Open AccessAnn Modeling For Predicting Car Travel Time using Bus As Probe.
Author(s) -
Akram S. Kotb*
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l3612.1081219
Subject(s) - travel time , global positioning system , artificial neural network , transport engineering , real time computing , computer science , arrival time , real time data , intelligent transportation system , simulation , engineering , artificial intelligence , telecommunications , world wide web
The critical issue of Intelligent Transportation Systems (ITS) applications is obtaining the near real time information of travel times. This paper proposes a dependable model for predicting car travel time on urban roads in Greater Cairo using buses as probes. The GPS receivers, which are installed on test vehicles and buses, used to collect real travel time data along the urban roads. The travel times of bus and car are compared in order to recognize similarities and differences between the trip profiles of test vehicles and buses. According to the comparison results, the model is developed and validated using Artificial Neural Network (ANN) for estimating car travel time using buses’ travel time with acceptable level of accuracy equals 10.53%.