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Traveller Information System for Heterogeneous Traffic Condition: A Case Study in Thiruvananthapuram City, India

Traveller Information System for Heterogeneous Traffic Condition: A Case Study in... Traffic in Kerala has been growing at a rate of 10–11% every year, resulting severe congestion especially in urban areas. Because of the limitation of spaces it is not always possible to construct new roads. Road users rely on travel time information for journey planning and route choice decisions, while road system managers are increasingly viewing travel time as an important network performance indicator. More recently Advanced Traveler Information Systems (ATIS) are being developed to provide real-time information to roadway users. For ATIS various methodologies have been developed for dynamic travel time prediction. For this work the Kalman Filter Algorithm was selected for dynamic travel time prediction of different modes. The travel time data collected using handheld GPS device were used for prediction. Congestion Index were calculated and Range of CI values were determined according to the percentage speed drop. After prediction using Kalman Filter, the predicted values along with the GPS data was integrated to GIS and using Network Analysis of ArcGIS the offline route navigation guide was prepared. Using this database a program for route navigation based on travel time was developed. This system will help the travelers with pre-trip information. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of The Institution of Engineers (India): Series A Springer Journals

Traveller Information System for Heterogeneous Traffic Condition: A Case Study in Thiruvananthapuram City, India

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Publisher
Springer Journals
Copyright
Copyright © 2017 by The Institution of Engineers (India)
Subject
Engineering; Civil Engineering
ISSN
2250-2149
eISSN
2250-2157
DOI
10.1007/s40030-017-0228-9
Publisher site
See Article on Publisher Site

Abstract

Traffic in Kerala has been growing at a rate of 10–11% every year, resulting severe congestion especially in urban areas. Because of the limitation of spaces it is not always possible to construct new roads. Road users rely on travel time information for journey planning and route choice decisions, while road system managers are increasingly viewing travel time as an important network performance indicator. More recently Advanced Traveler Information Systems (ATIS) are being developed to provide real-time information to roadway users. For ATIS various methodologies have been developed for dynamic travel time prediction. For this work the Kalman Filter Algorithm was selected for dynamic travel time prediction of different modes. The travel time data collected using handheld GPS device were used for prediction. Congestion Index were calculated and Range of CI values were determined according to the percentage speed drop. After prediction using Kalman Filter, the predicted values along with the GPS data was integrated to GIS and using Network Analysis of ArcGIS the offline route navigation guide was prepared. Using this database a program for route navigation based on travel time was developed. This system will help the travelers with pre-trip information.

Journal

Journal of The Institution of Engineers (India): Series A – Springer Journals

Published: Nov 7, 2017

References

  • Prediction model of bus arrival and departure times using AVL and APC data
    Shalaby, A; Farhan, A
  • Transit vehicle arrival prediction: algorithm and large-scale implementation
    Dailey, D; Maclean, S; Cathey, F; Wall, Z
  • Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses
    Vanajakshi, L; Subramanian, S; Sivanandan, R