CHAPTER 2

Literature Review/Industry Scan

A literature review/industry scan was undertaken to learn from existing sources the different types and approaches to paratransit fleet configuration. The study team sought this information from published, unpublished, and online material, including studies, proposals, conference proceedings and presentations, news articles, newsletters, software vendor marketing materials, and websites.

Paratransit

The term “paratransit” literally means “beside transit.” Many transit industry practitioners consider “paratransit” to be synonymous with ADA complementary paratransit—or ADA paratransit for short. Transit agencies operating fixed route services are obligated under the Americans with Disabilities Act of 1990 (ADA) to provide them to persons who, because of their disabilities, are unable to access or use the fixed route service. The minimum federal obligation to provide such service stipulates that ADA paratransit must be provided when the fixed route services are being operated.

Others in the industry take a much broader view, including defining paratransit to include “all other types of demand-responsive transportation (DRT) covering other need-based services” (Lave and Mathias, 2000). Under this definition, paratransit would include general public DRT services such as rural dial-a-ride services and even on-demand services such as microtransit.

At the direction of the study panel, these other types of paratransit services are limited to include (1) coordinated services, where ADA paratransit trips are commingled with other types of need-based trips such as sponsored trips taken by older adults or human service agency client trips; and (2) transit-agency or publicly provided specialized, non-ADA-paratransit, demand-responsive transportation services whose eligibility focuses on specific individuals such as dial-a-ride services for older adults and persons with disabilities, and not on the general public.

Paratransit Fleet Configuration

For this synthesis, “paratransit fleet configuration” is defined as the composition of the dedicated fleet used to serve paratransit trips. In practical terms, the definition has two parts:

1. The fleet mix is defined as the categorization of vehicles into two groups: wheelchair-accessible vehicles (WAVs) and non-accessible vehicles (non-WAVs), often expressed as a percentage with WAVs expressed first (e.g., a fleet mix of 75%/25% where 75% of the dedicated fleet are WAVs).

2. The stratification of vehicles into different types based on sizes, accessibility equipment (lifts or ramps), and seat/wheelchair capacities.

Vehicle types can be divided into three main categories, including physical dimensions (the capacity of the vehicle), compatibility constraints (service limit), and cost (Hoff et al., 2010).

In terms of seating capacity, a particular WAV, for example, might have a maximum seating capacity of 10 seats without any wheelchairs on board (as there may be flip seats that can be flipped down over the wheelchair positions) and a maximum wheelchair capacity of two. For this synthesis, such a vehicle is listed using the maximum number of each, so in this case, 10A/2WC for being able to accommodate 10 riders that are able to sit in a seat (including those riders able to transfer from a mobility device) and two wheelchairs. In actuality, the true seating capacity for this vehicle may vary from 10A/0WC to 8A/1WC to 6A/2WC.

Practical Considerations

The fleet configuration can affect the cost of providing service and the level of service (LOS) (Tolliver-Nigro, 1999). Using a fleet configuration ranging from small sedans to WAVs or buses accommodating both ambulatory and wheelchair riders is considered a cost-effective approach for paratransit agencies, noting that a mixed fleet is capable of addressing the variation in seating requirements and spatial and temporal riders’ requests (Fu and Ishkhanov, 2004). Fu and Ishkhanov also note that using larger vehicles can be effective when the ridesharing level is high, with larger vehicles being able to accommodate more shared rides, subject to service quality guidelines regarding on-time performance and excessively long on-board times. However, using larger vehicles, because of their higher operating cost, can impact cost efficiency. In contrast, small vehicles, such as sedans or minivans, have great value in serving single trips (that cannot be shared) and trips in low-demand areas and at low-demand times. Small vehicles also tend to have lower operating costs. However, up to 70% of the cost structure of a paratransit service is related to operator wages and fringe benefits, so the cost advantages of smaller vehicles can be negated if two vehicles need to serve a set of trips where one large vehicle is sufficient.

Drivers can also operate smaller vehicles without a CDL, which, in this era of driver shortages, can open up the prospective driver pool to many more applicants who do not wish to go through the time and expense of the required training of getting a CDL.

At the same time, a mixed fleet with different types of vehicles requires more complex vehicle routing and scheduling problem-solving as well. Not only does the scheduling and dispatching process have to recognize the different capacities of the vehicle assigned to a particular run and the sequencing of passengers boarding and alighting, but also the routing may change depending on the weight and turning radius of a vehicle. Turning radius is important in cases where smaller vehicles are able to go in and out of apartment complexes, but larger vehicles cannot. Moreover, the scheduling system must recognize when a WAV is required to “save” a late-running vehicle or to swap in for a WAV downed for a mechanical failure or accident, especially when there are only non-WAVs nearby.

