Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 5, Vanpools and Buspools (2005)

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however, using 15-passenger vehicles classified as vanpools. The operator is seeking California tax relief legislation to make private operation of commuter services more financially attractive (Urban Transportation Monitor, 2000; Buspool.org, 2001; Peoples, 2004). UNDERLYING TRAVELER RESPONSE FACTORS The transportation service attributes offered to the commuter by vanpools and buspools lie in gen- eral between the attributes of carpools and conventional transit. Of concern to the potential van- pool and buspool participants are travel time, cost, convenience, and other tangibles and intangibles. For vanpooling and buspooling, travel time includes access time, wait time, pickup time or trip cir- cuitry, and line haul time. Pickup Time, Line Haul Time, and Trip Distance Vanpool and buspool riders generally experience longer travel times than they would if traveling via single occupancy automobile, though this may not always be the case in congested corridors or crossings with major HOV facilities or ferry access privileges. The generally longer times result from either vanpooling/buspooling on a circuitous route to pick up or drop off other riders, or having to travel to a pick-up location. Additional discussion of the influence of pickup time is pro- vided under “Related Information and Impacts”—“Indicators of Market Potential”—“Service Attractiveness Guidelines.” The average former auto commuter among Golden Gate vanpoolers and the average Maryland vanpooler (typically a prior auto user) endured 11 to 12 minute one-way travel time increases over their former commute. This is essentially the same as the 10 to 11 minute increases on average reported by 3M and Michigan State Government employer-sponsored vanpool programs, and the 10 minute average extra travel time of Southern California COM-BUS subscription buspools as compared to comparable auto commutes. Riders trade off travel time for the other travel attributes (Dorosin, Fitzgerald, and Richard, 1979; McCall, 1977; Owens and Sever, 1974 and 1977; Stevens et al., 1980; U.S. Department of Energy, 1979). These additional time penalties are less significant in the context of a longer trip. Indeed, the mar- ket for vanpooling is primarily commuters with longer-than-average commute distances, normally over 20 miles each way. Analysis of data in an early vanpool demonstration in Minneapolis revealed that among vanpoolers, the trip lengths of former transit users and solo drivers are considerably shorter than those of former carpoolers. Because the cost advantage of vanpooling over automo- bile travel increases with distance, eventually overtaking even the savings of multi-occupant car- pooling, this finding suggests rational economic behavior on the part of vanpoolers in their mode switching behavior (Heaton et al., 1981). Former transit users most often save time vanpooling. Golden Gate vanpoolers, for example, saved an average of 9 minutes over using transit (Dorosin, Fitzgerald, and Richard, 1979). When an HOV facility is available to lessen or even reverse the normal vanpooling time disadvantage, vanpooling becomes more attractive relative to solo driving. VPSI estimated that vanpools on the Shirley Highway HOV lanes in Washington, DC, area outnumber VPSI vanpools on the other radial freeways by a ratio of three to one (Comsis and ITE, 1993). The occupancy requirement on the Shirley HOV lanes is three or more persons (3+), higher than most. The 3+ occupancy requirement is possibly an additional inducement to vanpooling, as discussed under “Preferences, Privileges, and Intangibles.” 5-19

Access Considerations Vanpools and buspools may offer door-to-door convenience, or travel between centralized collection and distribution points, or combinations and variations thereof. There is an obvious trade-off between accepting circuitous, time-consuming route deviations to achieve or approximate home pickup, and requiring passengers to get themselves to a more efficient or even centralized pickup point. The early small city subscription bus demonstrations, of which only the Peoria operation continued past the demonstration period, relied almost exclusively on home pickup. Riders cited the conve- nience of door-to-door service as the overriding reason for use of these short-haul buspools (Pratt, Pedersen, and Mather, 1977). Some early employer vanpool programs had a similar focus, but fairly early on, programs began reporting more diverse access modes, as illustrated in Table 5-7. 