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A tool to aid redesign of flexible transport services to increase efficiency in rural transport service provision

A tool to aid redesign of flexible transport services to increase efficiency in rural transport... JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS , VOL. , NO. , – https://doi.org/./.. A tool to aid redesign of flexible transport services to increase efficiency in rural transport service provision a a b c a Richard Mounce ,Steve Wright , C. David Emele , Cheng Zeng , and John D. Nelson a b Centre for Transport Research, University of Aberdeen, Aberdeen, United Kingdom; Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom; Computing Science, University of Aberdeen, Aberdeen, United Kingdom ABSTRACT ARTICLE HISTORY Received  December  Rural areas generally have lower and more dispersed demands for travel which cannot sustain con- Accepted  November  ventional public transport services and consequently have a greater number of flexible and demand responsive transport services operating. These services usually operate on a stand-alone basis, are KEYWORDS often subsidized and are typically only accessible by certain passenger types or for specific trip pur- constraint relaxation; flexible poses. This generally results in uncoordinated and inefficient transport provision overall. The Flexible transport system; rural integrated transport services (FITS) system featured in this paper has been designed to address this transport; subsidy; surcharge problem. FITS can be used as a planning tool to assess potential benefits from relaxing operating con- straints (e.g., a service’s operating boundaries), which can potentially suggest service redesign. It also includes the capacity to assign subsidy payments on a trip by trip basis to increase cost efficiency whilst meeting a greater proportion of transport needs. The case study in the paper focusses on trans- port to health in the Aberdeenshire and Morayshire areas of Scotland in the UK. Despite flexible trans- port operators receiving public funds to meet passenger needs, this is currently being supplemented by public bodies paying large amounts in taxi fares in instances where there is a statutory obliga- tion to provide travel but where no other suitable transport service exists. The results demonstrate the potential substantial savings which could be realized by allowing transport operators to redesign their services by relaxing constraints and by the reassignment of subsidies: resulting in more passen- ger demands being met and a reduction in public spending on taxi fares. 1 Introduction certain eligibility criteria, e.g., only for elderly people Flexible transport services (FTS) consist of a range of or only for people who are disabled. In the UK many mobility services oer ff ing greater flexibility than reg- services are provided by community transport orga- ular public transport services. Whereas urban flexible nizations, health sector funded organizations, or local transport includes shared taxis, car-pooling, and car- authority departments involved in social care. sharing (Nelson & Wright, 2016)which attemptto Currently, many flexible transport providers are paid a oer ff a greener alternative to solo car use, in rural areas flatratesubsidy or blockgrant regardless of thenumber of the passengers they transport (or are paid the subsidy where there is limited conventional (fixed-route) public provided that they fulfill their quota of trips within a transport, flexible transport providers often fill the gaps given period). This enables these operators to provide providing essential services. This is achieved through a core service to access essential goods, services, and demand responsive transport (DRT) for the general activities (such as local shops, GP surgeries, day care public or more commonly through dedicated services centres) at certain times of day and on certain days of (i.e., transport for specific groups of the population, e.g., the week. However, a common scenario is that vehicles the elderly). These rural FTS are characterized by flexible areunderutilized during otherperiods of theday dueto routing and scheduling of small to medium-sized vehi- insufficient funds to provide additional services and there cles operating in shared-ride mode between pick-up and is little or no financial incentive available to undertake drop-off locations according to passengers’ needs (Mulley or accommodate additional trips outside of their core et al., 2012), usually resulting in a “door-to-door” service. serviceunder theexistingfunding structure. Theremay Dedicated FTS are generally standalone services with CONTACT Richard Mounce r.mounce@abdn.ac.uk Centre for Transport Research, School of Engineering, University of Aberdeen, Fraser Noble Building, Aberdeen AB UE. Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/gits. ©  Richard Mounce, Steve Wright, C. David Emele, Cheng Zeng, and John D. Nelson. Published with license by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/./), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 176 R. MOUNCE ET AL. then be unmet demand, which is clearly an undesirable The benefits of FITS detailed above can be realized situation. In addition, these services are often largely through the use of the offline version of the FITS tool. uncoordinated and poorly promoted. In some areas the TheFITSsystemcan also operateinanonlinemode, tight eligibility restrictions lead to multiple services oper- interfacing between passengers and transport operators atinginthe same places at thesametime, each catering in real-time (Emele et al., 2013). This is conceptualized as for different trip purposes and user categories; this is a multiagent system (Ferber, 1999)comprisingavirtual very costly and inefficient. In other more rural areas the marketplace with three types of agents: tight eligibility restrictions lead to a much more limited 1. Passenger agents, operating on behalf of service, in terms of operating area and times, available to passengers, only particular users for particular trip purposes: this is 2. Transport operator agents, operating on behalf of ineffective for those whose trips do not fall within these transport operators, restrictive constraints, resulting in very limited choice for 3. The marketplace agent, which mediates between passengers. the passenger and transport operator agents. The flexible integrated transport services (FITS) The paper is organized as follows: Section 2 provides a system has been designed to address this problem of detailed overview of the FITS system, including the data inefficient transport service provision in rural areas. The requirements as well as the modes of operation. Section 3 FITS tool affords the opportunity to identify flexible is on the case study area and includes detail of the local transport services which could fulfill currently unmet context and results from the test runs. Finally, Section 4 passenger trip requests if certain constraints were to be discusses the benefits and future uses of the FITS tool and relaxed. Such an approach is of potential benefit to flexible provides conclusions. transport operators looking to extend their services and generate additional revenues.Itisalsoofpotential ben- 2 The FITS system efit to public sector organizations with an obligation to provide equal access to individuals for key services (e.g., 2.1 Data requirements access to education, social care, and health services). In cases when there is no existing public transport which is FITS requires data about passenger trips to ascertain suitable, these organizations have an obligation to pay for, whether passengers are both physically able and eligi- or at least subsidize using public funds, the use of taxis by ble to use given transport services. The following data is individuals. In addition, public sector organizations may required for each trip: pay block subsidies to transport operators to operate their 1. Journey origin and destination address. services. The FITS system can be used to demonstrate the 2. Expected time of departure or desired arrival time. effects of restructuring this system of subsidy payments: 3. Age group, chosen from: under 16, 16–21, 22–54, in place of only block subsidy payments, a more incentive- 55–59, and 60+. based structure is proposed where a lower block subsidy 4. Mobility status, chosen from: able-bodied, dis- is received to retain the basic service, but is supplemented abled (wheelchair user), disabled (other). In by additional subsidy payments to transport operators addition thereisanoptiontochoose“unable for operating outside of their usual operating constraints, to use regular public transport,” which includes e.g., operating outside of their usual operating times and the case where this is due to lack of provision areas, or transporting additional types of passengers. The or of frequency). Wheelchair users are further FITS tool can estimate the net savings through reductions categorized as “electric,” “nonelectric nonfolding” in taxi fares that are possible through the relaxation of and “nonelectric folding (and able to sit in car/bus constraints. seat).” Flexible transport operators can utilize the FITS tool 5. Journey purpose, chosen from: health appoint- to specify the extent to which they are prepared to relax ment, shopping, social care, leisure/visiting their core service constraints on when, where, and who friends, school/education and work/commuting. they are prepared to carry and it also allows them to 6. Whether there is a clinical need for ambulance ser- stipulate the financial compensation (within legislative vice transport. boundaries)theywouldrequiretomaketheserelaxations. 