Most paratransit scheduling and dispatching systems have ways to enter the seating capacities of different vehicle types (which are associated with specific vehicles, which in turn are assigned to specific runs) so that optimization processes or individual trips (with their own requirements based on a rider’s mobility needs) do not accidentally get assigned to a wrong vehicle type or to a vehicle that is already full. With many of the more sophisticated systems, one can also configure the speed and other scheduling parameters associated with different vehicle types.

Planning Considerations

One of the main tasks faced by transit agency paratransit managers and planners is re-sizing the fleet composition and fleet configuration of the paratransit fleet as conditions change. Fleet composition and the optimal number of vehicles are also significantly related to routing decisions. (Hoff et al., 2010).

To determine how well the existing system meets the service need, paratransit planners and providers need to analyze their existing system to determine any mismatch between the supply and demand for the service, as well as the quality of service. Fleet size, configuration and mix (the fleet required for specific operating needs and conditions), trip demand (the number of trips requested to be served), service level (the scheduled service hours), and quality of service (how well service operates) are the most important parameters to consider in the development of a methodological approach for the paratransit configuration (Fu, 2003).

Recognizing changing needs is key. For example, the increasing need of older adults for expanded mobility options has motivated transit agencies to switch from uniform to mixed fleets consisting of smaller accessible vehicles and non-accessible vehicles (usually sedans) (Chia, 2022) as well as to experiment with innovative forms of paratransit services that go beyond conventional models and offer more flexible modes of mobility (Weiner and Armenta, 2023). Two examples of such innovations are (1) “alternative services,” which are defined as transit agency–provided, on-demand service for ADA paratransit service customers and prevalently use TNCs such as Lyft and Uber, and (2) “opt-in services” in which ADA paratransit customers agree to allow their ADA paratransit request to be assigned to a TNC, taxis, or other service providers that have drivers that are not “ADA paratransit certified” (Ellis et al., 2023). Both such services result in many ambulatory trips shifting from the paratransit service’s dedicated fleet. Because of this shift, transit planners are reconsidering what fleet mix might be appropriate for the dedicated fleet due to a diminished ridership level (that needs to be served with the dedicated fleet) and ridership with a higher percentage of riders requiring WAVs.

It is important also to remember that during the COVID-19 pandemic and due to social distancing, larger vehicles could accommodate social distancing protocols. In contrast, smaller vehicles were unable to comply with the protocols. Consequently, ridesharing could still be accomplished in larger vehicles, while smaller vehicles could be used only for exclusive ride trips.

Another planning consideration when deciding what type of WAV to acquire is the accessibility equipment of the vehicle and, more specifically, the size of wheelchairs that can be accommodated. Pertinent minimum specifications in the ADA may be found in 49 CFR §38.23(b), which includes specifications for lifts; 49 CFR §38.23(b), which includes specifications for ramps; and 49 CFR §38.23(d), which includes specifications for wheelchair securement systems. For example, WAV lifts must have a minimum design load of 600 pounds, and lift platforms must accommodate a wheelchair measuring 30 inches wide by 48 inches deep. That said, some electric wheelchairs can be up to 36 inches wide. Thus, transit agencies with ADA paratransit obligations must decide whether or not to acquire WAVs that have wider lifts to accommodate customers with wheelchairs of this kind. As mentioned in the background section, some transit agencies decided to acquire WAVs with wide lifts. In contrast, others with few such users have chosen to utilize subcontractors that have WAVs with wide lifts, such as NEMT providers. As mentioned in the background section, some transit agencies, faced with long delays in replacing their cutaways, have sought smaller vehicles instead but have had to retain some of the larger cutaways (with wider lifts) well past their retirement age for the sole purpose of being able to accommodate such riders.

Another consideration when ordering WAVs is the configuration of seating versus wheelchair positions. The larger the vehicles, the more possibilities there are for multiple wheelchair positions. Thus, for systems in which larger group trips are made by riders in wheelchairs, having vehicles in hand that can handle three, four, five, and even six wheelchairs (as is the case in Salt Lake City) is important. If this is not the case, vehicles that can handle one or two wheelchair riders may suffice. Thus, the types of trips become a key determinant in deciding vehicle type.

For vehicles that can accommodate more than one wheelchair position, the placement of the wheelchair positions and the configuration of permanent versus flip seats, combined with the size of wheelchairs, can cause some inside-the-vehicle navigation issues, commonly called LIFO (last in, first out) issues. Those issues, in turn, can have a profound impact on scheduling and dispatching. Generally, the more wheelchairs that a vehicle can accommodate, the more challenging it is to navigate within the vehicle, and with some vehicles, a driver with two (or more) wheelchair riders on board cannot unload the first wheelchair rider without first unloading the last wheelchair rider(s) to board. LIFO is not only an inconvenience to riders who must be unloaded and then re-loaded onto the vehicle at an intermediate stop, but the additional loading and unloading time can dampen productivity. It may hinder on-time performance if the scheduler or scheduling package does not account for this extra time. Drivers faced with this issue in real time may choose instead to re-order the stops to avoid LIFO situations, but this may lead to excessively long on-board times and late trips—and frustrated riders. The need to reorder stops may also require tailoring the configurations of the scheduling system so as to avoid such events.

