International Journal of Advanced Computing and Communication Systems

The Road Information Program

Ilakkiyavani R, Savitha N and Prakash U, Department of CSE, Sri Eshwar College Of Engineering, Coimbatore, Tamilnadu, India.

International Journal of Advanced Computing and Communication Systems

ISSN (Online) : 2347 - 9299

ISSN (Print) : 2347 - 9280

Received On :

Revised On :

Accepted On :

Published On :

Volume 04, Issue 03

Page No : 001-006

Abstract

This project presents a smart driving direction system leveraging the intelligence of experienced drivers. In this system, GPS-equipped taxis are employed as mobile sensors probing the traffic rhythm of a city and taxi drivers’ intelligence in choosing driving directions in the physical world. We propose a time-dependent landmark graph to model the dynamic traffic pattern as well as the intelligence of experienced drivers so as to provide a user with the practically fastest route to a given destination at a given departure time. Then, a Variance-Entropy-Based Clustering approach is devised to estimate the distribution of travel time between two landmarks in different time slots. Based on this graph, we design a two-stage routing algorithm to compute the practically fastest and customized route for end users. We build our system based on a real-world trajectory data set generated by over 33,000 taxis in a period of three months, and evaluate the system by conducting both synthetic experiments and in-the-field evaluations. As a result, 60-70 percent of the routes suggested by our method are faster than the competing methods, and 20 percent of the routes share the same results. On average, 50 percent of our routes are at least 20 percent faster than the competing approaches.

Keywords

GPS, Traffic Pattern.

Cite this Article

Ilakkiyavani R, Savitha N and Prakash U, “The Road Information Program, ”International Journal of Advanced Computing and Communication Systems, pp. 001-006, November 2017.

Copyright

© 2017 Ilakkiyavani R, Savitha N and Prakash U.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.