5-20 Table 5-7 Means of Access to Vanpool and Buspool Programs of the Late 1970s Program Type Maryland Vanpools Knoxville Brokered Golden Gate Demoa Michigan Employees COM-BUS Southern CA Pickup Point Third Party & Owner-Op’r. Access Third Party Vanpools Third Party Vanpools Employer Van Program Buspool Home 19% Home 36% 44% 62% 5% Intersection 11 Walk 10 17 5 — Parking Lot 57 Auto 54 39 33 70 Other 13 Other — — 1 25b Notes: a First nine months of Demonstration Project; during bad weather. b Central pickup points (access unspecified). Sources: Dorosin, Fitzgerald, and Richard (1979); McCall (1977); Stevens et al. (1980); Pratt and Copple (1981). In the Pace Vanpool program of suburban Chicago, where free passes allow no-cost transfers to suburban buses, participants use a variety of modes to get to their vanpool. The primary Pace Vanpool access modes and percentages are shown in Table 5-8 (Pace Suburban Bus Service, 1993). Although no rigorous analysis has been done on it, home pickup may be somewhat more prevalent in smaller cities and regions. Mode Percentage Drive 38% Carpool 17 Walk 21 Home Pick-Up 19 Transit 5 Source: Pace Suburban Bus Service (1993). Table 5-8 Modes Used to Get to Pace Chicago Region Vanpool Pick-up Points

Work Scheduling Implications Vanpool and buspool users normally must adhere to a fixed commuting schedule. The worker who has to stay overtime is thus challenged. Even if work schedule aberrations are anticipated in advance, the only travel choice typically available is to forsake the vanpool or buspool mode for the occasion. This is probably a major reason, along with work absences, why the “attendance fac- tor” of these programs is typically 80 to 90 percent. Golden Gate vanpoolers rode 4 out of 5 days on the average. Seventy percent of 3M vanpool riders rode 5 days a week, 25 percent 4 days a week, and 5 percent 3 days or less a week (Dorosin, Fitzgerald, and Richard, 1979; Owens and Sever, 1974 and 1977). This irregular usage poses a dilemma in that the vanpool’s carrying potential is not maximized and therefore its per passenger costs are not minimized. Some programs have developed meth- ods to cope with irregular vanpool usage. One way is to over-subscribe; allowing lower monthly rates and assuming one or more persons will be away each day. Another way is to use trip-based pricing in conjunction with a low monthly base fee. Still another approach is to plan directly for part-time use—Connecticut’s Easy Street® allows 2 or 3 day a week subscriptions for part time workers (Alan M. Voorhees and Associates, 1974; The Rideshare Company, 1998; Suhrbier and Wagner, 1979). The requirement that vanpoolers pay for days that they miss as well as days that they ride has been cited as a detriment to vanpooling, especially during vacation periods. This is one reason Con- necticut’s Easy Street® program allows a rebate for passengers taking two consecutive weeks off (The Rideshare Company, 1998). For longer absences, most programs allow riders to leave the pro- gram with 30-days notice. There are support programs that may help to encourage vanpool use. Flextime is generally but not universally thought to be supportive of vanpooling and high occupancy vehicle use by allowing employees to better coordinate their schedules for ridesharing. A survey of commuter transporta- tion programs found that, circa 1990, ridesharers were offered flextime programs by their employer in 27 to 45 percent of all cases depending on type of service provider (see Table 5-9 for additional details) (Spence, 1990). An example of the contrary view about flextime comes from The 3M Com- pany, where managers speculated that high employee turnover, relocations, and the introduction of flextime were to blame for vanpool use declines (Bhatt and Higgins, 1989). To make riders more comfortable about leaving the car at home, many vanpool programs incor- porate a “guaranteed ride home” service. Such programs are addressed in Chapter 19, “Employer and Institutional TDM Strategies.” The service provides a ride to home or other destination in cases of emergency or unanticipated delay leaving work. The guaranteed ride may be provided by use of company or agency cars or fleet vehicles, short term auto rentals, or taxi services. Most programs limit the number of times per year each person may utilize the service, but maximums are rarely reached. Instead, the programs serve as a low cost mechanism for encouraging use of alternative transportation (K.T. Analytics, 1992). In a similar manner, the “straggler bus” of the original Reston Commuter Bus operation, run after the regular evening subscription service, encouraged use of the system by people that needed the assurance they would not be stranded at their workplace by a late meeting or other delay. Although actual ridership on this 7:00 PM bus varied between 15 and 20 passengers, its addition in 1970 attracted more than 80 new riders to the system as a whole (Furniss, 1977). 5-21