7. Whether there is a need for an escort (e.g., a carer This provides a mechanism by which flexible transport or other assistant) to accompany the passenger (to operators (including community transport providers) assist them). can generate additional revenues for accommodating 8. Therelativeweightingsofthe valueoftraveltime, transporttohealthpassengerswho otherwisewould money, and number of vehicle changes (for the need to be carried by taxi. online operation of FITS only). JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 177 Figure . FITS operator data input tool. Clearly there are certain restrictions that are placed 7. Penalty surcharges for operating outside defined on services that should not be violated if a service is operating hours (in bands). to remain legitimate and reputable, e.g., government 8. Passenger type eligibility penalty surcharges regulations, vehicle capacity etc. However, there are other for those passenger types who are normally discretionary constraints that operators assign to their ineligible (these are optional in that the operator services as they choose. Figure 1 shows the FITS operator has the option to keep these types as ineligible data input tool. The operating area can be drawn as regardless of any surcharge). a polygon in Google maps and the accompanying data The fare structure information consists of the entered into a web template. All this data is then imported following: into the FITS system. The following information needs to 1. Whether the service charges fares. be provided to theFITStoolfor each service: (notethat 2. Fares within mileage bands. if there are day-to-day variations, such as to the hours 3. Return fare multiplier. of operation, then these need to be defined as separate 4. Percentage discounts for over 60s and under 16s. services): 5. Whether escorts are charged a fare. 1. Operatingtimes:daysofthe week andhours of 6. Whether the service charges for dead mileage and operation. the location for this to be calculated from. 2. Operating area. 2.2 Searching and ranking of transport options 3. Fare structure (including concessions). 4. Vehicle specifications (including seat /wheelchair If the passenger can use conventional public trans- capacities and vehicle access). port, the FITS tool generates conventional fixed-route 5. Passenger type (age, mobility status, journey pur- public transport options using the Google Maps Transit pose) eligibility information. journey planner via the Google Directions application 6. Penalty surcharges for operating outside defined operating area (in bands). http://www.google.com/transit 178 R. MOUNCE ET AL. lowest generalized cost. For the online version of the FITS programming interface (API): parameters for this API tool, the transport options with the lowest generalized include desired arrival/departure time, mode, whether to cost are presented to the user to choose from. minimize transfers etc. The distance that different cate- gories of passenger (e.g., able-bodied, disabled, elderly, etc.)are assumedtobeableand willingtowalktoaccess 2.3 Constraint relaxation and surcharges public transport is set to a maximum value in order Sections 2.1 and 2.2 describe how FITS provides a tool to limit the number of options returned from Google which checks the operating criteria and constraints of Transit. all existing transport services in an area to identify suit- Flexible transport options are also generated in the able transport options for specific trip demands. For trip FITS tool by searching the available flexible transport ser- demands which cannot be fulfilled by current transport vices (details of which are input to FITS by operators services, the FITS tool provides the option to identify the as described in Section 2.1). These potential transport flexible transport services which could fulfill the passen- options are deemed suitable if the journey origin and des- ger request if certain constraints were relaxed. This con- tination are within the service’s operating area (which can straint relaxation takes into account the preferences of the be established using the ray method (Shimrat, 1962)since operatorsthemselvesaswellasthe compensation pay- theoperating area is defined by apolygon); thejourney mentsaflexibletransport operator wouldbepreparedto is within the operating times of the services; and also if accept for a given relaxation request. These compensation the passenger meets the service’s other eligibility criteria costs can be thought of as surcharges imposed by the flex- (e.g., age, mobility status etc.). The travel time for volun- ible transport operator to extend their core funded ser- tary car services (which involve volunteers driving their vice. Relevant legislative restrictions which place limits on own cars) is assumed to be the same as for a taxi, whereas relaxations and compensation payments are also consid- travel times for door-to-door bus services are multiplied ered in the process. by a penalty factor (or travel time ratio) of 1.5 to reflect Three types of surcharge, as identified in Section 2.1 the fact that they may need to divert for additional passen- are: ger pick-ups (the value of 1.5 is based on our experience 1. Penalty surcharges for operating outside defined of DRT services in rural areas). Simulation studies have operating area (in bands). shown this penalty factor to range from one, where only 2. Penalty surcharges for operating outside defined one passenger is carried, to over vfi e when there are a high operating hours (in bands). number of trip requests that each vehicle needs to accom- 3. Passenger type surcharges for those passenger modate.Inruralareas,whenrespondingtotriprequests types who are normally ineligible for mainly health purposes there are likely to be relatively In the instances where constraint relaxation is neces- few diversions to pick up additional passengers and hence sary to fulfill a passenger demand, the total fare f charged a relatively low value of travel time ratio is reasonable. by an operator is given by: A generalized cost g can be calculated for each possible transport option using the formula: f = f + d (2) p p g(t, f , t , c, t ) = t + ft + ct (1) f c f c where f is the standard fare for the operator to take pas- senger p and d is the surcharge for the operator to take where t is the travel time, f is the fare paid, t is the f p passenger p. The standard fare will depend on the passen- valueoffareinterms of travel time, c is the number of ger’s journey origin and destination and may include dead interchanges, and t is the average value of an interchange mileage. The surcharge will be the sum of all the penalty in termsoftraveltime(note that t and t are requested f c from the passenger in the booking entry form). Note surcharges identified above. Note that these surcharges firstly that for public transport options the travel time are additive, e.g., if the passenger’s origin and destination can be split up into in-vehicle travel time, waiting time, are both 5 miles outside of the usual operating area then and walking time with suitable value-of-time weighting thesurcharge will be twicethatfor operating5miles out- factors applied to each .Notealsothatthe generalized side of theusual operatingarea. In thecaseofthe origin cost defined in Eq. ( 1) is in time units; this is appropriate or destination being outside of the operating area the dis- sincewegenerally do nothaveany informationavailable tanceoutside of theoperating area canbecalculatedas regarding an individual passenger’s value of time in terms the minimum distance to any of the line segments which constitute the boundary (since the boundary is defined by of money. For the offline version of the FITS tool, each a polygon). The generalized costs of the options are cal- trip demand is assigned its transport option which has the culated using Eq. (1) but with the revised fare defined in https://developers.google.com/maps Eq. (2). Allowing these relaxations will obviously result https://www.gov.uk/government/publications/webtag-tag-unit-m-- in more transport options being available to passengers public-transport-assignment-modelling JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 179 Figure . Flow of data through the FITS system in the case of hospital appointment demands. overall, but with the accompanying cost incurred through the UK. The UK’s National Health Service (NHS) has a the operator surcharges. statutory duty to provide transport to get nonemergency Figure 2 presents the flow of data through the FITS sys- patients, but who have a medical need while being trans- tem in the case of hospital appointment demands. ported, to hospital for treatment. In many areas it is the Ambulance Trust that provides this service. For patients not deemed to have a medical need whilst being trans- 3 Case study ported the responsibilities for transport are less clear. In the UK, local authorities are obliged to assess whether TheFITSplanning tool hasbeenapplied in theruralcase people living in their area, particularly households on low study setting of Morayshire and Aberdeenshire in North incomes and people without cars, are able to reach key ser- East Scotland to explore how flexible transport service vices and activities safely, reliably, aoff rdably, and with rel- redesign can lead to potential increases in efficiency when ativeeasebypublictransport.Eachlocal authoritymust providing transport to health trips. Before discussing the thenproduceanactionplantoidentifyhowtheyandtheir results we briefly describe the national transport to health partner organizations will improve any gaps in accessibil- context. ity (for example, in our case study area the transport to health agenda is shaped by the Grampian Health Trans- port Action Plan team which is a consortium of local 3.1 Context authorities, NHS and transport agencies). This involves To set this work in context it is necessary to understand financially supporting bus operators (commercial or whoisresponsible forproviding transporttohealthin community) to provide necessary services, or filling the 180 R. MOUNCE ET AL. Table . Journeys by mode of travel to attend hospital and other health appointments in Scotland. Travel Mode Walk Car Driver Car Passenger Public Transport + Other Taxi Proportion .% .% .% .% .