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not contradict the vehicle trip reduction basis for this estimate, though a slow, steady growth of telecommuting has been seen. The trip timing decisions employees make when given the option of flexible work hours have been found in most cases to be as effective as mandatory staggered work hours in spreading out work arrival and departure times, although the 1980s Bishop Ranch and Pleasanton suburban programs in California stand as exceptions. A large-scale urban program could smooth traffic peaks enough, in the 1970s, to reduce maximum 15-minute passenger and vehicular loads by 15 to 35 percent at terminal facilities such as rapid transit stations and major parking lots. The effects dissipate, becoming diluted by 50 percent or more, on radial facilities serving the involved employment core. It is not known to what extent the gradual adoption of flexible work hours in recent years may have reduced the remaining potential for peak spreading by shifting the baseline starting point for con- centrated alternative work arrangements programs. Site-Specific and System-Level Impacts Site-specific impacts are the focus of this chapter, but it is important to understand the relationship with area-wide, regional, and system-level impacts of employer TDM programs. As one moves from the site level toward the broader area-wide or regional transportation facility level, dissipation of site-specific impacts occurs. Effectiveness is leveled out among differing participating employers and institutions, averaging out big and small employers and high- and low-effectiveness programs. Participating employer commuting is mixed in with commuting to and from non-participating employers. Mixing also occurs with passenger and vehicular flows associated with non-work activ- ities either at the site or at other nearby land uses. Further leveling-out of impacts occurs as locally generated trips become mixed on specific facilities with other intra-regional travel and even intercity travel in the case of major highways. A limited number of estimates have been made of actual and potential regional and system-level impacts of employer and institutional TDM strategies. In the Minneapolis-St. Paul airport area, for example, it was estimated that TDM with limited mandatory involvement and strong parking man- agement combined with mixed-use development would offer an 8 to 27 percent VTR at participat- ing sites, a 6 percent average workplace VTR, and a 2 percent peak-traffic reduction on adjacent I-494. Another examination of potential regional impact calculated that only 13 percent of daily VMT would be affected by a mandatory TDM program, and went on to estimate that a 25 percent increase in average vehicle ridership (AVR) at involved employment sites would produce a 2 to 3 percent reduction in regional vehicle trips and a 3 to 4 percent decrease in regional VMT. An eval- uation of actual 2003 Commute Trip Reduction (CTR) mandatory TDM program effects along an 8.6 mile centrally located section of I-5 in Seattle estimated that the average VTR at 189 involved employers was between 11 and 14 percent. Traffic simulation was then used to project that absent the TDM programs, peak-period I-5 ramp volumes would increase by about 4 percent, peak-period traffic congestion would be up from 23 to 44 percent, and corridor peak-period vehicular emissions would rise on the order of 11 percent. RESPONSE BY TYPE OF TDM STRATEGY This section examines the response of travelers to implementation of various employer and institu- tional transportation demand management (TDM) strategies. To the extent possible, what is known as to the effect of individual strategies on such key travel measures as vehicle trip generation/ 19-15

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trip reduction, vehicle miles of travel, mode split changes, vehicle occupancy, or time of day/ frequency--where relevant--is reported. Historically, TDM response findings have been difficult to derive in this detail, since strategies are frequently implemented in often unique groupings or packages, are not monitored in a manner that facilitates travel impact research, and may be changed or offered to different groups of employees. As noted earlier in the "Analytical Considerations" subsection, the approach that has been used by the Handbook authors to explore the relationships between particular types of TDM strategies and traveler behavior depends heavily on the detailed examination of a sample of 82 employer and institutional TDM programs (the 82-program sample). These project examples have been drawn primarily from three separate research studies, selected for comparable detail on program descrip- tion and measurement of travel impact. A listing of these individual programs, along with the employer characteristics, TDM strategies encompassed, and computed travel impact, is provided as Appendix Table 19-A. Travel impacts in this analysis are gauged by the inferred change in average vehicle trip rate. The vehicle trip rate is the number of vehicle trips made by the employees commuting to a given work site in relation to the total person trips to the site, expressed in Appendix Table 19-A in the form of average daily vehicle trips per employee. (See Footnote 1 in the "Analytical Considerations" dis- cussion above for alternative vehicle trip rate units of measurement.) By comparing the vehicle trip rate of the employer with the TDM program relative to the vehicle trip rate measured either before implementation or as some other control rate representing background conditions, one may interpret the change or difference in trip rate as a vehicle trip reduction (VTR) attributable to the TDM program. Control rates employed by the source studies include a similar employer in the adjacent area, the average performance for a sample of employers in similar physi- cal settings, or the average vehicle trip rate for the local area derived from modal split information in the Census Transportation Planning Package (CTPP) for the nearest comparable time period. Even though the sample of projects used for this assessment is viewed as the most robust data resource available in terms of program detail and impact measurement, the types of analyses and conclusions it allows are still quite limited. There are also important caveats to keep in mind when making use of findings drawn from it. These were enumerated at the conclusion of the "Analytical Considerations" subsection within the "Overview and Summary." The basic analysis consists of comparing VTR for a group of employers who have a particular TDM element with those who do not. For this comparison to be statistically valid at demonstrating the actual effect of the given element, it would be necessary to assume that everything else about the two groups being compared is the same, apart from this element. Clearly, this is a big assumption given the diversity of the examples highlighted in Appendix Table 19-A. In very large samples (as in epi- demiological studies), the randomness with which these other characteristics occur can be assumed to produce fairly comparable samples, and hence determining whether the difference between the means is real can be addressed with statistical reliability tests. In the case at hand, however, a rela- tively large sample of TDM programs is still small statistically in terms of all of the sources of inter- nal and external variance, particularly given the small number of observations in some analysis cells. As a result, the relationships presented here should be regarded as primarily descriptive, although in some instances the differences are so great that one may begin to suggest that the particular ele- ment surely must be influencing the outcome. The nature of this analysis is to begin to show what types of actions appear to be the most influential, and what underlying factors may complement or detract from the inferred effect. 19-16