Incentives and User Costs Overall Use of Incentives The success of vanpool programs is heavily influenced by the degree of employer support, even in the case of third-party programs. A Pace Suburban Bus Service survey in 1993 found the employ- ers of most Pace VIP vanpool participants provided at least one incentive. Of survey respondents, 82 percent indicated that their employer provided preferred spaces for vanpools and carpools, 62 percent reported flexible working hours that permitted them to synchronize work schedules with fellow participants, 59 percent had employers who provided a way to advertise for additional riders, 49 percent were given information on public incentives by their employer, and 30 percent received subsidies for vanpool or transit from their employer (Pace Suburban Bus Service, 1993). Table 5-9 illustrates the prevalence of various ridesharing incentives, circa 1990, among companies and other organizations known to be involved in ridesharing program activities. 5-22 Table 5-9 Ridesharing Incentives Available to Program Participants Served Type of Organization Type of Incentive Non-Profits (TMAs; other ridesharing or commute manage- ment organizations) Private Companies (any entity offering commute programs to their employees) Public Agencies (all levels of govern- ment; regional bod- ies; transit agencies) Free rides for driver 44% 57% 44% Driver has weekend use of van 46 33 49 44 Flextime 45 27 Free parking 36 72 27 Guaranteed ride home 41 58 13 Subsidized bus/transit fares 31 48 17 Subsidized vanpool fares 36 48 19 Note: See the text which precedes Table 5-12, and the Table 5-12 note, for more information on the conduct of this survey. Source: Spence (1990). The percentages shown in Table 5-9 were derived from a nationwide survey of a wide variety of commuter transportation organizations. The percentages do not reflect the behavior of companies and organizations without ridesharing programs; they were excluded from the sample (Spence, 1990). No nationwide quantification of the effect on vanpooling of incentives was encountered, but findings of research on financial incentive effects for Puget Sound commuters are presented below in the “Financial Incentives in Greater Seattle” subsection. Prodded by Commute Trip Reduction regulations and assisted by associated legislation, 71 percent of Puget Sound area vanpoolers in a rideshare pricing research sample were receiving such incentives in 1997 (Wambalaba, Concas, and Chavarria, 2004). A 1999 market study found that 93 percent of Puget Sound’s transit provider vanpools serve “major employers involved in Commute Trip Reduction (CTR) programs” (WSDOT, 2000).

Financial Incentives at TVA Headquarters Relatively little quantitative information is available on effects of incentives on vanpooling. One classic case involving financial incentives is offered by the Travel Demand Management program of the downtown Knoxville headquarters of the Tennessee Valley Authority. In that 1970s case, a comprehensive TDM program was initiated without financial incentives other than avoidance of the existing pay parking. Then, in a separate and distinct action, financial incentives were pro- vided. Table 5-10 presents the before, after without incentives, and after with incentives results (Wegmann, Chatterjee, and Stokey, 1979). 5-23 Table 5-10 Results of TVA Knoxville Headquarters Ridesharing/TDM Program and the Provision of Financial Incentives Before TDM Nov. 1973 TDM, No Monetary Incentives- December 1974 TDM + Monetary Incentives January 1977 Employee Travel Mode Employee Mode Share Employee Mode Share Change Versus Before TDM Employee Mode Share Change Versus No Incentives Drive Alone 65.0% 42.0% -35.4% 18.0% -57.1% Carpool 30.0 40.0 +33.3 41.0 +2.5 Regular Bus 3.5 3.0 -14.3 3.0 0.0 Express Bus 0.0 11.0 n/a 28.0 +154.6 Vanpool 0.0 2.3 n/a 7.0 +204.4 Walk, Bike, etc. 1.5 1.7 +13.3 3.0 +76.5 No. Employees 2,950 3,000 +1.7% 3,400 +13.3% Parking Need 2,200 1,640 -25.4 1,070 -34.8 Note: Gasoline shortage occurred between November 1973 and December 1974, but not between December 1974 and January 1977. Source: Wegmann, Chatterjee, and Stokey (1979). The scale of the financial incentives TVA offered can probably be inferred from the one-third dis- count provided on commuter bus tickets. Carpools received preferred and inexpensive parking, and vanpools were subsidized for every TVA rider. The response to monetary incentives and associated additional express buses and vanpools had 2 years to stabilize before the January 1977 data collec- tion date, as compared to 1 year before December 1974 for the TDM program without monetary incentives. However, this was more or less counterbalanced by the occurrence of the first 1970s fuel crisis and gasoline shortage during the initial phase. As Table 5-10 illustrates, the incremental effect of the monetary incentives was greater for all modes except carpooling than the initial TDM pro- gram effect, including introduction of direct express bus service and the vanpool mode. The largest effect percentagewise was on the vanpooling share (Wegmann, Chatterjee, and Stokey, 1979). Financial Incentives in Greater Seattle Seattle Metro tested vanpool subsidies as part of a 1987–89 demonstration of directed marketing aimed at persuading suburban office park commuters to use alternatives to driving alone. Among

