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Using Archived AVL-APC Data to Improve Transit Performance and Management (2006) / Chapter Skim
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Pages 66-69

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From page 66...
... 10.2.1 Time-at-Location and Locationat-Time Data Polling data can be characterized as location-at-time data, giving bus location at an arbitrary time; stop and timepoint records, on the other hand, have time-at-location data, giving the time at which a bus arrives or departs from a specific location. Most off-line analyses, including analyses of running time and schedule adherence, require knowledge of departure time from standard locations.
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From page 67...
... Stop-level analysis helps enable operations analysis to identify points of delay, determine the impact of changes to stop location or traffic control, and analyze bunching. Stop-level data also permits more customer-oriented service quality analysis, such as enabling determination of passenger waiting time at stops.
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From page 68...
... Such records can also add detail and accuracy matching to running time and service analyses, for example, by helping to confirm and perhaps explain long delays or indicating when the "everybody boards the first bus" assumption behind waiting time calculations is violated. While radio-based systems always benefit from this connection, it would also benefit passenger counting and event recording systems.
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From page 69...
... With a small fraction of the fleet instrumented, large sample sizes can still be obtained from crowded routes if the instrumented buses are disproportionately allocated to crowded routes. On the side of operations data, only near-100% penetration will provide the large sample sizes needed to determine extreme values used in statistically based running time analysis and design.
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Key Terms

  • waiting time
  • running time
  • radio channel
  • arrival time
  • extreme values

  • stop records
  • transit agencies
  • passenger waiting
  • apc data
  • polling data

  • avl data
  • stop location
  • designing avl
  • data offers
  • versus exception


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