Demand Supply Oriented Taxi Suggestion System for Vehicular Social Networks with Fuel Charging Mechanism
Author(s) -
C. P. Thamil Selvi,
D Keerthana
Publication year - 2019
Publication title -
international journal of scientific research in computer science engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit19515
Subject(s) - taxis , global positioning system , computer science , transport engineering , scale (ratio) , operations research , telecommunications , engineering , geography , cartography
Data mining depends on large-scale taxi traces is an important research concepts. A vital direction for analyzing taxi GPS dataset is to suggest cruising areas for taxi drivers. The project first investigates the real-time demand-supply level for taxis, and then makes an adaptive tradeoff between the utilities of drivers and passengers for different hotspots. This project constructs a recommendation system by jointly considering the profits of both drivers and passengers. At last, the qualified candidates are suggested to drivers based on analysis. The project also provides a real-time charging station recommendation system for EV taxis via large-scale GPS data mining. By combining each EV taxi’s historical recharging actions and real-time GPS trajectories, the present operational state of each taxi is predicted. Based on this information, for an EV taxi requesting a recommendation, recommend a charging station that leads to the minimal total time before its recharging starts.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom