Oakland Airport Connector Options Analysis Analysis of the Options
August 2010
Coming to the airport under any option, passengers would also want to budget extra time for the possibility of long check‐in and security lines (the airport recommends arriving a minimum of 90 minutes prior to departure and many airlines recommend 2 hours). When coming to the airport, budgeting extra time essentially means catching the next earlier BART train (which depending on the origin BART station and time of day, could leave 15–20 minutes earlier), and passengers would need to consider whether the small possibility of being, for example, 4 minutes late would be sufficient to leave 15 minutes earlier, particularly given time allowances for delays at the airport. Traveling from the airport, randomness in flight arrival times in relation to the schedule, baggage delivery times, and Connector arrival times at BART relative to the arrival of a BART train to one’s destination would make Connector travel time variability relatively unimportant.
RIDERSHIP Ridership in the year of opening (2013) was forecast based on the following factors: •
Base AirBART ridership for 2010, from the latest BART ridership forecast for the Oakland Airport Connector (3);
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Airport passenger growth to 2013 (from 8.8 to 9.6 million annual passengers), assuming Connector ridership grows proportionately to airport passenger volume;
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Ridership growth due to frequency improvements relative to AirBART;
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Ridership growth due to travel time improvements relative to AirBART, based on the complete BART trip (including time on regular BART trains); and
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Ridership growth due to rapid transit image.
Elasticity factors given in the BRT Practitioner’s Guide (10) and the Traveler Response to Transportation System Changes series of reports (15) can be used to estimate the change in ridership due to travel time and frequency improvements. For travel time, a midpoint arc elasticity of ‐0.4 was assumed (roughly stated, for every 1% reduction in travel time, ridership increases by 0.4%). For ridership, a midpoint arc elasticity of +0.2 for frequency was assumed, which roughly means for every 1% increase in frequency, ridership increases 0.2%. Because the existing AirBART service is already relatively frequent, a value toward the low end of the range of possible values was used. Certain transit modes will attract riders that are not attracted to local bus service. This phenomenon has long been known for rail modes, and is often incorporated into long‐range traffic forecasting models. A similar phenomenon has been documented for BRT, with full‐featured BRT routes showing up to a 25% increase in ridership beyond what would be expected from frequency and travel time improvements (10). The BRT Practitioner’s Guide (10) provides a method for estimating ridership growth due to the image of rapid transit, based on the number of BRT system features (e.g., type of running way, fare collection method, etc.) that are provided. This ridership growth is due to perceived comfort and reliability, branding, special vehicles, upgraded stations, ease of transfers, and other factors that generate additional ridership beyond that of a local bus with similar frequency and travel time characteristics. For Rapid Bus, 14% growth was used, while 22% growth was used for Full BRT. For AGT, 25% growth was assumed for this factor, based on a comparison of BART’s latest near‐term and long‐term low forecasts (3) to ridership growth due to frequency and travel time improvements. Kittelson & Associates, Inc.
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