As discussed in the previous section, the maximum number of seats in a vehicle, including seats for ambulatory riders and wheelchair positions, can also have a profound impact on driver recruitment because it affects whether or not a CDL is required to operate. Because CDLs require stringent and expensive training, the number of potential driver applicants is far smaller than for driving positions that do not require a CDL. Hence, smaller vehicles can be a strategy for combatting driver recruitment issues, especially for services with low [under 2.0 trips per revenue vehicle hour (RVH)] productivity. But because most of the cost of providing paratransit is attributable to driver wages and benefits, transit agency planners must explore the number of times two smaller vehicles would need to be dispatched when a larger vehicle would do as a factor for determining the vehicle type or types that compose the transit agency’s paratransit fleet.

Lastly, service equivalence issues come into play when a transit agency has a mixed fleet of WAVs and non-WAVs. Under the ADA, one of the key requirements for any demand-responsive transportation (DRT) service is service equivalence. The ADA says that a DRT service, when viewed in its entirety, must provide an equivalent service. Such services are deemed equivalent when persons with disabilities, including wheelchair users, are provided the same level of service according to the following seven criteria:

1. Response time
2. Fares
3. Geographic area of service
4. Hours and days of service
5. Restrictions or priorities based on trip purpose
6. Availability of information and reservation capability
7. Any constraints on capacity or service availability (FTA, 2015)

In short, the guidelines state that a transit agency may have some vehicles that are not wheelchair accessible as long as people with disabilities can’t feel the impact. Thus, having such a fleet mix is okay as long as service is equivalent based on these seven criteria. Moreover, a transit agency may have a fleet that is 100% made up of WAVs but not be compliant with service equivalence

if some of the other criteria are not met. While ADA paratransit, by policy, can’t be capacity-constrained, transit agencies do have to ensure that any constraints that do exist are equally applied to all riders. For example, to evidence this, a transit agency must provide evidence that the denial rate for riders with disabilities is essentially the same as for riders without disabilities. Any capacity constraints that do exist cannot result in riders with disabilities experiencing poorer on-time performance or longer ride times as compared to other riders because of the particular mix of vehicles.

Empirical and Practical Studies

There are various modeling methodologies analyzing the capacity and quality of demand-responsive services, including simulation methods and mathematical models. The simulation method is considered one of the most favorable methods to address the paratransit capacity and quality of service, the minimum number of vehicles or fleet size, and the maximum number of trips related to a fleet size (Fu, 2002, 2003; Quadrifoglio et al., 2008). Nevertheless, the limitations of simulation methods resulted in the development of analytical and mathematical methods. For instance, the early simulation model of Wilson et al. proposed that the minimum number of required vehicles for the dial-a-ride systems increases as the service area, service demand, and quality of service increase (Wilson et al., 1971). This model was developed for dynamic service systems with same-day-demand trips; however, currently, paratransit trips and scheduling can be made in advance (Fu, 2003). Daganzo simulated another theoretical model in which the minimum fleet size was considered as a function of average travel speed, boarding plus alighting time, and average number of requests waiting to be picked up (Daganzo, 1978). This model is only valid when the system does not have time constraints and the routing method is not complicated (Fu, 2003).

Several studies have been developed to model and evaluate the relationships between fleet size and service performance. In a study by Mindorff (2019), Disabled and Aged Regional Transit System (DARTS) service performance before and after mixing the service fleet was reviewed. DARTS Paratransit service in the city of Hamilton, Ontario, Canada, experienced a 50% increase in cost-per-passenger trip on bus vehicles from 2012 to 2017. In response to the rise in ridership, the growth in the number of ambulatory frail elderly people, and the need for carrying more than one mobility device (wheelchairs), DARTS retired 65 of its 72-bus fleet and contracted 21 wheelchair vans, 20 two-wheelchair microtransit vehicles, and 40 ambulatory vans in 2016–17. The service vehicle reconfiguration induced a fast decrease in the average passenger cost per passenger trip from $28.45 in 2012 to $26.29 in 2017 and an overall avoided cost of $7.5 million from 2017 to 2019 (Mindorff, 2019).