% Source: Scottish Household Survey (–) gaps with local authority in-house bus services. Whilst 3.2 Results this can be planned to some degree for certain types The FITS system was tested offline in order to assess of regular trip it is more difficult for hospital appoint- its potential. The trial was done using a set of typical ments which are largely unpredictable and are often one- health-related passenger trip demands along with trans- off demands. As a result, local authorities often resort port operator data (as detailed in Section 2.1)for the to using taxis to meet their responsibilities in provid- Morayshire and North-West Aberdeenshire area. The ing access to health appointments. Whilst health boards passenger trip demands were produced using a simulated andTrusts, understandably,wishtoconcentrate their demand generator, which was based on actual annual out- efforts and funding into advancements in clinical care, patient appointment data from nine origin districts (elec- poor access means that whilst those patients who have toral wards) to vfi e destination hospitals in the Morayshire access can enjoy improving clinical care, others without and North-West Aberdeenshire area (the Hospital loca- access frequently may not enjoy even basic levels of health tions and ward boundaries are illustrated in Figure 3). care, let alone any advancement. As a result, they also In total there were 107,120 annual outpatient appoint- support transport to health to ensure equal access. The ments at the vfi e destination hospitals originating in the result is often an uncoordinated system of funding trans- nine origin districts. This generates 214,240 annual trip port to health resulting in inefficient, poorly planned, demands, or 4120 trip demands per week. The distribu- and uncoordinated transport services. Whilst there have tion of the origin locations (passenger pick-up points) been several initiatives to better integrate funding and within each ward was generated by random selection from service provision (DfT, 2009), these have often strug- the full set of postcodes in each ward (the postcode loca- gled to get agreement on shared funding and establish tions give a reasonable representation of the spatial dis- joint commissioning for transport services. It remains tribution of population across the ward, and each post- thecasethatapart from theAmbulance Trusts’none- code provides a good proxy for the location of the patient’s mergency patient transport services, taxis are a main- address). Note that simulated passenger age was added stay for patients accessing health appointments from rural to the postcode dataset for each ward based on patient areas when limited or no public transport is available or age profiles for outpatient appointments and simulated suitable. mobility status was added based on simulated age. There- We see from Table 1 that 78% of health appointments foretheselectionofapostcodeprovidesthesimulatedori- in Scotland are accessed by foot or as a car passenger or ginpickuppoint,passenger age, andmobilitystatus. driver;the remaining22% arebybus,taxi, or otherpub- From Table 2 we seethere areanestimated 25% of hos- lic transport. Table 1 relates to hospital and other health pital appointment trips made by public transport and taxi. appointments including GP surgery visits. The data also This 25% multiplier was applied to the total number of relatestothe wholeofScotland. As such thedistances outpatient appointments to get the simulated daily pas- involved will tend to be shorter than for the hospital-only senger demand to be run through FITS; this was done vfi e appointments in the generally rural area of our exam- times to give vfi e different passenger demand sets for one ple. As a result, in our test (described in Section 3.2)we week, i.e., vfi e week days. In total this produced 515 pas- consider a slightly lower proportion of access by walking sengers, each making an outward and return trip, giving (10.9%) and a similarly higher proportion accessing by a total of 1030 trips. public transport and taxi (25%). Table 2 gives the expected Thetransport operator servicedatawas sourced weekly journeys by mode to outpatient appointments in from publicly available data as well as directly from the the study area, based on these slightly adjusted mode operators. This provided operating area boundaries, fare share proportions. Table . Estimated weekly journeys by mode to attend hospital appointments in the study area. Travel Mode Walk Car Driver Car Passenger Public Transport + Other Taxi Proportion .% .% .% .% .% Weekly Trips      JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 181 Figure . Map showing the districts (electoral wards) and hospital locations used in the testing. information, eligibility criteria, and core operating times saving if the overall fare charged by the flexible bus opera- (09:30–11:30 and 13:30–15:30) for seven flexible bus tor (including the penalty surcharges) is cheaper than the services across the study area. Operator surcharges for equivalent taxi fare (calculated using £2.40 flag drop plus constraint relaxation were estimated from information £1.80 per mile). These potential savings were the taxi fare provided from the operators. that wouldbepaidminus thetotal fare that wouldbepaid First, the FITS tool was run using this data without to the flexible bus operator. Whilst the beneficiary of these any constraint relaxation (i.e., as the services currently savings may be the private individual if they are prepared operate). In this first run, approximately 80% of the sim- and able to meet the high costs of a taxi trip, in most cases ulated trips were found to have at least one potentially it will be the local authority or health board which meets suitable transport option (either a conventional fixed- most of the cost of the taxi on behalf of the passenger. route service or an existing flexible service). However, Table 3 shows these potential savings for a single day (Day there remained a substantial number of passenger trip 1) of simulated demand data and Figure 4 shows the loca- demands for which the passenger did not have a suitable tion of each passenger trip demand. For passengers whose non-taxi travel option, e.g., because they required a door- total fare (including operator surcharges) is less than the to-door service and there was no suitable flexible trans- taxi fare there are potential savings, e.g., for the outward port provider operating at that time and/or within that trip of passenger 1 the trip distance is 26.4 miles, the taxi area. There were 194 such trips (counting the outward and fare would be £49.92 and the flexible bus cost including return trips as separate trips since passengers could have surcharge would be £23.60 (£7.60 basic fare plus £12 for an option for one but not the other). At present, use of a picking up 8.9 miles outside their normal area and £4.50 taxi is the only transport option available to these passen- for extending their normal operating hours by 0.5 hours) gers to be able to access their appointment. It is assumed resulting in a saving of £26.32 compared to using a taxi. therefore that they will all access the hospital by taxi. This Note that there were a small number of passengers whose is areasonableassumption sincethislevel of taxi useis relaxation was unrealistic because the ratio of relaxation consistent with the estimated use of taxis in the study area distance to relaxation time was too high, i.e., above 40 basedonthe Scottish HouseholdSurveydatadetailedin miles of relaxation distance per hour of relaxation time, Table 1. These 194 passenger trip demands were noted and these passengers were filtered out from the savings. andthenasecond runwas carried outwithconstraint Table 4 gives these potential savings (compared to taxi relaxation: in this case, it was just the flexible transport costs) foreachofthe vfi edaysofsimulated demand as providers’ operating times and areas that were relaxed in well as the total (weekly) savings. Note that these savings exchange for surcharge payments. This resulted in over are after accounting for the total cost of the trip (including two thirds (132 out of 194) of the originally unmet passen- thesurcharges)paidtotheflexiblebusoperator;hencethe ger trip demands having suitable travel options using flex- total surcharges listed in Table 4 are for information only. ible bus services. In each of these cases, there is a potential It should also be noted that the savings in Table 4 were the 182 R. MOUNCE ET AL. Table . Potential savings for day . Flexible Bus Service Hospital Operating area Operating time Passenger Trip No. destination Dist. (miles) Relax. dist. (miles) Relax. time (hrs) Base fare (£) surcharge (£) surcharge (£) Total fare (£) Taxi fare (£) Saving (£)  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . .  .   . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s .  . .  . . .   Dr. Gray’s .  . .  . . . .  Dr. Gray’s . .  . .  . .   Dr. Gray’s . .  . .  . .   Dr. Gray’s . .  .   . .   Dr. Gray’s . .  . .  . .   Dr. Gray’s . . . .  . . . .  Dr. Gray’s . .  . .  . .   Dr. Gray’s . .  .   . .   Dr. Gray’s .  . .  . . . .  Dr. Gray’s . .  .   . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Turner . . . .  . . . .  Chalmers  .  .   . . .  Chalmers  .  .   . . .  Dr. Gray’s . . . .  . . . . Total . . JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 183 Figure . Distribution of currently unmet demands which could be met through constraint relaxation at lower cost than using a taxi:  day of simulated data. maximum, since not necessarily all this cost will be met by Table . Total weekly savings (% of maximum possible) for differ- ent levels of constraint relaxation of time and distance. the public authorities as noted above. Table 4 suggests that the potential savings to the public Relaxation time (hours) authorities (due to a reduction in expenditure on trips by Relaxation distance (miles)  .  . taxi) are up to £2196 per week, or equivalently £114,000  . . . . per annum.  . . . . Table 5 shows the percentage of the total potential  . . . .  . . . . savings per week for different levels of constraint relax-  . . . . ation for both time and distance together, and illustrates  . . . .  . . . . clearlythe necessityfor time anddistanceconstraints to  . . . . be relaxed together in order to allow significant savings  . . . . to be made. In addition to the level of constraint relax-  . . . .  . . . . ation, the potential savings when applying the FITS tool  . . . . in a particular instance will depend also on the particulars of thetransport demands(i.e.,iftheyare closetoexisting operating times and areas). 