Travel Time Data Collection for Measurement of Advanced Traveler Information Systems Accuracy
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Travel Time Data Collection for Measurement of Advanced Traveler Information Systems Accuracy

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  • English

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    • Abstract:
      Users of real-time traffic information want to know how long their trips are going to take in order to choose between alternate routes or modes, determine when to leave, or adjust their schedules if necessary. This has spurred interest among traffic managers to estimate point-to-point travel times as part of Advanced Traveler Information Systems (ATIS). Of course, it is impossible to always predict point-to-point travel times with perfect accuracy. There are numerous sources of potential error including the reliability of sensors, the calculation of travel time from sensor measurements, and the inability to accurately forecast how conditions will change over the course of a pending trip. In this paper we underscore the importance of measuring the accuracy of ATIS travel time estimates, discuss the pros and cons of different data collection techniques and provide cost estimates for sufficient studies. This may be as simple as driving a moderately-equipped probe vehicle to measure "ground truth" travel times. Probe vehicle techniques are the best approach to assess the accuracy of an ATIS that covers a number of segments in a metropolitan network. We estimate that 100 probe vehicle runs would comprise a sufficient study for an average sized metropolitan area. Collecting this much data would cost approximately $21,000. Day-to-day travel time variability is a key indicator for how accurate ATIS travel time estimates need to be. An error of 20% is a suitable initial target, though this value may vary significantly by metropolitan area. Under ideal circumstances, one could calculate network-wide variability using archived ATIS travel time estimates. However, if these estimates are shown to be inaccurate based on the ground truth data obtained from the probe vehicle study, this would lead to an inaccurate estimate of variability. Therefore, if travel time estimation error is 20% or worse, additional field data using license plate matching techniques should be taken for the purpose of accurately characterizing day-today variability. For a single study, it is estimated that this would cost approximately $48,000.
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