Fu and Ishkhanov (2004) studied the practical process for determining the optimal fleet mix (i.e., that maximizes the operating efficiency of paratransit services). Based on a real-life example, they first explored the effect of vehicle size on vehicle productivity, fleet size, and passenger ride time by using sensitivity analysis on an example case. The results indicated that:

• Larger vehicle sizes can generate higher vehicle productivity, can result in smaller fleet sizes, and can result in significant savings from fewer operators.
• The optimal vehicle size is affected by travel demand; larger vehicles can be used in high-demand services. Higher demand paratransit services have more tendency for ridesharing. Consequently, they have a greater probability of using large vehicle sizes.
• Service constraints and policy influence the optimal vehicle size. Ridesharing becomes less likely when the ride time window constrains the service; therefore, small vehicles are needed. Services with more relaxed constraints would have higher cost efficiency when having larger vehicles (Fu and Ishkhanov, 2004).

Edmonton’s Disabled Adult Transit Service (DATS) is a paratransit service operating within the city of Edmonton, Canada, for individuals with significant physical or cognitive disabilities. The service was investigated by University of Alberta researchers in 2011 to optimize vehicle models and numbers that would lead to maximized service efficiency. The demand and performance of DATS with its current vehicle mix were evaluated while considering seat type usage (permanent seats versus flip seats in the wheelchair space), trip times and destinations, and vehicle runs for the peak of months, weekdays, and hours of demand for DATS paratransit. The study results revealed that although the service had sufficient unoccupied spaces for all time windows, seat type configuration was not optimized. Calculating the maximum passenger per seat time in each vehicle run could help service planners look at different scenarios during peak hours of demand and rank different vehicle modes for DATS (such as the 6 wheelchair-8 flip model and the 8 passenger-4 wheelchair-2 flip model) that would be capable of transporting more ambulatory and total passengers. The new fleet configuration was suggested to allow the service to be more adaptable when demand for seat type changes (Diep et al., 2011).

In another study, the operations and ridership of The RIDE [Massachusetts Bay Transportation Authority’s (MBTA’s) ADA Paratransit Service in Greater Boston] were analyzed to identify how to optimize paratransit trips with alternative service providers to minimize system costs. This study explored the operations and demand patterns before and after the introduction of on-demand alternative service that allowed eligible ADA paratransit customers to use Uber, Lyft, or Curb for a subsidized trip in addition to conventional ADA paratransit service. The report noted a 42% mode shift of (mostly ambulatory) riders from The RIDE to TNCs and taxis. This new program led to a 33% increase in total trips and a 26% decrease in overall cost (Gonzales et al., 2019).

Planning Tools

A comprehensive and useful planning tool to help determine an optimal fleet size and configuration came out of a study, Access Link Forecasting Study, carried out for NJ TRANSIT’s ADA paratransit service, Access Link (KFH Group, Inc., 2022). The planning tool that was developed for this study incorporated a methodology for forecasting ridership and identifying the optimal fleet size and configuration and fleet replacement and expansion. The methodology to forecast the ridership utilizes ridership data (FY2017–2020), population data (ACS, 2019), and service characteristics. Next, vehicle forecasting was developed based on peak-hour ridership, productivity, vehicle mix, spare ratio, useful life threshold, and average annual mileage of vehicles by capacity type and region. This vehicle demand methodology was used to predict the fleet size/mix, replacement, and expansion. The tool developed for NJ TRANSIT included two modules explaining (1) how to determine optimal fleet size and (2) how to develop the vehicle replacement and expansion plan.

Equation 1 was used to calculate the optimal fleet size:

Equation 1

Fi = Vi(1 + S%)

Vi = (Ri/Pi)

Where:

Equation 2 was used to estimate the optimal fleet mix:

Equation 2

Fi = Xi+ Yi + Zi

Xi = Fi x Xpi Yi =Fi x Ypi Zi = Fi x Zpi

Xpi = Xcfi/CFi Ypi = Ycfi/CFi Zpi = Zcf/Cfi

Where:

The recommendation of the study emphasized the role of the productivity factor in predicting fleet needs. However, it noted that many factors affect paratransit productivity (e.g., size and density of service area, traffic, common trip destinations, peak period, and weather) that are not in the service operator’s control.

Another planning tool of interest can help with planning the use of non-dedicated service providers as overflow providers for paratransit service. As part of TCRP Research Report 121: Toolkit for Integrating Non-Dedicated Vehicles in Paratransit Service on the optimal split of dedicated and non-dedicated service for paratransit service (Nelson\Nygaard Consulting Associates et al., 2007), Roger Teal developed an Excel-based tool to optimize that split that was later streamlined and commercialized. The importance of this tool to the topic at hand is that the use of non-dedicated service providers directly impacts the size and configuration of the dedicated fleet.

Lastly, the new crop of on-demand technology vendors, such as Via Mobility, Spare Labs, RideCo, and others, all have “optimization simulation” tools that can size a dedicated or non-dedicated fleet. While all these were developed for general on-demand services, they can be applied to more specialized populations and services such as ADA paratransit.