4. Discussion and conclusions 4.1 Immediate benefits from the use of FITS as a Table . Potential savings by day. planning tool Total Direction of No. of No. of surcharges Total savings The main beneficiaries of the savings calculated in Sec- Day travel passengers savings paid (£) (£) tion 3.2 are a) individuals who may pay all or part of the Day  Outward    . taxi fare; and b) public sector organizations which pay all Return   . . or part of the taxi fare where there is an obligation to pro- Total   . . Day  Outward   . . vide transport to health. In rural areas where there are no Return   . . other transport alternatives the latter case is prevalent. Total    . Day  Outward   . . If the £114,000 annual savings are extrapolated from Return   . . thecasestudy area to thewhole of ruralScotland(i.e., Total    . Day  Outward    . scaling up proportional to rural population) there are esti- Return   . . matedpotential savingsofupto£1.8million perannum. Total   . . Day  Outward   . . Although not all these estimated potential savings should Return    . be attributed to spending by public authorities (since Total   . . some of these taxi costs will be met by passengers them- Total Outward   . . Return   . . selves)itislikelythatalargeproportionshouldbe. The Total   . . possible savings are significant since the total spend on 184 R. MOUNCE ET AL. transport for patients by NHS boards in Scotland was £4.5 services can ensure the core services evolve to incorporate million (Audit Scotland, 2011). This figure includes reim- changing health and social care demands, thereby keep- bursement of £2.5 million for the Healthcare Travel Costs ing the additional subsidy payments within manageable Scheme, much of which is spent on taxis in rural areas. levels. The surcharges in Table 4 are payments that would be made to the flexible transport providers, potentially 4.3 Future uses of the tool on behalf of the passenger by the public authorities. These surcharges are significant (up to £1577 per week As mentioned above, the FITS tool has been devel- or £82,000 per annum) and hence potentially provide a oped to operate in both online and offline modes. In valuable revenue stream for these operators. This could itsonlinemodeitisatool whichutilizesthe operat- be up to £1.3 million per annum across rural Scotland. ing requirements and constraints of all existing trans- This is equivalent to over 40% of the £3 million in total port services in a defined area to identify the trans- grants received annually by the community transport port services which potentially could fulfill passenger trip sector (the main providers of flexible transport services requests. It then presents these to the passenger as a list in rural areas) in Scotland from statutory bodies (CTA, of transport options, ranked according to their prefer- 2012)and more than three times thelevel of fundingthat ences. There is clearly the potential to build constraint the community transport sector currently receives from relaxation into the online operation of FITS. This would health bodies (Audit Scotland, 2011). open the possibility of incorporating the FITS constraint relaxation approach into emerging Mobility-as-a-service (MaaS) systems (Heikkilä, 2014;Hietanen, 2014; Kamar- 4.2 Longer term benefits for transport to health gianni,Matyas, Li,&Schafer, 2015, Transport Systems Part of the savings identified above for local authorities Catapult, 2016). Within MaaS, an individual’s travel needs andNHS boards couldbeusedtofundmorepatient (usually satisfied by owning a car), are met by a range of services that include car leasing, car clubs, carpooling, transport to reduce the number of “Did Not Attends” community transport, cycle, and taxi services in combi- (DNAs). There is little research on what proportion of nation with “traditional” public transport. Arguably, this these are attributable to transport issues, but figures rang- could remove the need and cost of running a second car, ing from 20% (PCC and CC, 2013) up to 69% (Coun- or even remove theneed forowningany caratall.Ifcom- tryside Agency, 2004) in more rural areas have been munity transportservicescould adapttheir serviceoeff r- reported. The number of DNAs stands at over 7600 per annum in our case-study region alone. Each DNA was ing, through suitable constraint relaxation, in response to estimated to cost the NHS in Scotland approximately passenger requests then these community transport ser- £112 (Audit Scotland, 2011). If only 20% of these can vices and other flexible transport services could oer ff a be avoided by oeff ring additional door–to-door flexible much stronger component within MaaS solutions in rural transport through FITS constraint relaxation, this would as well as urban environments. reduce DNAs in the case study area by 1520 per annum, with an associated cost saving of £170,240 per annum 4.4 Conclusions (£2.7 million per annum if scaled up to the whole of rural Scotland). In addition to this are patient-cancelled The paper showed how the FITS tool could help increase appointments, which is an even higher number and which efficiency in transport provision to health appointments also incurs a cost to the NHS. Some of these cancellations in rural areas, by demonstrating its benefits in a case study. could also potentially be avoided with more extensive The flexible transport services in the case study area of door-to-door transport provision. As well as the finan- Aberdeenshire and Morayshire, which is typical of rural cial cost of missed appointments, one must also factor in areas across the UK and many developed countries world- the benefits to health of patients being able to attend their wide, are highly subsidized and have strict eligibility cri- appointments. teria; this has resulted overall in an inefficient patchwork Over time, if shifting demands suggest a different core of transport provision. The FITS system allows the relax- service provision then this can be specified in future ation of transport operators’ constraints in exchange for contracts with flexible transport providers in return for operators receiving surcharge payments. The FITS tool the statutory grants received. With improved knowledge was applied to a simulated demand set and substantial of the spatio-temporal distribution of health and social potential savings were identified by relaxing operating care related demands which the system captures (through constraints. Additional benefits were also identified in the data on unmet trip requests and requests requiring addi- form of increased revenue to transport operators and the tional subsidy payments) the commissioners of transport potential to reduce the number of missed appointments. JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 185 As well as identifying such benefits, FITS is also useful as Ferber, J. (1999). Multi-agent systems: An introduction to dis- tributed artificial intelligence .New York:AddisonWesley a tool for decision makers to consider modifying funding Longman. mechanisms in a way which motivates operators to amend Heikkilä, S. (2014). Mobility as a service – A proposal for action their service provision in order to better meet passengers’ for the public administration, Case Helsinki (MSc disserta- transport to health needs. tion), Helsinki, Finland: Aalto University. Hietanen, S. (2014). ‘MobilityasaService’–thenew transport model? Eurotransport, 12(2), 15 2–4. Funding Kamargianni, M., Matyas, M., Li, W., & Schafer, A. (2015). Fea- sibility Study for “Mobility as a Service” concept in London. This research was supported by the Research Councils UK Report – London, UK: UCL Energy Institute and Depart- Digital Economy programme award (reference: EP/G066051/1) ment for Transport. to the dot.rural Digital Economy Hub, at the University of Mulley, C., Nelson, J., Teal, R., Wright, S., & Daniels, R. Aberdeen. (2012). Barriers to implementing flexible transport services: An international comparison of the expe- riences in Australia, Europe and USA. Research in References Transportation Business and Management, 3, 3–11. doi: 10.1016/j.rtbm.2012.04.001. Audit Scotland. (2011). Transport for Health and Social Nelson, J. D., & Wright, S. (2016). Flexible transport manage- Care.Available at: http://www.audit-scotland.gov.uk/docs/ health/2011/nr_110804_transport_health.pdf ment. In M., Bliemer, C. Mulley, & C. Moutou Handbook CTA. (2012). State of the Sector Report for Scotland 2012. on Transport and Urban planning in the developed world Available at: http://www.ctauk.org/UserFiles/Documents/ (Eds.). (pp. 709–742). Cheltenham, Gloucester, UK and In%20Your%20Area/Scotland/State%20of%20the%20 Massachusetts, USA: Edward Elgar. Sector%20Scotland%202012.pdf PCC and CC. (2013). Transport Issues in Accessing Health and Countryside Agency. (2004). The benefits of providing transport Social Care Services. The Patient and Client Council & to Health-Care in Rural Areas. Final Report to The Coun- the Consumer Council, Northern Ireland. Available at: tryside Agency, prepared by CAG Consultants and the TAS http://www.consumercouncil.org.uk/filestore/documents/ Partnership Ltd, UK. TRANSPORT_ISSUES_IN_ACCESSING_HEALTH_ DfT. (2009). Providing Transport in Partnership – a guide AND_SOCIAL_CARE_SERVICES_REPORT_FINAL.pdf for health agencies and local authorities. Available at: Shimrat, M. (1962). Algorithm 112: Position of point rela- http://www.gov.scot/Resource/Doc/935/0085701.pdf tive to polygon. Communications of the ACM, 5(8), 434. Emele, C. D., Oren, N., Zeng, C., Wright, S., Velaga, N., Nel- doi:10.1145/368637.368653. son, J., Norman, T. J., & Farrington, J. (2013). Agent-driven Transport Systems Catapult. (2016). Mobility as a service: variable pricing in flexible rural transport services. In J. Cor- Exploring the opportunity for Mobility as a Service in chado, J. Bajo,J.Kozlak, P. Pawlewski, J. Molina,V.Julian, R. the UK. Transport Systems Catapult, July. Available Silveira,R.Unland,&S.Giroux Highlights on practical appli- at: https://ts.catapult.org.uk/wp-content/uploads/2016/ cations of agents and multi-agent systems (eds.). (pp. 24–35). 07/Mobility-as-a-Service_Exploring-the-Opportunity-for- Vol. 365 of Communications in Computer and Information MaaS-in-the-UK-Web.pdf Science, Heidelberg: Springer Berlin. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent Transportation Systems Taylor & Francis

A tool to aid redesign of flexible transport services to increase efficiency in rural transport service provision

A tool to aid redesign of flexible transport services to increase efficiency in rural transport service provision

Abstract

Rural areas generally have lower and more dispersed demands for travel which cannot sustain conventional public transport services and consequently have a greater number of flexible and demand responsive transport services operating. These services usually operate on a stand-alone basis, are often subsidized and are typically only accessible by certain passenger types or for specific trip purposes. This generally results in uncoordinated and inefficient transport provision overall. The Flexible integrated transport services (FITS) system featured in this paper has been designed to address this problem. FITS can be used as a planning tool to assess potential benefits from relaxing operating constraints (e.g., a service's operating boundaries), which can potentially suggest service redesign. It also includes the capacity to assign subsidy payments on a trip by trip basis to increase cost efficiency whilst meeting a greater proportion of transport needs. The case study in the paper focusses on transport to health in the Aberdeenshire and Morayshire areas of Scotland in the UK. Despite flexible transport operators receiving public funds to meet passenger needs, this is currently being supplemented by public bodies paying large amounts in taxi fares in instances where there is a statutory obligation to provide travel but where no other suitable transport service exists. The results demonstrate the potential substantial savings which could be realized by allowing transport operators to redesign their services by relaxing constraints and by the reassignment of subsidies: resulting in more passenger demands being met and a reduction in public spending on taxi fares.

