Travel Time Estimation and Prediction using Mobile Phones: A Cost Effective Method for Developing Countries

Authors

  • Satyakumar, M. Traffic and Transportation Engineering Division, Department of Civil Engineering, College of Engineering Trivandrum, Kerala
  • Anil, R. Traffic and Transportation Engineering Division, Department of Civil Engineering, College of Engineering Trivandrum, Kerala
  • Sivakumar, B. Traffic and Transportation Engineering Division, Department of Civil Engineering, College of Engineering Trivandrum, Kerala

DOI:

https://doi.org/10.9744/ced.16.1.33-39

Keywords:

Resource Tracking and Management Service (RTMS), mobile phone tracking, real time traffic data collection

Abstract

Conventional data collection methods lack real time information and involve excessive cost of installation and maintenance. A real-time, low cost travel time data collection system can be developed using mobile phones. This project examines the use of mobile phones for travel time prediction of public transit vehicles and develops a dynamic travel time prediction model. Personnel were employed in public transit vehicles with mobile phones and these mobile phones were tracked continuously. Space information of the mobile phones represents the position of the buses and movement pattern of these mobile phones in turn represents the movement pattern of the public buses. The starting and arrival time at sections obtained from the cellular database were used to get the travel time and speed. Results obtained were statistically significant and it shows that use of mobile phone for travel time data collection is a low cost data collection technique for Indian cities.

References

Sutandi, A.C., Evaluation of the Impacts of VMS on Traffic Performance Measures in an Urban Area in Indonesia, Civil Engineering Dimension, 10(1), 2008, pp. 28-34

Borzacchiello, M.T., Steenbruggen, J., Nijkamp, P., and Scholten, H., The Use of Data from Mobile Phone Networks for Transportation Applications, TRB Annual Meeting CD-ROM, 2010.

http://www.circuitstoday.com/how-the-gsm-system-works. Last accessed on 10-11-2011.

Calabrese, F., Colonna, M., Lovisolo, P., Parata, D., and Ratti, C., Real-time Urban Monitoring using Cellular Phones: A Case-study in Rome, SENSEable Working Paper, Senseable City Lab, 2007.

Bar-Gera, H., Evaluation of a Cellular Phone-based System for Measurements of Traffic Speeds and Travel Times: A Case Study from Israel, Transportation Research, Part C, 15, 2007, pp. 380-391.[CrossRef]

White, J. and Wells, Extracting Origin Destination Information from Mobile Phone Data, Proceedings of the 11th International Conference on Road Transport Information and Control, London, Conf. Publ. No.486, 2002, pp. 30-34.

Pattara-atikom, W. and Peachavanish, R., Estimating Road Traffic Congestion from Cell Dwell Time using Neural Network, Telecommunications 2007, Proceedings of the 7th International Conference on ITS, June 2007.

Lu, B. and Huang, M., A New Measure for Traffic Data Collection and Processing, Second International Conference on Intelligent Computation Technology and Automation, IEEE Computer Society, 2009, pp. 440-443.

Bekhor, S., Hirsh, M., Nimre, S., and Feldman, I., Identifying Spatial and Temporal Congestion Characteristics Using Passive Mobile Phone Data, Transportation Research Board Annual Meeting, Paper # 08-1534, 2008.

Imagery © 2009 Cnes/Spot Image, Digital Globe, Landsat, Map data © 2009 Google.

Shalaby, A. and Farhan, A., Bus Travel Time Prediction Model for Dynamic Operations Control and Passenger Information Systems, TRB, Annul Meeting CD-ROM, 2003, TRB 82nd Annual Meeting, Washington D C.

Shalaby, A. and Farhan, A., Prediction Model of Bus Arrival and Departure Times Using AVL and APC Data, Journal of Public Transportation, 7(1), 2004, pp. 41-61.

Patnaik, J., Chein, S. and Bladikas, A., Estimation of Bus Arrival Times using APC Data, Journal of Public Transportation, 7(1), 2004, pp. 1-20.

MATLAB Version 7.10.0.499 (R2010a), The MathWorks, Inc.

Seema, S., R. and Alex, S., Dynamic Bus Arrival Time Prediction using GPS Data, Proceedings of the 10th National Conference on Technological Trends (NCTT09), 2009, College of Engineering, Trivandrum, India.

Sivakumar. B., Traffic Monitoring using GSM Technology: An Emerging Opportunity for ATIS, M Tech Thesis, University of Kerala, India 2010.

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Published

2014-03-01

How to Cite

M., S., R., A., & B., S. (2014). Travel Time Estimation and Prediction using Mobile Phones: A Cost Effective Method for Developing Countries. Civil Engineering Dimension, 16(1), 33-39. https://doi.org/10.9744/ced.16.1.33-39

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Articles