smart traveller-effective and proficient taxi buisness application
Raut Prasad S ,Lipane Bhagwat S ,Auti Dattatraya A ,Swami Vijyaykumar V
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:5 Issue:3 Year: 22 March,2015 Pages:384-394
Abstract
Taxi administration is imperative business which focused around GPS has turned into an essential apparatus for essential and proficient Taxi business. It will utilized for the purpose of Taxi driver administration and additionally give helpful data to cabbies to win more benefit. We are proposing a Taxi recommender i.e ”Smart Traveler” Framework for discovering traveler area which could be a valuable module for efficient Taxi business. In that three elements have been considered, and separated between the current area and the suggested traveler area, expected toll for the outing and holding up time for next travelers at that area. We additionally allude an ON-OFF model to gauge the normal charge for an outing began at a suggested area. A certifiable data set is utilized to assess the proposed framework. A Framework will reenact cruising conduct of taxis in the CRAWDAD data set and one virtual taxi which travels focused around our recommender framework. Our system helps to discover taxi productively and adequately. Because of utilization of this application we can encounter a normal holding up time to pick-up a traveler 5 lower than its rival. For the powerful business of Taxi we anticipate the spatial temporal dissemination continuously.
Kewords
GPS, ON-OFF model, OFF-ON model, CRAWDAD.
Reference
[1]Yu-Ling Hsueh, Ren-Hung Hwang, and Yu-Ting Chen,”An Effective Taxi Recommender System Based on a Spatiotemporal Factor Analysis Model”, International conference on computing, Networking and communication, Mobile Computing and Vehicle Communication Symposium, 2014, pp.429-433 [2]Nicholas Jing Yuan,Yu Zheng,Liuhang Zhang, and Xing Xie,”T-Finder: A Recommender System for Finding Passengers and Vacant Taxis”,IEEE Transactions on Knowledge And Data Engineering, VOL. 25, NO. 10, OCTOBER 2013, pp 2390-2403 [3]Ye Ding, Siyuan Liu, Jiansu Pu, Lionel M. Ni,”HUNTS: A Trajectory Recommendation System for Effective and Efficient Hunting of Taxi Passengers” , 2013 IEEE 14thInternational Conference on Mobile Data Management, pp 107-116 [4]L. Moreira-Matias, R. Fernandez, J. Gama, M. Ferreira, J. o. Mendes-Moreira, and L.Damas, An online recommendation system for the taxi stand choice problem (poster),in VNC, 2012, pp. 173180. [5]M. Ester, H. peter Kriegel, J. S, and X. Xu, “A density-based algorithm for discovering clusters in large spatial databases with noise”, in the 2nd International Conference on Knowledge Discovery and Data Mining,1996, pp. 226231. [6] J.W. Powell, Y. Huang, F. Bastani, and M. Ji, “Towards reducing taxicab cruising time using spatio-temporal profitability maps”, in Proceedings of the 12th international conference on Advances in spatial and temporal databases, Berlin, Heidelberg, 2011, pp. 242260. [7]https://play.google.com/store/apps/details?id=br.com.easytaxihl=en [8]https://play.google.com/store/apps/details?id=com.alnetsystems.cmshl=en [9] www.cabmanagementsystem.com/67852902926pageNumber3D4 [10]https://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6785373punumber3D67784 7626sortTyp3DascpSequence26filter3DAND28pISNumber3A67852902926pageNumber3 D7