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1547-2442
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10.1080/15472450.2017.1410062
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Abstract

JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS , VOL. , NO. , – https://doi.org/./.. A tool to aid redesign of flexible transport services to increase efficiency in rural transport service provision a a b c a Richard Mounce ,Steve Wright , C. David Emele , Cheng Zeng , and John D. Nelson a b Centre for Transport Research, University of Aberdeen, Aberdeen, United Kingdom; Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom; Computing Science, University of Aberdeen, Aberdeen, United Kingdom ABSTRACT ARTICLE HISTORY Received  December  Rural areas generally have lower and more dispersed demands for travel which cannot sustain con- Accepted  November  ventional public transport services and consequently have a greater number of flexible and demand responsive transport services operating. These services usually operate on a stand-alone basis, are KEYWORDS often subsidized and are typically only accessible by certain passenger types or for specific trip pur- constraint relaxation; flexible poses. This generally results in uncoordinated and inefficient transport provision overall. The Flexible transport system; rural integrated transport services (FITS) system featured in this paper has been designed to address this transport; subsidy; surcharge problem. FITS can be used as a planning tool to assess potential benefits from relaxing operating con- straints (e.g., a service’s operating boundaries), which can potentially suggest service redesign. It also includes the capacity to assign subsidy payments on a trip by trip basis to increase cost efficiency whilst meeting a greater proportion of transport needs. The case study in the paper focusses on trans- port to health in the Aberdeenshire and Morayshire areas of Scotland in the UK. Despite flexible trans- port operators receiving public funds to meet passenger needs, this is currently being supplemented by public bodies paying large amounts in taxi fares in instances where there is a statutory obliga- tion to provide travel but where no other suitable transport service exists. The results demonstrate the potential substantial savings which could be realized by allowing transport operators to redesign their services by relaxing constraints and by the reassignment of subsidies: resulting in more passen- ger demands being met and a reduction in public spending on taxi fares. 1 Introduction certain eligibility criteria, e.g., only for elderly people Flexible transport services (FTS) consist of a range of or only for people who are disabled. In the UK many mobility services oer ff ing greater flexibility than reg- services are provided by community transport orga- ular public transport services. Whereas urban flexible nizations, health sector funded organizations, or local transport includes shared taxis, car-pooling, and car- authority departments involved in social care. sharing (Nelson & Wright, 2016)which attemptto Currently, many flexible transport providers are paid a oer ff a greener alternative to solo car use, in rural areas flatratesubsidy or blockgrant regardless of thenumber of the passengers they transport (or are paid the subsidy where there is limited conventional (fixed-route) public provided that they fulfill their quota of trips within a transport, flexible transport providers often fill the gaps given period). This enables these operators to provide providing essential services. This is achieved through a core service to access essential goods, services, and demand responsive transport (DRT) for the general activities (such as local shops, GP surgeries, day care public or more commonly through dedicated services centres) at certain times of day and on certain days of (i.e., transport for specific groups of the population, e.g., the week. However, a common scenario is that vehicles the elderly). These rural FTS are characterized by flexible areunderutilized during otherperiods of theday dueto routing and scheduling of small to medium-sized vehi- insufficient funds to provide additional services and there cles operating in shared-ride mode between pick-up and is little or no financial incentive available to undertake drop-off locations according to passengers’ needs (Mulley or accommodate additional trips outside of their core et al., 2012), usually resulting in a “door-to-door” service. serviceunder theexistingfunding structure. Theremay Dedicated FTS are generally standalone services with CONTACT Richard Mounce r.mounce@abdn.ac.uk Centre for Transport Research, School of Engineering, University of Aberdeen, Fraser Noble Building, Aberdeen AB UE. Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/gits. ©  Richard Mounce, Steve Wright, C. David Emele, Cheng Zeng, and John D. Nelson. Published with license by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/./), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 176 R. MOUNCE ET AL. then be unmet demand, which is clearly an undesirable The benefits of FITS detailed above can be realized situation. In addition, these services are often largely through the use of the offline version of the FITS tool. uncoordinated and poorly promoted. In some areas the TheFITSsystemcan also operateinanonlinemode, tight eligibility restrictions lead to multiple services oper- interfacing between passengers and transport operators atinginthe same places at thesametime, each catering in real-time (Emele et al., 2013). This is conceptualized as for different trip purposes and user categories; this is a multiagent system (Ferber, 1999)comprisingavirtual very costly and inefficient. In other more rural areas the marketplace with three types of agents: tight eligibility restrictions lead to a much more limited 1. Passenger agents, operating on behalf of service, in terms of operating area and times, available to passengers, only particular users for particular trip purposes: this is 2. Transport operator agents, operating on behalf of ineffective for those whose trips do not fall within these transport operators, restrictive constraints, resulting in very limited choice for 3. The marketplace agent, which mediates between passengers. the passenger and transport operator agents. The flexible integrated transport services (FITS) The paper is organized as follows: Section 2 provides a system has been designed to address this problem of detailed overview of the FITS system, including the data inefficient transport service provision in rural areas. The requirements as well as the modes of operation. Section 3 FITS tool affords the opportunity to identify flexible is on the case study area and includes detail of the local transport services which could fulfill currently unmet context and results from the test runs. Finally, Section 4 passenger trip requests if certain constraints were to be discusses the benefits and future uses of the FITS tool and relaxed. Such an approach is of potential benefit to flexible provides conclusions. transport operators looking to extend their services and generate additional revenues.Itisalsoofpotential ben- 2 The FITS system efit to public sector organizations with an obligation to provide equal access to individuals for key services (e.g., 2.1 Data requirements access to education, social care, and health services). In cases when there is no existing public transport which is FITS requires data about passenger trips to ascertain suitable, these organizations have an obligation to pay for, whether passengers are both physically able and eligi- or at least subsidize using public funds, the use of taxis by ble to use given transport services. The following data is individuals. In addition, public sector organizations may required for each trip: pay block subsidies to transport operators to operate their 1. Journey origin and destination address. services. The FITS system can be used to demonstrate the 2. Expected time of departure or desired arrival time. effects of restructuring this system of subsidy payments: 3. Age group, chosen from: under 16, 16–21, 22–54, in place of only block subsidy payments, a more incentive- 55–59, and 60+. based structure is proposed where a lower block subsidy 4. Mobility status, chosen from: able-bodied, dis- is received to retain the basic service, but is supplemented abled (wheelchair user), disabled (other). In by additional subsidy payments to transport operators addition thereisanoptiontochoose“unable for operating outside of their usual operating constraints, to use regular public transport,” which includes e.g., operating outside of their usual operating times and the case where this is due to lack of provision areas, or transporting additional types of passengers. The or of frequency). Wheelchair users are further FITS tool can estimate the net savings through reductions categorized as “electric,” “nonelectric nonfolding” in taxi fares that are possible through the relaxation of and “nonelectric folding (and able to sit in car/bus constraints. seat).” Flexible transport operators can utilize the FITS tool 5. Journey purpose, chosen from: health appoint- to specify the extent to which they are prepared to relax ment, shopping, social care, leisure/visiting their core service constraints on when, where, and who friends, school/education and work/commuting. they are prepared to carry and it also allows them to 6. Whether there is a clinical need for ambulance ser- stipulate the financial compensation (within legislative vice transport. boundaries)theywouldrequiretomaketheserelaxations. 