National Academies Press: OpenBook
« Previous: Response by Type of Strategy
Page 21
Suggested Citation:"Underlying Traveler Response Factors." National Academies of Sciences, Engineering, and Medicine. 2004. Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 9, Transit Scheduling and Frequency. Washington, DC: The National Academies Press. doi: 10.17226/23433.
×
Page 21
Page 22
Suggested Citation:"Underlying Traveler Response Factors." National Academies of Sciences, Engineering, and Medicine. 2004. Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 9, Transit Scheduling and Frequency. Washington, DC: The National Academies Press. doi: 10.17226/23433.
×
Page 22
Page 23
Suggested Citation:"Underlying Traveler Response Factors." National Academies of Sciences, Engineering, and Medicine. 2004. Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 9, Transit Scheduling and Frequency. Washington, DC: The National Academies Press. doi: 10.17226/23433.
×
Page 23

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

9-21 ridership, the system actually faced a 16 percent loss (Finn, 1997). Further exploration of the effects on VRE and other commuter rail ridership of service reliability problems, changing conditions on parallel transportation facilities, and other external factors is found in Chapter 8, “Commuter Rail.” The impact of strikes on transit ridership was the subject of a time-series analysis of the effects of major incidents on ridership in Orange County, California, including the 1979 gasoline shortage and transit strikes of 1981 and 1986. The work underscores the long-term effects a prolonged strike can have on transit ridership. The gasoline shortage caused a temporary 20 percent increase in ridership which only lasted as long as the shortage. The 1981 6-week work stoppage caused a 20 percent decrease in ridership and a prolonged multi-year negative effect on ridership levels. A shorter work stoppage in 1986 caused a similar decrease, but ridership levels returned close to normal relatively quickly (Ferguson, 1991). For an analysis of impacts during a strike, see the case study “Impacts of a Bus Transit Strike in the San Francisco East Bay Cities,” in Chapter 10, “Bus Routing and Coverage.” UNDERLYING TRAVELER RESPONSE FACTORS Wait and Transfer Time Savings Service frequency changes affect the time a transit patron must wait for service, both initially and at transfer points. Increasing the frequency reduces these wait times and makes transit a more attractive travel mode. Studies of urban travel behavior show that the travel time implications of travel alternatives are a highly important determinant of consumer choices. For urban area travel to and from work, overall travel time savings are valued at roughly one-third to one-half of the wage rate, on average. The value depends on the choice situation involved, such as mode choice and path choice. Non-work travel time savings are usually valued less (Charles River Associates, 1997). Not all components of travel time are equal in value per minute as perceived by the trip maker. Time components of the complete trip that are often referred to as the “out-of-vehicle time” are the time spent getting to and from motorized transport or waiting for the vehicle to arrive or depart. These appear to be more onerous than the time actually spent in the vehicle, the so-called “in-vehicle time.” Typically, reductions in out-of-vehicle times are more highly valued than reductions in in-vehicle times, and thus more strongly affect consumer choice of mode. This finding has important service design implications Travel demand research done using various modeling techniques has for some time suggested that transit wait time, transfer time, and walk time lumped together as “out-of-vehicle time” may be at least on the order of twice as important in mode choice as an equal time spent in the transit vehicle (Quarmby, 1967; Shunk and Bouchard, 1970; Schultz, 1991). More recent modeling efforts, utilizing advanced techniques and protocols for more precise treatment of out-of-vehicle time components, are divided between identifying out-of-vehicle time as being twice as important or four times as important as in-vehicle travel time. In the roughly twice as important category (basing out-of-vehicle time importance on the first 4.5 or more minutes of waiting for the initial bus, journeying to or from work) are Houston at 2.58 times in-vehicle time, Portland at 1.25 times and Cleveland at 2.13 times (Barton-Aschman, 1993; Kim, 1998; Parsons Brinckerhoff, 1998). In the roughly four times as important category, using the same basis of comparison, are

