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Pages 28-33

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From page 28...
... TR N EW S 30 3 M AY –J UN E 20 16 28 The author is Associate Professor, Geography and Planning Department, State University of New York at Albany. Data and information technology are not onlytransforming the way that people use busesbut also the way that bus systems are being planned to serve riders more effectively.
From page 29...
... TR N EW S 303 M AY–JUN E 2016 29 Types of Data To answer these questions, operators traditionally have relied on "paper and pencil" data collection programs. For example, traffic checkers can collect three types of data: u Ride checks: the number of passengers getting on and getting off and the time for each stop; u Point checks: a record of the time, the number of passengers getting on and off, and of passing buses at a particular point; and u Fare checks: an onboard record of each passenger's fare category when boarding at a bus stop.
From page 30...
... TR N EW S 30 3 M AY –J UN E 20 16 30 destination matrices. These data also can inform fare policy strategies and facilitate revenue modeling.
From page 31...
... TR N EW S 303 M AY–JUN E 2016 31 Microtransit is not an on-demand car and not a scheduledbus but fills a gray area in between. The Kansas City Area Transportation Authority (KCATA)
From page 32...
... TR N EW S 30 3 M AY –J UN E 20 16 32 GTFS-Realtime, or GTFS-R, for an on-screen display of buses traveling in real time. Universal access to GTFS, including the instructions, is available via the Internet.
From page 33...
... TR N EW S 303 M AY–JUN E 2016 33 microsimulation routing engine. Bus riders take microsimulated trips in Open Trip Planner based on the GTFS schedule, as if they were using their smartphones to navigate their way to work via the bus.

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