7. Whether there is a need for an escort (e.g., a carer This provides a mechanism by which flexible transport or other assistant) to accompany the passenger (to operators (including community transport providers) assist them). can generate additional revenues for accommodating 8. Therelativeweightingsofthe valueoftraveltime, transporttohealthpassengerswho otherwisewould money, and number of vehicle changes (for the need to be carried by taxi. online operation of FITS only). JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 177 Figure . FITS operator data input tool. Clearly there are certain restrictions that are placed 7. Penalty surcharges for operating outside defined on services that should not be violated if a service is operating hours (in bands). to remain legitimate and reputable, e.g., government 8. Passenger type eligibility penalty surcharges regulations, vehicle capacity etc. However, there are other for those passenger types who are normally discretionary constraints that operators assign to their ineligible (these are optional in that the operator services as they choose. Figure 1 shows the FITS operator has the option to keep these types as ineligible data input tool. The operating area can be drawn as regardless of any surcharge). a polygon in Google maps and the accompanying data The fare structure information consists of the entered into a web template. All this data is then imported following: into the FITS system. The following information needs to 1. Whether the service charges fares. be provided to theFITStoolfor each service: (notethat 2. Fares within mileage bands. if there are day-to-day variations, such as to the hours 3. Return fare multiplier. of operation, then these need to be defined as separate 4. Percentage discounts for over 60s and under 16s. services): 5. Whether escorts are charged a fare. 1. Operatingtimes:daysofthe week andhours of 6. Whether the service charges for dead mileage and operation. the location for this to be calculated from. 2. Operating area. 2.2 Searching and ranking of transport options 3. Fare structure (including concessions). 4. Vehicle specifications (including seat /wheelchair If the passenger can use conventional public trans- capacities and vehicle access). port, the FITS tool generates conventional fixed-route 5. Passenger type (age, mobility status, journey pur- public transport options using the Google Maps Transit pose) eligibility information. journey planner via the Google Directions application 6. Penalty surcharges for operating outside defined operating area (in bands). http://www.google.com/transit 178 R. MOUNCE ET AL. lowest generalized cost. For the online version of the FITS programming interface (API): parameters for this API tool, the transport options with the lowest generalized include desired arrival/departure time, mode, whether to cost are presented to the user to choose from. minimize transfers etc. The distance that different cate- gories of passenger (e.g., able-bodied, disabled, elderly, etc.)are assumedtobeableand willingtowalktoaccess 2.3 Constraint relaxation and surcharges public transport is set to a maximum value in order Sections 2.1 and 2.2 describe how FITS provides a tool to limit the number of options returned from Google which checks the operating criteria and constraints of Transit. all existing transport services in an area to identify suit- Flexible transport options are also generated in the able transport options for specific trip demands. For trip FITS tool by searching the available flexible transport ser- demands which cannot be fulfilled by current transport vices (details of which are input to FITS by operators services, the FITS tool provides the option to identify the as described in Section 2.1). These potential transport flexible transport services which could fulfill the passen- options are deemed suitable if the journey origin and des- ger request if certain constraints were relaxed. This con- tination are within the service’s operating area (which can straint relaxation takes into account the preferences of the be established using the ray method (Shimrat, 1962)since operatorsthemselvesaswellasthe compensation pay- theoperating area is defined by apolygon); thejourney mentsaflexibletransport operator wouldbepreparedto is within the operating times of the services; and also if accept for a given relaxation request. These compensation the passenger meets the service’s other eligibility criteria costs can be thought of as surcharges imposed by the flex- (e.g., age, mobility status etc.). The travel time for volun- ible transport operator to extend their core funded ser- tary car services (which involve volunteers driving their vice. Relevant legislative restrictions which place limits on own cars) is assumed to be the same as for a taxi, whereas relaxations and compensation payments are also consid- travel times for door-to-door bus services are multiplied ered in the process. by a penalty factor (or travel time ratio) of 1.5 to reflect Three types of surcharge, as identified in Section 2.1 the fact that they may need to divert for additional passen- are: ger pick-ups (the value of 1.5 is based on our experience 1. Penalty surcharges for operating outside defined of DRT services in rural areas). Simulation studies have operating area (in bands). shown this penalty factor to range from one, where only 2. Penalty surcharges for operating outside defined one passenger is carried, to over vfi e when there are a high operating hours (in bands). number of trip requests that each vehicle needs to accom- 3. Passenger type surcharges for those passenger modate.Inruralareas,whenrespondingtotriprequests types who are normally ineligible for mainly health purposes there are likely to be relatively In the instances where constraint relaxation is neces- few diversions to pick up additional passengers and hence sary to fulfill a passenger demand, the total fare f charged a relatively low value of travel time ratio is reasonable. by an operator is given by: A generalized cost g can be calculated for each possible transport option using the formula: f = f + d (2) p p g(t, f , t , c, t ) = t + ft + ct (1) f c f c where f is the standard fare for the operator to take pas- senger p and d is the surcharge for the operator to take where t is the travel time, f is the fare paid, t is the f p passenger p. The standard fare will depend on the passen- valueoffareinterms of travel time, c is the number of ger’s journey origin and destination and may include dead interchanges, and t is the average value of an interchange mileage. The surcharge will be the sum of all the penalty in termsoftraveltime(note that t and t are requested f c from the passenger in the booking entry form). Note surcharges identified above. Note that these surcharges firstly that for public transport options the travel time are additive, e.g., if the passenger’s origin and destination can be split up into in-vehicle travel time, waiting time, are both 5 miles outside of the usual operating area then and walking time with suitable value-of-time weighting thesurcharge will be twicethatfor operating5miles out- factors applied to each .Notealsothatthe generalized side of theusual operatingarea. In thecaseofthe origin cost defined in Eq. ( 1) is in time units; this is appropriate or destination being outside of the operating area the dis- sincewegenerally do nothaveany informationavailable tanceoutside of theoperating area canbecalculatedas regarding an individual passenger’s value of time in terms the minimum distance to any of the line segments which constitute the boundary (since the boundary is defined by of money. For the offline version of the FITS tool, each a polygon). The generalized costs of the options are cal- trip demand is assigned its transport option which has the culated using Eq. (1) but with the revised fare defined in https://developers.google.com/maps Eq. (2). Allowing these relaxations will obviously result https://www.gov.uk/government/publications/webtag-tag-unit-m-- in more transport options being available to passengers public-transport-assignment-modelling JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 179 Figure . Flow of data through the FITS system in the case of hospital appointment demands. overall, but with the accompanying cost incurred through the UK. The UK’s National Health Service (NHS) has a the operator surcharges. statutory duty to provide transport to get nonemergency Figure 2 presents the flow of data through the FITS sys- patients, but who have a medical need while being trans- tem in the case of hospital appointment demands. ported, to hospital for treatment. In many areas it is the Ambulance Trust that provides this service. For patients not deemed to have a medical need whilst being trans- 3 Case study ported the responsibilities for transport are less clear. In the UK, local authorities are obliged to assess whether TheFITSplanning tool hasbeenapplied in theruralcase people living in their area, particularly households on low study setting of Morayshire and Aberdeenshire in North incomes and people without cars, are able to reach key ser- East Scotland to explore how flexible transport service vices and activities safely, reliably, aoff rdably, and with rel- redesign can lead to potential increases in efficiency when ativeeasebypublictransport.Eachlocal authoritymust providing transport to health trips. Before discussing the thenproduceanactionplantoidentifyhowtheyandtheir results we briefly describe the national transport to health partner organizations will improve any gaps in accessibil- context. ity (for example, in our case study area the transport to health agenda is shaped by the Grampian Health Trans- port Action Plan team which is a consortium of local 3.1 Context authorities, NHS and transport agencies). This involves To set this work in context it is necessary to understand financially supporting bus operators (commercial or whoisresponsible forproviding transporttohealthin community) to provide necessary services, or filling the 180 R. MOUNCE ET AL. Table . Journeys by mode of travel to attend hospital and other health appointments in Scotland. Travel Mode Walk Car Driver Car Passenger Public Transport + Other Taxi Proportion .