other tactics, Metro developed an Early Start Program to encourage and speed vanpool start-up, subsidizing empty seats while a full complement of passengers was being sought. This strategy was applied at two major employment centers, coupled with a one-month free subsidy to new van- poolers at one location, and a two-months-free subsidy to vanpoolers toward the end of the proj- ect at the other. By the end of the two-year demonstration, the number of known vanpools at these sites had in- creased from 6 to 24. Although the vanpool component was considered a success, third year proj- ect area surveys found that, overall, there had been no net change between 1987 and 1989 in the share of commuters in high occupancy vehicles. Reversion back to single-occupant commuting was shown to be the predominant post-demonstration response. It was concluded that a program of positive services and incentives could not make up for limited employer and employee interest in seeking commute alternatives (Comsis, 1991). Seattle region employer involvement was stimulated in the early 1990s by the coming together of a number of forces, including growing congestion affecting all parties, passage of Washington State’s Commute Trip Reduction and Growth Management legislation, associated “Concurrency Requirements” mandating adequate public facilities for new development and thus further en- couraging demand management, and regional policies favoring alternative transportation (Samdahl, 1999; WSDOT, 2000; Kavage and Samdahl, 2004). The impetus provided strengthens the now ongo- ing employer subsidy program for transit fares, vanpools, and other non-traditional commuter ser- vices administered by King County Metro for the Seattle region. The results provide some additional information on vanpooler response to monetary incentives. Metro now offers a family of payment instruments and commuter incentive programs for use in partnership with employers and other major generators, primarily educational institutions. As of the late 1990s, these included a Traditional Pass Subsidy Program, the Commuter Bonus Program, and FlexPass. Vanpoolers can apply the face value of their subsidized traditional pass against their van- pool fare. The Commuter Bonus Program provides vouchers that can likewise be applied to vanpool fares among several other options. The FlexPass Program is an umbrella program providing an annual transit pass, vouchers, and other benefits. The FlexPass provides a predetermined vanpool fare discount (Michael Baker et al., 1997). The FlexPass Program and transit rider response to it are described in Chapter 12, “Transit Pricing and Fares,” under “Response by Type of Strategy”—“Changes in Fare Categories”—“Unlimited Travel Pass Partnerships.” There in Table 12-16, seven selected King County Metro employer FlexPass programs are examined in terms of their offerings and the before and after mode shares associated with their implementation, including the reduction in single occupant driving. The van- pool subsidies at the seven companies ranged from $40 per month to full subsidy. The overall increase in vanpool usage for the five companies reporting vanpool shares was approximately 70 percent (King County Metro, 1998). Not included in this average is the case of Microsoft, in Redmond, Washington, where a full-subsidy FlexPass program was initiated in 1996 for 16,000 employees and contractors (up to over 21,000 in October 1998). Results included formation of 35 new vanpool groups as of 1998, where before there had been none known of (King County DOT, 1998). National Center for Transportation Research (NCTR) investigators have attempted to quantify for Puget Sound commuters the effect on vanpool mode choice of financial incentives. Their research used employer surveys and employee travel data generated by Washington State’s Commute Trip Reduction program requirements. Over 200,000 employee travel choice observations from 1997 5-24

were analyzed along with a lesser number from 1999. Among the 1997 observations, 1.98 percent of employees were vanpooling, and of these, 71 percent received vanpool subsidies. Regression and logit models were developed. The formulations included both a vanpool cost variable and a yes/no variable indicating whether there was a rider subsidy available, with similar variables for other travel modes, and a demographic variable addressing work status. A vanpool subsidy odds ratio of 1.089 was estimated from the 1997 data set, meaning that user sub- sidies were estimated to increase the likelihood of choosing the vanpool mode by 8.9 percent. The comparable odds ratio estimated from the smaller 1999 data set was 2.79, implying an increase of 179 percent in the likelihood of vanpooling with rider subsidy. The researchers concluded, based on statistical tests, that the magnitude of subsidy impact could not be reliably estimated. However, they found the results to be sufficient evidence of a positive impact (Wambalaba, Concas, and Chavarria, 2004). Sensitivity to Fare Changes Evidence concerning the related matter of sensitivity of vanpool and buspool ridership to fares is from the late 1960s and 1970s on one hand, and from the recent NCTR research on the other. Available investigations present a varied picture, one in which some reports and research results indicate little or no sensitivity to