Intelligent Vehicular Tracking System For Smooth Public Trasnport |
Author(s): |
| Akshaya Tonde , Pune University; Kalashree Borgaonkar, Pune University; Apoorva Behere, Pune University |
Keywords: |
| Speed, distance, traffic, time prediction, GPS data fields |
Abstract |
|
Many approaches had been proposed for travel time prediction in recent years. Travel time prediction for urban network in real time is challenging, because we have to overcome several factors: complexity and path routing problem in urban network, nonexistence of real-time sensor data and lacking real-time events consideration. In this paper, we propose a heuristic approach based on real-time travel time prediction model which contains real-time and historical travel time predictors to forecast travel time for public transport system. The proposed framework uses three GPS-Data fields (Date-Time, Latitude, and Longitude) to estimate Travel Time, Distance and Speed. As a case study, we have maintained a database for day-to-day traffic behavior of Pune, India. The implementation of this framework will show that using only three GPS data fields, travel time prediction can be achieved. |
Other Details |
|
Paper ID: IJSRDV2I12275 Published in: Volume : 2, Issue : 12 Publication Date: 01/03/2015 Page(s): 529-532 |
Article Preview |
|
|
|
|