% .% .% .% .% Source: Scottish Household Survey (–) gaps with local authority in-house bus services. Whilst 3.2 Results this can be planned to some degree for certain types The FITS system was tested offline in order to assess of regular trip it is more difficult for hospital appoint- its potential. The trial was done using a set of typical ments which are largely unpredictable and are often one- health-related passenger trip demands along with trans- off demands. As a result, local authorities often resort port operator data (as detailed in Section 2.1)for the to using taxis to meet their responsibilities in provid- Morayshire and North-West Aberdeenshire area. The ing access to health appointments. Whilst health boards passenger trip demands were produced using a simulated andTrusts, understandably,wishtoconcentrate their demand generator, which was based on actual annual out- efforts and funding into advancements in clinical care, patient appointment data from nine origin districts (elec- poor access means that whilst those patients who have toral wards) to vfi e destination hospitals in the Morayshire access can enjoy improving clinical care, others without and North-West Aberdeenshire area (the Hospital loca- access frequently may not enjoy even basic levels of health tions and ward boundaries are illustrated in Figure 3). care, let alone any advancement. As a result, they also In total there were 107,120 annual outpatient appoint- support transport to health to ensure equal access. The ments at the vfi e destination hospitals originating in the result is often an uncoordinated system of funding trans- nine origin districts. This generates 214,240 annual trip port to health resulting in inefficient, poorly planned, demands, or 4120 trip demands per week. The distribu- and uncoordinated transport services. Whilst there have tion of the origin locations (passenger pick-up points) been several initiatives to better integrate funding and within each ward was generated by random selection from service provision (DfT, 2009), these have often strug- the full set of postcodes in each ward (the postcode loca- gled to get agreement on shared funding and establish tions give a reasonable representation of the spatial dis- joint commissioning for transport services. It remains tribution of population across the ward, and each post- thecasethatapart from theAmbulance Trusts’none- code provides a good proxy for the location of the patient’s mergency patient transport services, taxis are a main- address). Note that simulated passenger age was added stay for patients accessing health appointments from rural to the postcode dataset for each ward based on patient areas when limited or no public transport is available or age profiles for outpatient appointments and simulated suitable. mobility status was added based on simulated age. There- We see from Table 1 that 78% of health appointments foretheselectionofapostcodeprovidesthesimulatedori- in Scotland are accessed by foot or as a car passenger or ginpickuppoint,passenger age, andmobilitystatus. driver;the remaining22% arebybus,taxi, or otherpub- From Table 2 we seethere areanestimated 25% of hos- lic transport. Table 1 relates to hospital and other health pital appointment trips made by public transport and taxi. appointments including GP surgery visits. The data also This 25% multiplier was applied to the total number of relatestothe wholeofScotland. As such thedistances outpatient appointments to get the simulated daily pas- involved will tend to be shorter than for the hospital-only senger demand to be run through FITS; this was done vfi e appointments in the generally rural area of our exam- times to give vfi e different passenger demand sets for one ple. As a result, in our test (described in Section 3.2)we week, i.e., vfi e week days. In total this produced 515 pas- consider a slightly lower proportion of access by walking sengers, each making an outward and return trip, giving (10.9%) and a similarly higher proportion accessing by a total of 1030 trips. public transport and taxi (25%). Table 2 gives the expected Thetransport operator servicedatawas sourced weekly journeys by mode to outpatient appointments in from publicly available data as well as directly from the the study area, based on these slightly adjusted mode operators. This provided operating area boundaries, fare share proportions. Table . Estimated weekly journeys by mode to attend hospital appointments in the study area. Travel Mode Walk Car Driver Car Passenger Public Transport + Other Taxi Proportion .% .% .% .% .% Weekly Trips      JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 181 Figure . Map showing the districts (electoral wards) and hospital locations used in the testing. information, eligibility criteria, and core operating times saving if the overall fare charged by the flexible bus opera- (09:30–11:30 and 13:30–15:30) for seven flexible bus tor (including the penalty surcharges) is cheaper than the services across the study area. Operator surcharges for equivalent taxi fare (calculated using £2.40 flag drop plus constraint relaxation were estimated from information £1.80 per mile). These potential savings were the taxi fare provided from the operators. that wouldbepaidminus thetotal fare that wouldbepaid First, the FITS tool was run using this data without to the flexible bus operator. Whilst the beneficiary of these any constraint relaxation (i.e., as the services currently savings may be the private individual if they are prepared operate). In this first run, approximately 80% of the sim- and able to meet the high costs of a taxi trip, in most cases ulated trips were found to have at least one potentially it will be the local authority or health board which meets suitable transport option (either a conventional fixed- most of the cost of the taxi on behalf of the passenger. route service or an existing flexible service). However, Table 3 shows these potential savings for a single day (Day there remained a substantial number of passenger trip 1) of simulated demand data and Figure 4 shows the loca- demands for which the passenger did not have a suitable tion of each passenger trip demand. For passengers whose non-taxi travel option, e.g., because they required a door- total fare (including operator surcharges) is less than the to-door service and there was no suitable flexible trans- taxi fare there are potential savings, e.g., for the outward port provider operating at that time and/or within that trip of passenger 1 the trip distance is 26.4 miles, the taxi area. There were 194 such trips (counting the outward and fare would be £49.92 and the flexible bus cost including return trips as separate trips since passengers could have surcharge would be £23.60 (£7.60 basic fare plus £12 for an option for one but not the other). At present, use of a picking up 8.9 miles outside their normal area and £4.50 taxi is the only transport option available to these passen- for extending their normal operating hours by 0.5 hours) gers to be able to access their appointment. It is assumed resulting in a saving of £26.32 compared to using a taxi. therefore that they will all access the hospital by taxi. This Note that there were a small number of passengers whose is areasonableassumption sincethislevel of taxi useis relaxation was unrealistic because the ratio of relaxation consistent with the estimated use of taxis in the study area distance to relaxation time was too high, i.e., above 40 basedonthe Scottish HouseholdSurveydatadetailedin miles of relaxation distance per hour of relaxation time, Table 1. These 194 passenger trip demands were noted and these passengers were filtered out from the savings. andthenasecond runwas carried outwithconstraint Table 4 gives these potential savings (compared to taxi relaxation: in this case, it was just the flexible transport costs) foreachofthe vfi edaysofsimulated demand as providers’ operating times and areas that were relaxed in well as the total (weekly) savings. Note that these savings exchange for surcharge payments. This resulted in over are after accounting for the total cost of the trip (including two thirds (132 out of 194) of the originally unmet passen- thesurcharges)paidtotheflexiblebusoperator;hencethe ger trip demands having suitable travel options using flex- total surcharges listed in Table 4 are for information only. ible bus services. In each of these cases, there is a potential It should also be noted that the savings in Table 4 were the 182 R. MOUNCE ET AL. Table . Potential savings for day . Flexible Bus Service Hospital Operating area Operating time Passenger Trip No. destination Dist. (miles) Relax. dist. (miles) Relax. time (hrs) Base fare (£) surcharge (£) surcharge (£) Total fare (£) Taxi fare (£) Saving (£)  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . .  .   . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s .  . .  . . .   Dr. Gray’s .  . .  . . . .  Dr. Gray’s . .  . .  . .   Dr. Gray’s . .  . .  . .   Dr. Gray’s . .  .   . .   Dr. Gray’s . .  . .  . .   Dr. Gray’s . . . .  . . . .  Dr. Gray’s . .  . .  . .   Dr. Gray’s . .  .   . .   Dr. Gray’s .  . .  . . . .  Dr. Gray’s . .  .   . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Dr. Gray’s . . . .  . . . .  