2015•Transport Research ForumRequires access

Quality investigation and variability analysis of GPS travel time data in Sydney

Ruimin Li, Malcolm Bradley, Matthew D. Jones, Steven Moloney

Open publisher page 1 citations

Abstract

Reliable and accurate travel time data can provide valuable performance measures to support operational applications in areas of congestion management and routing analysis. The travel time information is also essential to the calibration and validation of travel demand models in order to better model current and future travel for congested area. Historically, the ability to collect travel time data in sufficient quantity to provide reliable, robust evidence has been severely limited, almost to the point of being unattainable. Indeed, to take it further, any aspirations of addressing travel time variability are almost inconceivable. Recent developments with Global Positioning Systems (GPS) data have shed new light in this field. The ability to collect large volumes of data from GPS devices has provided a wealth of data for use in this area. Such data collected and processed by Intelematics for a large proportion of the Greater Metropolitan strategic road network has been reviewed and analysed to examine time of day and day of week variations in travel times by traffic conditions for individual sections of road. Findings from this research could significantly influence the guidelines, processes and procedures for future model validation.

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What this paper is about

Reliable and accurate travel time data can provide valuable performance measures to support operational applications in areas of congestion management and routing analysis. The travel time information is also essential to the calibration and validation of travel demand models in order to better model current and future travel for congested area. Historically, the ability to collect travel time data in sufficient quantity to provide reliable, robust evidence has been severely limited, almost to the point of being unattainable. Indeed, to take it further, any aspirations of addressing travel time variability are almost inconceivable. Recent developments with Global Positioning Systems (GPS) data have shed new light in this field. The ability to collect large volumes of data from GPS devices has provided a wealth of data for use in this area. Such data collected and processed by Intelematics for a large proportion of the Greater Metropolitan strategic road network has been reviewed and analysed to examine time of day and day of week variations in travel times by traffic conditions for individual sections of road. Findings from this research could significantly influence the guidelines, processes and procedures for future model validation.

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Available abstract

Reliable and accurate travel time data can provide valuable performance measures to support operational applications in areas of congestion management and routing analysis. The travel time information is also essential to the calibration and validation of travel demand models in order to better model current and future travel for congested area. Historically, the ability to collect travel time data in sufficient quantity to provide reliable, robust evidence has been severely limited, almost to the point of being unattainable. Indeed, to take it further, any aspirations of addressing travel time variability are almost inconceivable. Recent developments with Global Positioning Systems (GPS) data have shed new light in this field. The ability to collect large volumes of data from GPS devices has provided a wealth of data for use in this area. Such data collected and processed by Intelematics for a large proportion of the Greater Metropolitan strategic road network has been reviewed and analysed to examine time of day and day of week variations in travel times by traffic conditions for individual sections of road. Findings from this research could significantly influence the guidelines, processes and procedures for future model validation.

Key concepts: Global Positioning System, Metropolitan area, Computer science, Transport engineering, Travel time, Data quality, Quality (philosophy), Travel behavior

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