fares, but other reports and results strongly suggest a high van- pool fare elasticity, even into the elastic range in some instances. Overall, it seems reasonable to conclude that while vanpool fare elasticities may vary widely, their average is in the inelastic range but significantly larger than—indeed roughly double—the −0.4 average for local bus transit fare changes.4 In the late 1970s, a 20 percent fare increase for Commuter Computer vanpoolers in Southern California led to a 14 percent drop-off in vanpooling among those not receiving a subsidy. This equates to a fare elasticity of −0.83. Among the vanpoolers directly subsidized by ARCO, a major employer, the drop-off was only 3 percent. The ARCO vanpooler subsidy was set equal to their estimate of parking subsidy savings: $22.00 per employer per month at the time (Suhrbier and Wagner, 1979). In Peoria, although a survey of buspool riders indicated that convenience, timing, speed and relia- bility were more important than price, a subsequent 21 percent fare increase, accompanied by a reduction in passenger amenities, resulted in a 21 percent decrease in ridership. In contrast, there was no evidence that incremental fare increases to cover increased costs had identifiable impact on ridership in any of the long-haul commuter buspool operations of the era (Pratt and Copple, 1981). The NCTR research already described obtained fare elasticities for vanpool ridership of −0.61 from the 1997 Puget Sound employer/employee dataset, −1.34 from the smaller 1999 dataset, and approx- imately −1.14 from a separate nested logit model fare elasticity analysis. The data set was structured 5-25 4 A fare elasticity of −0.4 (the average for bus transit fare changes) indicates a 0.4 percent decrease (increase) in ridership in response to each 1 percent fare increase (decrease), calculated in infinitesimally small increments. The negative sign indicates that the effect operates in the opposite direction from the cause. An elastic value is −1.0 or beyond, and indicates a demand response that is more than proportionate to the change in the impe- tus. (See “Concept of Elasticity” in Chapter 1, “Introduction”; Appendix A, “Elasticity Discussion and Formulae”; and also “Response by Type of Strategy”—“Changes in General Fare Level” in Chapter 12, “Transit Pricing and Fares.”)

such that these findings pertained to change in daily cost of vanpooling before application of any user subsidy. The point elasticity computation method was employed (Wambalaba, Concas, and Chavarria, 2004). Taken together, the Puget Sound results suggest a vanpool fare elasticity more or less on the cusp of elastic response, where a percentage decrease in fares results in a roughly equal percentage increase in ridership. The 1970s Peoria buspool case is an example of such a response, except that example is clouded by the simultaneous reduction in special rider amenities. NCTR researchers also calculated mid-point elasticities for vanpooling in other regions, utilizing ridership and fare data furnished by transit providers. Both short-term and so-called “long-term” elasticities were computed for two separate fare increases by the VanGo operation in the greater Denver-Boulder area of Colorado, making adjustments for exogenous employment factors. In this region, there were no mandatory trip reduction regulations in the applicable 2000–02 time period. Roughly 1⁄4 to 1⁄3 of riders received some form of subsidy. Computed short-term elasticities ranged from −0.3 to −1.7, averaging −0.8. The “long-term” elasticities for both fare increases were each close to −0.6 (Wambalaba, Concas, and Chavarria, 2004). The “long-term” elasticities appear to be for time spans that would, in typical transit fare elasticity evaluations, be considered “mid-term” at most. The vanpool operation of the transit agency VOTRAN in Volusia County, Florida, sustained an average growth rate of some 74 percent during the FY 1998/1999 through FY 2002/2003 period. There was a monthly fare change from $28 to $30 in 2000. Looking only at the ridership of three vans that were in operation both before and after the change, representing 21 percent of the fleet at the time, a fare elasticity of −1.7 was computed. Elasticity computations were also made for the LYNX operation in the Orlando area. Here the results ranged from +4.7 to −2.0 (Wambalaba, Concas, and Chavarria, 2004). In both of these cases, small samples, upward growth trends, and other exogenous factors make the fare elasticity results of questionable value except as a demon- stration of the variability possible. The NCTR researchers make the point that vanpoolers face the problem that if a fare increase causes a vanpool member to drop out, the cost no longer covered by that rider may have to be dis- tributed among the remaining riders, creating a “double whammy” effect. They note that un- subsidized vanpool fares are generally fairly large, such that a change is quite noticeable, and also that vanpool riders tend not to be captive riders without other options (Wambalaba, Concas, and Chavarria, 