Road Network Change Detection Based on Floating Car Data
Abstract
The efficiency and accuracy of road network data in the latest electronic maps cannot satisfy the current demands of their application's needs. The present paper proposes a new method to use floating car data to detect and update changes in the road network. An experiment was carried out with actual data to test and verify the feasibility of the novel method. With the highly accurate map-matching between the floating car data and the current road network, the method not only determines road network changes promptly, but also uses incremental detection to obtain updated information on road networks in real time. Compared with the traditional updating method, the new method proposed in the current work can greatly shorten the update period of road networks and improve update efficiency.
Keywords
References
[1] T. Kilpelainen and T. Sarjakoski, “Incremental generalization for multiple representations of geographic objects,” AGRANGE J. WEIBEL R GIS and Generalization. London: Taylor & Francis, 1995, pp. 209-218.
[2] T. Badard, “Towards a generic updating tool for geographic databases,” Proceeding of GIS/LIS98 Annual Exposition and Conference. USA, 1998, pp.352-363.
[3] T. Ai, B. Guo and Y. Huang, “Construction of 1:50000 map database by computer generalization method,” Geometics and Information Science of Wuhan University, 2005, Vol.30, pp. 1-4.
[4] Y. Liu, “Research on the precision of renewal contour map by the high definition remote sensing image,” LiaoNing Technical University, 2007, vol.4, pp.237-284.
[5] Y. Xiao, T. Tan and S. Tay, “Utilizing edge to extract roads in high-resolution on satellite imagery,” IEEE International Conference on Image Processing, ICIP, 2005, pp. 637-640.
[6] C. Jia, L. Zhao and Q. Wu, “Automatic road extraction from SAR imagery based on genetic algorithm,” Journal of Image and Graphics, 2008, vol. 6, pp. 1134-1142.
[7] C. Fabritiis, R. Ragona and G. Valenti, “Traffic Estimation and prediction based on real time floating car data,” IEEE International Conference on Intelligent Transportation Systems, 2008, vol.8, pp. 197-203.
[8] S. Messelodi, C. Modena M., etc, “Intelligent extended floating car data collection,” Expert Systems with Applications, 2009, vol.3, pp. 4213-4227.
http://dx.doi.org/10.1016/j.eswa.2008.04.008
[9] B. Zhou, “The research and application of GPS data preprocessing,” The master's degree thesis, Hehai University, 2005, pp. 18-20.
Full Text: PDF


