• 베이커리
• /
• no.7 s.396
• /
• pp.34-51
• /
• 2001

• Journal of Korea Multimedia Society
• /
• v.12 no.2
• /
• pp.300-312
• /
• 2009

An indoor location-based service cannot be realized unless the indoor positioning problem is solved. However, the cost-effective indoor positioning systems are suffering from their inaccurateness. This paper proposes a map information-based correction method for the indoor positioning systems. Using our Kalman filter with map information-based appropriate parameter values, our method estimates the track of the moving object, then it performs the Frechet Distance-based map matching on the obtained track. After that it applies our real time correction method. In order to verify efficiency of our method, we also provide our test results.

• Journal of KIISE
• /
• v.43 no.1
• /
• pp.40-46
• /
• 2016

Digital road map generation is primarily based on artificial satellite photographing or in-site manual survey work. Therefore, these map generation procedures require a lot of time and a large budget to create and update road maps. Consequently, people have tried to develop automated map generation systems using GPS trajectory data sets obtained by public vehicles. A fundamental problem in this road generation procedure involves the extraction of representative trajectory such as main roads. Extracting a representative trajectory requires the base data set of piecewise line segments(GPS-trajectories), which have close starting and ending points. So, geometrically similar trajectories are selected for clustering before extracting one representative trajectory from among them. This paper proposes a new divide- and-conquer approach by partitioning the whole map region into regular grid sub-spaces. We then try to find similar trajectories by sweeping. Also, we applied the $Fr{\acute{e}}chet$ distance measure to compute the similarity between a pair of trajectories. We conducted experiments using a set of real GPS data with more than 500 vehicle trajectories obtained from Gangnam-gu, Seoul. The experiment shows that our grid partitioning approach is fast and stable and can be used in real applications for vehicle trajectory clustering.