Enabling Routes of Road Network Constrained Movements as Mobile Service Context
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With the continuing advances in wireless communications, geo-positioning, and portable electronics, an infrastructure is emerging that enables the delivery of on-line, location-enabled services to very large numbers of mobile users. A typical usage situation for mobile services is one characterized by a small screen and no keyboard, and by the service being only a secondary focus of the user. Under such circumstances, it is particularly important to deliver the “right” information and service at the right time, with as little user interaction as possible. This may be achieved by making services context aware. Mobile users frequently follow the same route to a destination as they did during previous trips to the destination, and the route and destination constitute important aspects of the context for a range of services. This paper presents key concepts underlying a software component that identifies and accumulates the routes of a user along with their usage patterns and that makes the routes available to services. The problems associated with of route recording are analyzed, and algorithms that solve the problems are presented. Experiences from using the component on logs of GPS positions acquired from vehicles traveling within a real road network are reported.
Keywordsmobile service context geopositioning portable electronics GPS positions mobile services location-based services routes destinations context awareness
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- 1.American National Standards Institute. Geographic Information Framework—Data Content Standards For Transportation: Roads, ANSI, Washington, DC, 2003.Google Scholar
- 3.C. Barrett, K. Bisset, R. Jacob, G. Konjevod, and M. Marathe. “Classical and contemporary shortest path problems in road networks: implementation and experimental analysis of the TRANSIMS router,” in Proc. of European Symposium on Algorithms, LNCS vol. 2461, pp. 126–138, Springer, 2002.Google Scholar
- 4.D. Bernstein and A. Kornhauser. An Introduction to Map Matching for Personal Navigation Assistants. New Jersey TIDE Center, New Jersey 1996.Google Scholar
- 5.S. Brakatsoulas, D. Pfoser, and N. Tryfona. “Modeling, storing, and mining moving object databases,” in Proc. of IDEAS, Coimbra, Portugal, pp. 68–77, IEEE Computer Society, 2004.Google Scholar
- 6.S. Brakatsoulas, D. Pfoser, and N. Tryfona. “Practical data management techniques for vehicle tracking data,” in Proc. of the 21st International Conference on Data Engineering (ICDE’05), pp. 324-325, ACM, 2005.Google Scholar
- 7.A. Brilingaitė, C.S. Jensen, and N. Zokaitė. “Enabling routes as context in mobile services,” in Proc. of ACM GIS, pp. 127–136, ACM, 2004.Google Scholar
- 8.J.A. Butler and K.J. Dueker. “Implementing the enterprise GIS in transportation database design,” Journal of the Urban and Regional Information Systems Association, Vol. 13(1):17–28, 2001.Google Scholar
- 9.H. Cao and O. Wolfson. “Nonmaterialized motion information in transport networks,” in Proc. of ICDT, pp. 173–188, 2005.Google Scholar
- 10.A. Čivilis, C.S. Jensen, J. Nenortaitė, and S. Pakalnis. “Efficient tracking of moving objects with precision guarantees,” in Proc. of MobiQuitous, pp. 164–173, 2004.Google Scholar
- 12.CommLinx Solutions Pty Ltd. “Common NMEA sentence types,” http://www.commlinx.com.au/, 2002.
- 13.Z. Ding and R.H. Güting. “Modeling temporally variable transportation networks,” in Proc. of DASFAA, pp. 154–168, 2004.Google Scholar
- 14.European Commission. “GALILEO. European satellite navigation system,” http://europa.eu.int/comm/dgs/energy_transport/galileo/index_en.htm, 2006.
- 15.Federal Communications Commission. “Enhanced 911—wireless services,” http://www.fcc.gov/911/enhanced/ .
- 16.C. Hage, C.S. Jensen, T.B. Pedersen, L. Speicys, and I. Timko. “Integrated data management for mobile services in the real world,” in Proc. of VLDB, pp. 1019–1030, Morgan Kaufmann, 2003.Google Scholar
- 17.A. Harrington and V. Cahill. “Route profiling—putting context to work,” in Proc. of SAC, pp. 1567–1573, ACM, 2004.Google Scholar
- 18.X. Huang and C.S. Jensen. “In-route skyline querying for location-based services,” in Proc. of the Fourth International Workshop on Web and Wireless Geographic Information Systems, pp. 223–238, 2004. (Also pp. 120–135 in the Lecture Notes in Computer Science, Vol. 3428, Springer, 2005.)Google Scholar
- 19.C.S. Jensen, H. Lahrmann, S. Pakalnis, and J. Runge. “The infati data,” TimeCenter Technical Report TR-79, July 2004, 10 pages. Also CoRR cs.DB/0410001, http://arxiv.org/abs/cs.DB/0410001.
- 20.L. Liao, D. Fox, and H. A. Kautz. “Learning and inferring transportation routines,” in Proc. of AAAI, pp. 348–353, AAAI, 2004.Google Scholar
- 21.C. Murray. Oracle Spatial User Guide and Reference, Release 9.2., Oracle Corporation, 2002.Google Scholar
- 22.NMEA. NMEA 0183 Standard. http://www.nmea.org/pub/0183/, 2002.
- 23.N. Roussopoulos, S. Kelley, and F. Vincent. “Nearest neighbor queries,” in Proc. of ACM SIGMOD, pp. 71–79, ACM, 1995.Google Scholar
- 24.P. Scarponcini. “Generalized model for linear referencing,” in Proc. of ACM-GIS, pp. 53–59, ACM, 1999.Google Scholar
- 25.J. Schiller and A. Voisard. Location-based Services. Morgan Kaufmann: San Mateo, CA, 2004.Google Scholar
- 26.Z. Song and N. Roussopoulos. “K-nearest neighbor search for moving query point,” in Proc. of SSTD, Redondo Beach, CA, pp. 79–96, Springer, 2001.Google Scholar
- 27.M. Vazirgiannis and O. Wolfson. “A spatiotemporal model and language for moving objects on road networks,” in Proc. of SSTD, pp. 20–35, Springer, 2001.Google Scholar
- 28.H. Yin and O. Wolfson. “A weight-based map matching algorithm in moving objects databases,” in Proc. of SSDBM, pp. 437–438, IEEE, 2004.Google Scholar