9-22 Minneapolis-St. Paul at 4.36 times and Chicago (bus and rapid transit) at 3.41 times (Parsons Brinckerhoff, 1993 and 1999). Table 9-9 gives the relative weights on travel time exhibited by the Minneapolis-St. Paul mode choice model. In this model, the relative importance of transfer wait time must be taken together with the importance of the penalty associated with each transfer to judge the degree to which travelers view transferring as undesirable. (Transfer penalties are examined further in Chapter 10.) Similarly, the relative importance of initial (non-transfer) wait time must be judged by taking the values for the first 7.5 minutes together with the values for additional wait time (Parsons Brinckerhoff, 1993). Table 9-9 Relative Importance of Minneapolis-St. Paul Model Travel Time Components Trip Purpose Running Time Initial Wait (First 7.5 min.) Initial Wait (Over 7.5 min.) Transfer Wait Time Added Penalty per Transfer Home-Work 4.36 0.88 4.36 none Home-Other 4.00 10.78 3.77 17.27 Non-Home Based, Work Related 1.0 1.0 1.0 4.00 2.50 27.28 Non-Home Based, Non-Work Related 1.0 4.00 4.00 7.63 1.58 121.05 Notes: All values are normalized to minutes of running (in-vehicle) time. Relative importance values of 4.00 (four times as important as running time) are assumed on the basis of the home-work model calibration results. All other relationships are “originally estimated” using the 1990 Minneapolis- St. Paul survey data. Source: Parsons Brinckerhoff (1993). Note that in the case of the Minneapolis-St. Paul model, the time over 7.5 minutes is not viewed as even as important as running time by work trip commuters. This outcome is presumably because commuters know the schedule and can avoid a long time at the bus stop. Conversely, travelers making trips likely to be less repetitive and more discretionary apparently find the longer waits increasingly onerous, as indicated by the “Initial Wait over 7.5 Minutes” values in Table 9-9 for home-other (non-work) trips and non-home based non-work related trips. An examination of over 50 work purpose travel demand models from throughout the United States found each minute of transit wait time to average 2.12 times as important as a minute of in- vehicle travel time. Ranges were from 2.72 average for urban areas under 750,000 population to roughly 2.0 for larger cities, and from 2.48 average for 1990s models to about 2.0 for older models (U.S. Environmental Protection Agency, 2000). Newer models often afford differentiation among the out-of-vehicle time components. This capability provides mixed indications, but as discussed further in Chapter 10, transfer wait is most often shown to be of greater importance than the overall initial wait. If transit service is reasonably reliable, passengers can reduce the impact of the initial wait time by adjusting their time of arrival to more closely coincide with the transit schedule. Transfer waits, in contrast, cannot be controlled by the passenger. (The several references to Chapter 10 in this discussion refer specifically to the “Running, Walk and Wait Time” subsection within the “Underlying Traveler Response Factors” section of Chapter 10, “Bus Routing and Coverage.”)

9-23 There is some indication that out-of-vehicle times tend to be more important for non-work travel than for work purpose travel, as suggested by the values in the Minneapolis-St. Paul model presented in Table 9-9 when taken together. The recent Portland, Oregon, mode choice model offers additional and straightforward evidence. In the Portland model, the various out-of-vehicle time components range from 1.25 to 2.46 times as important as running time for work trips (see Chapter 10), as compared to 2.67 times as important for non-work trips (Kim, 1998). This finding suggests that off-peak service design in particular needs to focus on minimizing out-of-vehicle times, either by lessening them or somehow mitigating their effect. Physical, Operating and Economic Environment The effects of waiting time are influenced by a number of external factors. One of these is the physical environment. For instance, protection from weather in wet, hot, or cold climates makes a difference in a rider’s perception of waiting and transfer times. Seasonal variations in ridership can perhaps be attributed in part to differences in the waiting environment (Webster and Bly, 1980). Circumstantial and anecdotal evidence suggest that image and the general operating environment may affect response to frequency improvements. A disappointing ridership response in Charlottesville, Virginia (elasticity of +0.33) occurred in the environment imposed by old and unreliable buses among other problems described under “Response by Type of Strategy” — “Bus Frequency Changes” — “More Recent Experience” (SG Associates and Transportation Behavior Consultants, 1982). In contrast, the outstanding responses to service hours and frequency enhancements in Santa Clarita and Santa Monica, California (elasticities of +1.14 and +0.82) were accompanied by aggressive marketing ranging from direct mail campaigns and free- ride coupons to image building keyed to a striking new bus paint design (Stanley, 1998; Catoe, 1998). Economic conditions may likewise influence the extent of response to service frequency enhancements. The few cases where local economic conditions have been reported tend to suggest that poor economic environments may be associated with dampened ridership responses to frequency improvements, whereas a booming local economy may be a factor in heightened response (Mass Transportation Commission et al., 1964; Catoe, 1998). Even if there is not a direct impact on sensitivity to service improvements, superimposition of an average traveler response onto downward or upward trends will produce differing results. With respect to service frequency reductions, there is no consistent evidence concerning effect of economic conditions. Looking to the future, the information made possible by Intelligent Transportation Systems (ITS) technologies offers potential for reducing rider uncertainty about wait times, holding out the possibility of making transit use more attractive even where reliability improvements are impractical. A completed trial application in London tied automatic vehicle location (AVL) Transit wait time becomes more important when the trip is short and easily substituted for by another mode, typically walking. Commuters will opt for the other mode or walk to the destination rather than wait for an infrequent bus. In the downtown Chicago area, surveys showed travelers were more willing to walk than to wait for a special shuttle from the rail stations, because walking was an easy alternative (Kurth, Chang and Costinett, 1994). Mixed experiences with connecting peripheral parking to downtowns with bus shuttles exhibit similar phenomena (see Chapter 18, “Parking Management and Supply” — “Response by Type of Strategy” — “Peripheral Parking around Central Business Districts”).

Next: Related Information and Impacts »
Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 9, Transit Scheduling and Frequency Get This Book
×
 Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 9, Transit Scheduling and Frequency
Buy Paperback | $20.00
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

TRB’s Transit Cooperative Research Program (TCRP) Report 95: Chapter 9 – Transit Scheduling and Frequency examines scheduling changes made to conventional bus and rail transit, including changes in the frequency of service, hours of service, structuring of schedules, and schedule reliability.

The Traveler Response to Transportation System Changes Handbook consists of these Chapter 1 introductory materials and 15 stand-alone published topic area chapters. Each topic area chapter provides traveler response findings including supportive information and interpretation, and also includes case studies and a bibliography consisting of the references utilized as sources.

READ FREE ONLINE

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!