TY - GEN
T1 - An FCD compensation model based on traffic condition trends matching
AU - Lv, Weifeng
AU - Liang, Yun
AU - Zhu, Tongyu
AU - Du, Bowen
AU - Wu, Dongdong
PY - 2009
Y1 - 2009
N2 - As an advanced means of collecting information of traffic condition of roads, floating car technology has drawn increasing attention from many countries. Whereas, Floating Car Data (FCD) collected by floating car technology often could not cover all the roads of a city. Therefore, in order to increase the integrality and usability of FCD which reflects the traffic condition of roads, a model based on History FCD (HFCD) is proposed to compensate the information of traffic condition of roads which are not covered by real-time FCD. The model corrects the abnormal data in HFCD and extracts all the changing modes of driving speed of all roads from HFCD, and by matching the changing trend of driving speed in real-time FCD with these modes, the vacant real-time data could be derived. In the end, 20 floating car are arranged to testify the effectiveness of the model, the results shows that the model compensates the vacant real-time data accurately and increases the coverage of road networks.
AB - As an advanced means of collecting information of traffic condition of roads, floating car technology has drawn increasing attention from many countries. Whereas, Floating Car Data (FCD) collected by floating car technology often could not cover all the roads of a city. Therefore, in order to increase the integrality and usability of FCD which reflects the traffic condition of roads, a model based on History FCD (HFCD) is proposed to compensate the information of traffic condition of roads which are not covered by real-time FCD. The model corrects the abnormal data in HFCD and extracts all the changing modes of driving speed of all roads from HFCD, and by matching the changing trend of driving speed in real-time FCD with these modes, the vacant real-time data could be derived. In the end, 20 floating car are arranged to testify the effectiveness of the model, the results shows that the model compensates the vacant real-time data accurately and increases the coverage of road networks.
KW - Floating Car data (FCD)
KW - History Data Pattern Library (HDPL)
KW - Trend matching
UR - https://www.scopus.com/pages/publications/77749277461
U2 - 10.1109/ICCIT.2009.47
DO - 10.1109/ICCIT.2009.47
M3 - 会议稿件
AN - SCOPUS:77749277461
SN - 9780769538969
T3 - ICCIT 2009 - 4th International Conference on Computer Sciences and Convergence Information Technology
SP - 1201
EP - 1206
BT - ICCIT 2009 - 4th International Conference on Computer Sciences and Convergence Information Technology
T2 - 4th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2009
Y2 - 24 November 2009 through 26 November 2009
ER -