2004). These factors would all explain relatively high fare sensitivities. Looking at the available findings, and giving extra weight to the recent and less problematical Puget Sound area and Denver-Boulder VanGo results, average vanpool fare elasticities seem to mostly fall in the zone of −0.65 to −0.95, but with individual vanpool and buspool results ranging from no discern- able impact to elastic response. Preferences, Privileges, and Intangibles When Pace VIP vanpoolers were asked what they liked most about the vanpool program, they gave convenience, cost savings, and avoiding driving as the top responses (15 percent each). Other survey respondents cited “less stress” and social aspects of the vanpool as being most important. Liked least was the constraint of a fixed schedule, the van itself, and the fare schedule (21 percent, 15 percent, and 11 percent of respondents, respectively) (Pace Suburban Bus Service, 1993). Vanpool response is affected by the personalities of the driver and the riders. It has been stated that for a vanpool to become permanent, it must establish its own social identity and pattern of 5-26

personal relationships. Twelve percent of Pace survey respondents reported the social aspects of the vanpool to be what they most liked about the mode. The driver is a key to the success of a long- lived vanpool, with commitment, affability, leadership, and driving skills being cited as prerequi- site characteristics. In the Pace vanpool survey, 92 percent of respondents indicated satisfaction with driver performance (Suhrbier and Wagner, 1979; Pace Suburban Bus Service, 1993). All vanpools have the privilege of using any HOV facility open to carpools, plus the few open only to buses and vanpools. This is true, for all practical purposes, whatever the carpool occupancy requirements of the HOV facility. Nevertheless, this privilege may mean more when the HOV facil- ity occupancy requirement is high enough to make carpool formation more bothersome than the minimum difficulty. Circumstantial evidence of this effect is provided by the sharp drop in van- pooling recorded when the occupancy requirement on I-66 in the Virginia suburbs of Washington was dropped from three or more occupants (3+) to two or more (2+), and when the occupancy requirement on the Katy Freeway in Houston was progressively lowered from buses and vanpools only to 2+ carpools. The circumstances are described and the outcomes are tabulated in Chapter 2, “HOV Facilities” under “Traveler Response by Type of HOV Application”—“Response to Changes in Vehicle Occupancy Requirements”—“I-66, Northern Virginia” and “Katy (I-10W) HOV Lane, Houston.” On I-66 in Virginia, average vehicle occupancy (AVO) on the facility was only moderately affected by the occupancy requirement change from 3+ to 2+, declining 11 percent in the AM peak period. However, the corresponding number of vanpools dropped by 25 percent, from 102 to 77 (Virginia Department of Transportation, 1996). The peak one hour drop in I-66 vanpools was 42 percent, a statistic that is perhaps suspect, as all of the 25-van peak period vanpool decline is shown as apply- ing to the peak one hour traffic count. The situation on the Katy (I-10W) Freeway HOV lane in Houston is more complex, as vanpooling in Houston was already in precipitous decline during the entire 1980s time period of interest. Houston vanpooling fell victim to the 1980s collapse of energy prices, recession in the local energy industry, and abandonment of vanpooling programs by affected employers. The Katy HOV lane AM peak one hour vanpool count started at 66 when the facility opened in 1984 as a bus and vanpool lane only, increasing to 68 vanpools 6 months later. (Specially autho- rized 4+ carpools were allowed on at that time, but only 3 peak-hour carpools took advantage.) From then through 1986, as occupancy requirements were progressively loosened, vanpool vol- umes dropped by 44 percent, to 38 vans in the AM peak hour. This decline was 23 percentage points more than the corresponding reduction in Houston vanpooling, which was down 21 per- cent (estimated) during the same period. The 23 percentage point differential between the Katy HOV lane percentage decline in vanpooling, and the less precipitous decline for Houston as a whole, held again in 1987. At this point, the Katy HOV lane AM peak hour vanpool count was 21 vans. Then in 1988, after the carpool occupancy requirement was raised from 2+ to 3+ in response to congestion, AM peak hour vanpool volumes increased to 24 vans after 6 months and 28 vans after one year, a 33 percent recovery. This recovery, although it brought Katy Freeway vanpool trends back in line with Houston trends (and possibly more), failed to stem long-term decline in Katy Freeway HOV lane use by vanpools. The peak hour vanpool vehicle count was back down to 19 vans after another 6 months, where it more or less sta- bilized for some time, as illustrated by the Chapter 2 tabulations (Christiansen and Morris, 1990, with unpublished worksheets; Texas Energy, 1978–88; Stockton et al., 1997). 5-27