Loughborough University
Sanaullah Quddus Enoch low frequency GPS JITS paper 21 1 2016 accepted version.pdf (427.65 kB)

Developing travel time estimation methods using sparse GPS data

Download (427.65 kB)
journal contribution
posted on 2016-03-08, 11:10 authored by Irum Sanaullah, Mohammed Quddus, Marcus EnochMarcus Enoch
Existing methods of estimating travel time from GPS data are not able to simultaneously take account of the issues related to uncertainties associated with GPS and spatial road network data. Moreover, they typically depend upon high frequency data sources from specialist data providers which can be expensive and are not always readily available. The study reported here therefore sought to better estimate travel time using ‘readily available’ vehicle trajectory data from moving sensors such as buses, taxis and logistical vehicles equipped with GPS in ‘near’ real-time. To do this, accurate locations of vehicles on a link were first map-matched to reduce the positioning errors associated with GPS and digital road maps. Two mathematical methods were then developed to estimate link travel times from map-matched GPS fixes, vehicle speeds and network connectivity information with a special focus on sampling frequencies, vehicle penetration rates and time window lengths. GPS data from Interstate I-880 (California, USA) for a total of 73 vehicles over 6 hours were obtained from the UC-2 Berkeley’s Mobile Century Project, and these were used to evaluate several travel time estimation methods, the results of which were then validated against reference travel time data collected from high resolution video cameras. The results indicate that vehicle penetration rates, data sampling frequencies, vehicle coverage on the links and time window lengths all influence the accuracy of link travel time estimation. The performance was found to be best in the 5 minute time window length and for a GPS sampling frequency of 60 seconds.



  • Architecture, Building and Civil Engineering

Published in

Journal of Intelligent Transportation Systems






532 - 544


SANAULLAH, I., QUDDUS, M.A. and ENOCH, M.P., 2016. Developing travel time estimation methods using sparse GPS data. Journal of Intelligent Transportation Systems: technology, planning, and operations, 20 (6), pp. 532-544.


© Taylor & Francis


  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date


Publication date



This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Intelligent Transportation Systems on 27 Apr 2016, available online: http://www.tandfonline.com/10.1080/15472450.2016.1154764.






  • en