View Item 
      •   Home
      • 1. Schools
      • College of Engineering
      • School of Electrical and Electronic Engineering (EEE)
      • EEE Theses
      • View Item
      •   Home
      • 1. Schools
      • College of Engineering
      • School of Electrical and Electronic Engineering (EEE)
      • EEE Theses
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.
      Subject Lookup

      Browse

      All of DR-NTUCommunities & CollectionsTitlesAuthorsBy DateSubjectsThis CollectionTitlesAuthorsBy DateSubjects

      My Account

      Login

      Statistics

      Most Popular ItemsStatistics by CountryMost Popular Authors

      About DR-NTU

      Methods for real time prediction and visualization of traffic using smartphones

      Thumbnail
      Main article (10.38Mb)
      Author
      Narayanan, Aditya
      Date of Issue
      2016
      School
      School of Electrical and Electronic Engineering
      Related Organization
      Nanyang Technological University
      Abstract
      The advances in the capabilities of smartphones and their widespread popularity have opened up new avenues for improvement in Advanced Traveller Infonnation Systems (ATIS). Increased computation power, storage capacity and better internet connectivity have made smartphones the optimal choice in providing more useful real time information to the travellers and allowed the implementation of intelligent algorithms on smartphones. The compressed traffic prediction method is one such algorithm that provides accurate real time predictions of traffic speeds by explicitly predicting speeds only at a small number of links in the network . The objective of this thesis is to illustrate and evaluate the different approaches to disseminate and visualize compressed traffic prediction data using an android application. An android application that allows effective visualization of traffic data overlaid on a map and perform other geospatial tasks is created. The application provides an illustration of the entire road network of Singapore, where road segments are colored according to average speed of the particular segment, which can be overlaid with rainfall patterns or road incidents, for visual analysis. For the back end, different methods are introduced and evaluated. First, a server based approach is tried out where the traffic information is stored and predictions are done on the server. This is followed by a hybrid method where the computation of traffic predictions alone is done on the server while the device generates the spatial features locally. Next, both computation of traffic predictions as well as visualization of traffic conditions is performed on the smartphone. In this case, the server behaves only as a data collector from where the smartphone fetches current traffic data. The performance of smartphones in each of the above methods is studied and the advantages and disadvantages of each of the proposed method is highlighted. Further, the feasibility of using predicted traffic data to address real world problems such as optimal route planning and travel time calculation is explored.
      Subject
      DRNTU::Engineering::Electrical and electronic engineering
      Type
      Thesis
      Collections
      • EEE Theses

      Show full item record


      NTU Library, Nanyang Avenue, Singapore 639798 © 2011 Nanyang Technological University. All rights reserved.
      DSpace software copyright © 2002-2015  DuraSpace
      Contact Us | Send Feedback
      Share |    
      Theme by 
      Atmire NV
       

       


      NTU Library, Nanyang Avenue, Singapore 639798 © 2011 Nanyang Technological University. All rights reserved.
      DSpace software copyright © 2002-2015  DuraSpace
      Contact Us | Send Feedback
      Share |    
      Theme by 
      Atmire NV
       

       

      DCSIMG