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UNDERLYING TRAVELER RESPONSE FACTORS ! " ! # $ % ! ! & ' ! $ ! ( ) * + % & ' $ , ! !! $ !! ! Change in Service Parameters , ! !! - - ! $ ! ! * + . ! ! $ ! ! / 0 !! * 123+$ *4 5!2637+ $ !! 8 *9+! ! $ ! 4 9 $! $ ! ! ! *. &:! , ! ! 0 ' $+
6-26 Change in Dispatching Technology or Procedures The availability of ever more powerful desktop computers has permitted the advance reservation time to be reduced. Several software packages that provide either full or partial automation of the vehicle routing/dispatching problem are now in use. These systems enable agencies to at a minimum adhere to the âno more than one day advance reservationâ requirement for complementary paratransit services offered to comply with the Americans with Disabilities Act. More advanced dispatching systems, coupled with automated vehicle location (AVL) systems that keep track (in real time) of the position of each vehicle in a paratransit system, offer the promise of real-time dispatching so that call-ahead times can be reduced from days or hours to minutes. Reductions of this magnitude in the required âpre-bookingâ time could be expected to have a greater effect on demand than changes in the number of days in advance of a trip that a reservation must be made, since impulse trips could be accommodated, truly reducing need for travelers to pre-schedule activities. One demand responsive operations software system under development will allow on-board computers to âtalkâ to each other and âbidâ for an incoming trip request based on cost to serve it (Casey et al, 1998). Interestingly, this is what the drivers of the Kosciusko Area Bus Service in Warsaw, Indiana do by radio, such that their operation may presage the service (and response) that will be possible on a larger scale with Advanced Public Transportation Systems. The Kosciusko Area Bus Service, with an annual rider per capita rate to 6 to 7 trips, has a high ridership rate compared to most other systems, but there may be a number of reasons for this. (See âResponse to General Public, Urban Demand for Kosciusko Area Bus Service operational and patronage information.) A stated preference survey and modeling analysis involving riders of a dial-a-ride service provided for senior citizens, disabled persons, and young children attending school provides additional insights. The existing service required 24-hour reservations for the initial pickup, while the return trip was provided within one hour. Reducing the initial trip advance reservation requirement to 15 or 30 minutes was found to be much less important than reducing the wait for the return trip. It was estimated that reducing the return trip wait from an hour would increase ridership by 17 percent if a 30 minute wait was offered, and 24 percent if a 15 minute return trip wait could be achieved. This same analysis estimated an 11 percent ridership gain for a 10 minute travel time saving (Ben-Akiva et al, 1996). Use of Advanced Public Transportation Systems should improve service reliability in addition to reducing traveler waiting and riding times. The corresponding traveler response would be engendered not directly by the dispatching technology, but rather by the ability of transit agencies to respond more quickly and consistently to service requests. Change in Service Supply The service elasticities presented earlier in Table 6-6 for rural general public demand responsive service range from +0.6 to +1.1 for service supply measures including vehicle hours, vehicle miles and vehicles per square mile. These elasticity estimates were all developed based on cross- sectional data, an approach that brings with it the warning that the elasticities identified may reflect not only a traveler response component, but also the effects of agencies matching service supplied to generated demand (see âResponse to General Public Servicesâ). âResponse by Type of Strategyâ â â âReplacement of Fixed Route Service by Demand Responsive Serviceâ Responsive Servicesâ âResponse by Type of Strategyâ â Rural Demand Responsive
6-27 Indeed, urban data from Chicago show that close to a half of all persons using Chicagoâs paratransit service on other than a subscription basis report no, little, or only occasional success in making a trip reservation. The 1998 CTA paratransit reservations survey also shows that 55 percent of those unable to book a trip at the desired time reported inability to make the trip by other means (Chicago Transit Authority, 1998). Unsatisfied demand such as this will quickly be absorbed if the effective capacity of a demand responsive service is increased by adding vehicles and drivers or by enhancing call taking and dispatching procedures. These caveats notwithstanding, service hour elasticities based on quasi-experimental before and after data from five of the Norfolk areaâs urban demand responsive services, all open to the general public, average the same (+0.88) as the rural service elasticities. The Norfolk service elasticities range from +0.5 to +1.8 (Comsis, 1985). This very limited data is thus suggestive that average demand responsive service elasticities are at least as high as for conventional bus service, higher than average fixed route transit frequency elasticities (+0.5), and probably around the middle range of fixed route service coverage elasticities (+0.6 to +1.0). As with conventional bus services, the variability of service elasticities for demand responsive transit is substantial. Change in Fares Change in Fares for the General Public The market segments and market areas served by demand responsive systems tend to be different than the areas and markets to which fixed routes are oriented. While some demand responsive services are targeted to the general public over a wide area, such as in Warsaw, Indiana and several Minneapolis suburbs, the markets are often more specialized, such as commuters to a specific office park complex, or persons with disabilities. Moreover, the markets typically have lower demand densities. Travelers using demand responsive services in these particular environments might be expected to have fewer choices and, hence, exhibit less sensitivity to price or service factors. This remains a supposition, however, that is unsupported by presently available empirical data. At least for changes in fares and service supply for the general public, the limited available data do not seem to indicate lower than normal overall sensitivities. The available data also suggest that the sensitivity to service supply, although probably not to other service factors, is greater than the sensitivity to fares. Observed data from 1980s fare changes on seven of the Norfolk areaâs demand responsive services show log arc elasticities of transit trips to fare ranging from -0.16 to -0.64 (Comsis, 1985). These plus demand responsive service and paratransit fare elasticities from the 1970s (Dygert, Holec and Hill, 1977; McGillivray, 1979), are provided in Table 6-10. Although there is wide variation, the average observation (-0.38) is of the same order-of-magnitude as fare elasticities observed for fixed route services.
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