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49 CHAPTER 6 Predicting Outcomes of Selected Strategies A menu of strategies airport operators can implement to models, airport parking models, and an airport parking fore- resolve ongoing public parking constraints or manage con- cast model developed based on the research conducted for strained parking events was provided in Chapter 5. Implemen- ACRP Project 10-06. tation of many of those strategies requires advanced planning and consideration of the impacts the strategy may have on Airport Mode Choice Models related issues, such as parking facility use, capital or operational costs, parking-derived revenue, vehicle traffic and emissions, A regional organization, such as an MPO, is often respon- and customer service. sible for regional travel demand forecasting, and may main- Implementation of strategies intended to resolve an ongoing tain a regional travel demand forecasting model. In some public parking constraint may require capital investment and cases, modeling efforts my be initiated by or coordinated with possibly executive or regulatory approval, whereas implemen- an airport operator to incorporate airline passenger O&D sur- tation of strategies to address shorter-term constrained parking vey data into the regional travel demand forecasting model. events tends to involve a lower level of effort and investment. This airport mode choice module can provide estimates of For those strategies that require more time and investment to changes in mode share and trip volumes based on various implement, decision makers need to understand whether the parking and transportation policy changes. Such a modeling strategies are likely to achieve the desired outcomes, especially effort requires significant input from the airport operator as within the framework of an airport operator's goals and objec- the entity most familiar with the ground access travel patterns tives for its parking program. of airport customers. The formal and informal tools and methodologies for pre- Of the 15 airport operators participating in this research dicting the outcome of strategies implemented to resolve ongo- project, 2 have developed this type of predictive tool--the ing constrained public parking are described in this chapter. Massachusetts Port Authority for BOS and the Port of Port- Some of these tools and methodologies may also be useful to land for PDX. These two examples are discussed in the follow- predict the outcome of strategies to manage short-term parking ing sections. constraints. This research project included the development and evalu- Logan Mode Choice Model ation of the usefulness of a formal predictive tool (i.e., a model) to assist airport operators in understanding the magnitude of The Boston Region MPO, Central Transportation Planning changes in parking behavior resulting from implementation of Staff, maintains and operates a regional travel demand model a strategy. Such a model could reveal unanticipated outcomes that encompasses the 101 cities and towns that form the that would influence decision making. The consequences of a Boston metropolitan area. This model has a nested airport lack of understanding of the potential outcomes in advance of mode choice model, referred to as the Logan Mode Choice strategy adoption and implementation can be severe. Model, which is used to estimate trips generated by BOS air- line passengers. This model is calibrated to airline passenger travel behavior using airline passenger O&D survey data col- Formal Tools lected every 3 years by Massport, owner and operator of BOS. Formal tools can be used to predict the outcomes of strate- The most recent calibration was completed in 2007. gies being considered to address constrained parking. Three The Logan Mode Choice Model is a multinomial nested formal tools are discussed in this section--airport mode choice logit model used to estimate access trips to BOS based on
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50 15 travel modes, consistent with the categories in the airline · A spreadsheet model that enables the Port of Portland to passenger O&D survey. These travel modes include detailed test scenarios related to changes in airline passenger ground information on private automobile use--use of the curbside access costs, travel times, and transit availability to determine only for pickup and drop-off, use of short-term parking for the change in trip distribution and mode choice to PDX. pickup and drop-off, or use of parking for the duration of the · An application code that is tied to the regional travel demand airline passenger's trip. The model produces an estimate of model and is used to estimate the outcome of certain strate- trips for the four main airline passenger customer segments-- gies related to parking, expansion of the regional transit sys- resident business, resident nonbusiness, nonresident business, tem, and other measures at the regional level. and nonresident nonbusiness. It incorporates trip character- istics that influence airline passenger airport access choices, The APDM is a multinomial nested logit model that esti- including trip duration, travel party size, number of bags mates trips for four airline passenger customer segments: resi- checked, whether an employer is paying travel costs for a busi- dent business, resident personal, visitor business, and visitor ness trip, and other factors that affect mode choice decisions. personal. Trips are distributed among 11 modes, which include The model can be used to (1) constrain BOS public parking long-term parking in each of the three on-airport parking facil- demand to the existing number of spaces; (2) estimate trips by ities as well as privately operated off-airport parking, and pickup mode at different parking rates; (3) estimate trips for different or drop-off in private automobile with and without the use of fares on HOV access modes; and (4) estimate the effects of short-term parking. The model was developed using approxi- changes in airport transit service, regional transit service, and mately 2,000 responses from passenger intercept surveys col- the regional highway system. This information is then used to lected from O&D airline passengers at PDX traveling during calculate estimated changes in VMT by airline-related passen- June and September 2008. Passenger intercept survey data indi- ger trips on local and regional roadways. cate that resident business travelers value their travel time twice Airport employee trips are not included in the Logan Mode as much as residents and visitors whose travel purpose is per- Choice Model. Trips generated by airport employees are esti- sonal. Visitors traveling for business valued their time the mated in the regional model; however, the regional travel most--2.5 times more than resident business travelers. demand model does not account for the unique trip patterns Airport employee trips are not included in APDM. Trips of airport employees. (1) generated by airport employees are estimated in the regional model, which does not account for the unique trip patterns of airport employees. Airport Passenger Demand Model The Port of Portland has tested multiple scenarios with its In fall 2009, the Port of Portland, owner and operator of spreadsheet model to determine how airline passenger mode PDX, finalized an update to the airline passenger ground access choices would shift with increases in parking rates, changes travel component of the regional travel demand model referred in costs of other travel modes, changes in travel times, and to as the Airport Passenger Demand Model (APDM). The MPO changes in the frequency of transit services. The results, shown maintains the regional travel demand model. The APDM was in Table 6, are illustrative of how the model can predict changes developed to provide the following: to assist the Port in determining the outcome of policy changes Table 6. Portland International Airport airline passenger mode share with application of different transportation policy scenarios. Policy Scenario Mode Shares Parking Charge Increase Increase Travel Time and Automobile Existing Double Operating Costs by 20%, Provide Free Mode Travel Transit at Double the Frequency, and Access Mode Share 10% 25% 200% Time Double the Parking Costs Drive and Park 34% 31% 27% 10% 37% 16% Pickup and Drop-off 33% 36% 39% 54% 25% 44% Taxicab, Limousine, Town Car 6% 6% 6% 7% 6% 6% Rental Car 17% 17% 17% 17% 17% 17% Shuttle 4% 4% 4% 4% 4% 4% Transit 6% 6% 7% 8% 11% 13% Total 100% 100% 100% 100% 100% 100% Source: Port of Portland, October 2009. (19)