The position of an individual on Earth is of great importance and can have enormous applications such as Route Recommendation, Driving Navigation, Vehicular Turn Prediction, Travel Pattern Similarity, Pattern Mining, Route Planning, Social Networks, Vehicular ad-hoc networks and so on. Trying to figure out where you are and where you are going is probably one of man’s oldest pastimes. Route Prediction is also dealing with the same thing. There are many attributes, for example, temporal attributes, and transportation means, which can also be used for predicting next optimal point towards the destination. Over the years, all kinds of technologies have tried to simplify this task such as Landmark Techniques, Dead Reckoning Technique, Celestial Techniques, OMEGA Technique, LORAN Techniques, Satellite Navigation Technique and so on. This paper gives a detailed survey of some recent algorithms of route prediction, the attributes handled by them and the methods used by them.

Data Mining, Route Prediction, Probabilistic Model, Route Predictor Systems, GPS, Route Pattern, Map Matching, Spatial Database, Trajectory

[1] Ling Chen, Mingqi Lv, Qian Ye, Gencai Chen and John Woodward, “A personal route prediction system based on trajectory data mining,” Information Sciences, vol. 181, pp. 1264-1284, Apr. 2011.
[2] J. M. Kim, H. Baek and Y. T. Park, “Probabilistic graphical model based personal route prediction in mobile environment,” Applied Mathematics and Information Sciences, vol. 6, No. 2S, pp. 651S-659S, Jan 2012.
[3] Mingqi Lv, Yinglong Li, Zhenming Yuan and Qihui Wang, “Route Pattern Mining From Personal Trajectory Data”, Journal of Information Science and Engineering, vol. 31, pp. 147-164, 2015.
[4] Seongwon Min, Jong-Yong Lee and Kye-Dong Jung, “Real-time path prediction and grid-based path modeling method using gps,” International Journal of Applied Engineering Research, Vol. 12, No. 20, pp. 9997-10001, 2017.
[5] Vishnu Shankar Tiwari and Arti Arya, “Horizontally scalable probabilistic generalized suffix tree (PGST) based route prediction
using map data and GPS traces,” Journal of Big Data, vol. 4, No. 23, 2017.
[6] Vishnu Shankar Tiwari and Arti Arya, “Distributed Context Tree Weighting (CTW) for route prediction,” Open Geospatial Data, Software and Standards, vol. 3, No 10, 2018.
[7] Shun Taguchi, Satoshi Koide and Takayoshi Yoshimura, “Online Map Matching With Route Prediction,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, No. 1 pp. 338-347, Jan. 2018.
[8] Sudhir Kumar Adhlaka, Neelam Duhan, Komal Kumar Bhatia and Himanshu Sharma, “Route Prediction Techniques using GPS Traces and Spatial Data,” Proceedings of INDIACom IEEE International Conference on “Computing for Sustainable Global Development”, BVICAM, New Delhi, pp. 1475-1481, 13th-15th March, 2019.
[9] Y. Deguchi, “HEV charge/discharge control system based on car navigation information,” Proceedings of SAE Convergence International Congress & Exposition on Transportation Electronics, pp. 1–4, 2004.
[10] Ron Begleiter , Ran El-Yaniv and Golan Yona, “On Prediction Using Variable Order Markov Models,” Journal of Artificial Intelligence Research, vol. 22, pp. 385-421, Apr. 2004.
[11] W.H. Lee, S.S. Tseng, W.Y. Shieh, “Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system,” Information Sciences, vol. 180, No. 1, pp. 62-70, Jan 2010.
[12] K. Torkkola, K. Zhang, H. Li, H. Zhang, C. Schreiner and M. Gardner, “Traffic advisories based on route prediction,” Proceedings of Workshop on Mobile Interaction with the Real World, pp. 33–36, 2007.
[13] J. Froehlich and J. Krumm, “Route prediction from trip observations,” in Proc. of the World Congress on Society of Automotive Engineers (SAE), Apr. 2008.
[14] Claire F. Minett, A. Maria Salomons, Winnie Daamen, Bart van Arem and Sjon Kuijpers, “Eco-routing: Comparing the fuel consumption of different routes between an origin and destination using field test speed profiles and synthetic speed profiles,” 2011 IEEE Forum on Integrated and Sustainable Transportation System, Jun. 2011.
[15] E. D. Tate and S.P. Boyd, “Finding Ultimate Limits of Performance for Hybrid Electric Vehicles,” SAE Transactions - Journal of Passenger Car - Mechanical Systems,vol 109, 2001.
[16] U. C. Satish, P. Kondikoppa, S. Park, M. Patil, and R. Shah, “Mapreduce based parallel suffix tree construction for human genome,” in Proc. of the IEEE 20th International Conference on Parallel and Distributed Systems (ICPADS 2014), Taiwan, pp. 664-670, 2014.
[17] E. Mansour, A. Allam, S. Skiadopoulo, and P. Kalnis, “ERA: efficient serial and parallel suffix tree construction for very long strings,” Proc VLDB Endow (PVLDB), vol. 5, no. 1, pp. 49-60, 2011.
[18] J. Yuan, Y. Zheng, X. Xie, and G. Sun, “T-Drive: Enhance driving directions with taxi drivers’ intelligence,” IEEE Transactions on Knowledge and Data Engineering, Vol. 25, pp. 220-232, 2013.
[19] Y. Takeuchi and M. Sugimoto, “CityVoyager: An outdoor recommendation system based on user location history,” Ubiquitous Intelligence and Computing, Vol. 4159, pp. 625-636, 2006.
[20] A. Karbassi and M. Barth, “Vehicle route prediction and time of arrival estimation techniques for improved transportation system management,” in Proceedings of Intelligent Vehicles Symposium, pp. 511-516, 2003.
[21] Y. Zheng and X. Xie, “Learning travel recommendations from usergenerated GPS traces,” ACM Trans. Intell. Syst. Technol., vol. 2, no. 1, 2011.
[22] J. Yuan et al., “T-drive: Driving directions based on taxi trajectories,” in Proc. 18th ACM SIGSPATIAL Int. Conf. Adv. Geograph. Inf. Syst., pp. 99–108, 2010.
[23] V. S. Tiwari, A. Arya, and S. Chaturvedi, “Framework for horizontal scaling of map matching using map-reduce,” in Proc. of the IEEE 13th International Conference on Information Technology (ICIT 2014), pp. 22-24, 22-24 December, 2014.
[24] A. Ghoting and K. Makarychev, “Indexing genomic sequences on the IBM blue gene,” in Proc. of the Conference on High-Performance Computing Networking,” Storage and Analysis (SC), pp. 1-11, 2009.
[25] V. S. Tiwari, A. Arya and S. S. Chaturvedi, “Route prediction using trip observations and map matching,” in Proc. of the IEEE Advance Computing Conference (IACC 2013), pp. 583-587, Feb. 2013.