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taxi drivers intelligence

M.Manjula,C.Brinda,K.Giridharan

Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology

ISSN: 2321-3337          Impact Factor:1.521         Volume:4         Issue:3         Year: 30 March,2016         Pages:519-527

International Journal of Advanced Research in Computer Science Engineering and Information Technology

Abstract

Finding efficient driving directions has become a daily activity and been implemented as a key feature in many map services like Google and Bing Maps. A fast driving route saves not only the time of a driver but also energy consumption (as most gas is wasted in traffic jams). Therefore, this service is important for both end users and governments aiming to ease traffic problems and protect environment. 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. A time-dependent landmark graph is proposed 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, a two-stage routing algorithm is designed to compute the practically fastest and customized route for end users. The experimental evaluation for the project is designed using Microsoft Visual Studio .Net 2005. The coding language used is C# .Net. The back end used is MS SQL Server 2000.

Kewords

GPS-equipped taxis

Reference

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