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December 27, 2006

Origin and Destination Estimation In New York City with Automated Fare System Data

[Syndicated from CiteULike: fruminator's library]

Transportation Research Record, Vol. 1817 (2002), pp. 183-187.

New York City Transit's automated fare collection system, known as MetroCard, is an entry-only system that records the serial number of the MetroCard and the time and location (subway turnstile or bus number) of each use. A methodology that estimates station-to-station origin and destination (O-D) trip tables by using this MetroCard information is described. The key is to determine the sequence of trips made throughout a day on each MetroCard. This is accomplished by sorting the MetroCard information by serial number and time and then extracting, for each MetroCard, the sequence of the trips and the station used at the origin of each trip. A set of straightforward algorithms is applied to each set of MetroCard trips to infer a destination station for each origin station. The algorithms are based on two primary assumptions. First, a high percentage of riders return to the destination station of their previous trip to begin their next trip. Second, a high percentage of riders end their last trip of the day at the station where they began their first trip of the day. These assumptions were tested by using travel diary information collected by the New York Metropolitan Transportation Council. This diary information confirmed that both assumptions are correct for a high percentage (90%) of subway users. The output was further validated by comparing inferred destination totals to station exit counts by time of day and by estimating peak load point passenger volumes by using a trip assignment model. The major applications of this project are to describe travel patterns for service planning and to create O-D trip tables as input to a trip assignment model. The trip assignment model is used to determine passenger volumes on trains at peak load points and other locations by using a subway network coded with existing or modified service. These passenger volumes are used for service planning and scheduling and to quantify travel patterns. This methodology eliminates the need for periodic systemwide O-D surveys that are costly and time-consuming. The new method requires no surveying and eliminates sources of response bias, such as low response rates for certain demographic groups. The MetroCard market share is currently 80% and increasing. MetroCard data are available continuously 365 days a year, which allows O-D data estimation to be repeated for multiple days to improve accuracy or to account for seasonality.

May 16, 2007

What, me Published?

Well, not really. But some ideas that I helped develop and data I helped gather/generate were recently written up in this paper from the Harvard Business Review on Big Seed Marketing by my pals Jonah Peretti and Duncan Watts. The basic idea, embodied in the open source ForwardTrack project I helped create, is, as Kottke says:
Instead of relying purely on viral marketing or mass media marketing alone, big-seed marketing combines the two approaches so that a large initial audience spreads the marketing message to a secondary audience, yielding more overall interest than either approach would have by itself, even if the message isn't that contagious. "Because big-seed marketing harnesses the power of large numbers of ordinary people, its success does not depend on influentials or on any other special individuals; thus, managers can dispense with the probably fruitless exercise of predicting how, or through whom, contagious ideas will spread."

While I was not listed as an author in the HBR paper, I am listed on the as yet unpublished version on Dr. Watts' web site (abstract).

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