parking availability information. We design a phone-based system to track a driver's trajectory to detect when they are about to leave their parking spot. We focus on the efficiency and accuracy of using a phone to monitor the driver's walking trajectory, applying a waist-mounted PDR method that can measure the driver's moving distance with a high accuracy. In addition, we design a map matching algorithm to calibrate the direction errors when the driver is in an indoor environment, using widely-available building floor plans. The results of our experiment show that we can achieve about 98% accuracy in estimating the user's walking distance, with an overall location error of about 0.48 m.
AB - It is often frustrating for drivers to find parking spaces, and parking itself is costly in almost every major city in the world. Here we propose a crowdsourcing solution by exploiting sensors in smart-phones to collect real-time parking availability information. We design a phone-based system to track a driver's trajectory to detect when they are about to leave their parking spot. We focus on the efficiency and accuracy of using a phone to monitor the driver's walking trajectory, applying a waist-mounted PDR method that can measure the driver's moving distance with a high accuracy. In addition, we design a map matching algorithm to calibrate the direction errors when the driver is in an indoor environment, using widely-available building floor plans. The results of our experiment show that we can achieve about 98% accuracy in estimating the user's walking distance, with an overall location error of about 0.48 m.
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U2 - 10.1016/j.eswa.2013.09.044
DO - 10.1016/j.eswa.2013.09.044
M3 - Article
AN - SCOPUS:84890122491
SN - 0957-4174
VL - 41
SP - 2443
EP - 2456
JO - Expert Systems With Applications
JF - Expert Systems With Applications
IS - 5
ER -