Turner . . . .  . . . .  Chalmers  .  .   . . .  Chalmers  .  .   . . .  Dr. Gray’s . . . .  . . . . Total . . JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 183 Figure . Distribution of currently unmet demands which could be met through constraint relaxation at lower cost than using a taxi:  day of simulated data. maximum, since not necessarily all this cost will be met by Table . Total weekly savings (% of maximum possible) for differ- ent levels of constraint relaxation of time and distance. the public authorities as noted above. Table 4 suggests that the potential savings to the public Relaxation time (hours) authorities (due to a reduction in expenditure on trips by Relaxation distance (miles)  .  . taxi) are up to £2196 per week, or equivalently £114,000  . . . . per annum.  . . . . Table 5 shows the percentage of the total potential  . . . .  . . . . savings per week for different levels of constraint relax-  . . . . ation for both time and distance together, and illustrates  . . . .  . . . . clearlythe necessityfor time anddistanceconstraints to  . . . . be relaxed together in order to allow significant savings  . . . . to be made. In addition to the level of constraint relax-  . . . .  . . . . ation, the potential savings when applying the FITS tool  . . . . in a particular instance will depend also on the particulars of thetransport demands(i.e.,iftheyare closetoexisting operating times and areas). 4. Discussion and conclusions 4.1 Immediate benefits from the use of FITS as a Table . Potential savings by day. planning tool Total Direction of No. of No. of surcharges Total savings The main beneficiaries of the savings calculated in Sec- Day travel passengers savings paid (£) (£) tion 3.2 are a) individuals who may pay all or part of the Day  Outward    . taxi fare; and b) public sector organizations which pay all Return   . . or part of the taxi fare where there is an obligation to pro- Total   . . Day  Outward   . . vide transport to health. In rural areas where there are no Return   . . other transport alternatives the latter case is prevalent. Total    . Day  Outward   . . If the £114,000 annual savings are extrapolated from Return   . . thecasestudy area to thewhole of ruralScotland(i.e., Total    . Day  Outward    . scaling up proportional to rural population) there are esti- Return   . . matedpotential savingsofupto£1.8million perannum. Total   . . Day  Outward   . . Although not all these estimated potential savings should Return    . be attributed to spending by public authorities (since Total   . . some of these taxi costs will be met by passengers them- Total Outward   . . Return   . . selves)itislikelythatalargeproportionshouldbe. The Total   . . possible savings are significant since the total spend on 184 R. MOUNCE ET AL. transport for patients by NHS boards in Scotland was £4.5 services can ensure the core services evolve to incorporate million (Audit Scotland, 2011). This figure includes reim- changing health and social care demands, thereby keep- bursement of £2.5 million for the Healthcare Travel Costs ing the additional subsidy payments within manageable Scheme, much of which is spent on taxis in rural areas. levels. The surcharges in Table 4 are payments that would be made to the flexible transport providers, potentially 4.3 Future uses of the tool on behalf of the passenger by the public authorities. These surcharges are significant (up to £1577 per week As mentioned above, the FITS tool has been devel- or £82,000 per annum) and hence potentially provide a oped to operate in both online and offline modes. In valuable revenue stream for these operators. This could itsonlinemodeitisatool whichutilizesthe operat- be up to £1.3 million per annum across rural Scotland. ing requirements and constraints of all existing trans- This is equivalent to over 40% of the £3 million in total port services in a defined area to identify the trans- grants received annually by the community transport port services which potentially could fulfill passenger trip sector (the main providers of flexible transport services requests. It then presents these to the passenger as a list in rural areas) in Scotland from statutory bodies (CTA, of transport options, ranked according to their prefer- 2012)and more than three times thelevel of fundingthat ences. There is clearly the potential to build constraint the community transport sector currently receives from relaxation into the online operation of FITS. This would health bodies (Audit Scotland, 2011). open the possibility of incorporating the FITS constraint relaxation approach into emerging Mobility-as-a-service (MaaS) systems (Heikkilä, 2014;Hietanen, 2014; Kamar- 4.2 Longer term benefits for transport to health gianni,Matyas, Li,&Schafer, 2015, Transport Systems Part of the savings identified above for local authorities Catapult, 2016). Within MaaS, an individual’s travel needs andNHS boards couldbeusedtofundmorepatient (usually satisfied by owning a car), are met by a range of services that include car leasing, car clubs, carpooling, transport to reduce the number of “Did Not Attends” community transport, cycle, and taxi services in combi- (DNAs). There is little research on what proportion of nation with “traditional” public transport. Arguably, this these are attributable to transport issues, but figures rang- could remove the need and cost of running a second car, ing from 20% (PCC and CC, 2013) up to 69% (Coun- or even remove theneed forowningany caratall.Ifcom- tryside Agency, 2004) in more rural areas have been munity transportservicescould adapttheir serviceoeff r- reported. The number of DNAs stands at over 7600 per annum in our case-study region alone. Each DNA was ing, through suitable constraint relaxation, in response to estimated to cost the NHS in Scotland approximately passenger requests then these community transport ser- £112 (Audit Scotland, 2011). If only 20% of these can vices and other flexible transport services could oer ff a be avoided by oeff ring additional door–to-door flexible much stronger component within MaaS solutions in rural transport through FITS constraint relaxation, this would as well as urban environments. reduce DNAs in the case study area by 1520 per annum, with an associated cost saving of £170,240 per annum 4.4 Conclusions (£2.7 million per annum if scaled up to the whole of rural Scotland). In addition to this are patient-cancelled The paper showed how the FITS tool could help increase appointments, which is an even higher number and which efficiency in transport provision to health appointments also incurs a cost to the NHS. Some of these cancellations in rural areas, by demonstrating its benefits in a case study. could also potentially be avoided with more extensive The flexible transport services in the case study area of door-to-door transport provision. As well as the finan- Aberdeenshire and Morayshire, which is typical of rural cial cost of missed appointments, one must also factor in areas across the UK and many developed countries world- the benefits to health of patients being able to attend their wide, are highly subsidized and have strict eligibility cri- appointments. teria; this has resulted overall in an inefficient patchwork Over time, if shifting demands suggest a different core of transport provision. The FITS system allows the relax- service provision then this can be specified in future ation of transport operators’ constraints in exchange for contracts with flexible transport providers in return for operators receiving surcharge payments. The FITS tool the statutory grants received. With improved knowledge was applied to a simulated demand set and substantial of the spatio-temporal distribution of health and social potential savings were identified by relaxing operating care related demands which the system captures (through constraints. Additional benefits were also identified in the data on unmet trip requests and requests requiring addi- form of increased revenue to transport operators and the tional subsidy payments) the commissioners of transport potential to reduce the number of missed appointments. JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 185 As well as identifying such benefits, FITS is also useful as Ferber, J. (1999). Multi-agent systems: An introduction to dis- tributed artificial intelligence .New York:AddisonWesley a tool for decision makers to consider modifying funding Longman. mechanisms in a way which motivates operators to amend Heikkilä, S. (2014). Mobility as a service – A proposal for action their service provision in order to better meet passengers’ for the public administration, Case Helsinki (MSc disserta- transport to health needs. tion), Helsinki, Finland: Aalto University. Hietanen, S. (2014). ‘MobilityasaService’–thenew transport model? Eurotransport, 12(2), 15 2–4. Funding Kamargianni, M., Matyas, M., Li, W., & Schafer, A. (2015). Fea- sibility Study for “Mobility as a Service” concept in London. This research was supported by the Research Councils UK Report – London, UK: UCL Energy Institute and Depart- Digital Economy programme award (reference: EP/G066051/1) ment for Transport. to the dot.rural Digital Economy Hub, at the University of Mulley, C., Nelson, J., Teal, R., Wright, S., & Daniels, R. Aberdeen. (2012). Barriers to implementing flexible transport services: An international comparison of the expe- riences in Australia, Europe and USA. 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Available at: tryside Agency, prepared by CAG Consultants and the TAS http://www.consumercouncil.org.uk/filestore/documents/ Partnership Ltd, UK. TRANSPORT_ISSUES_IN_ACCESSING_HEALTH_ DfT. (2009). Providing Transport in Partnership – a guide AND_SOCIAL_CARE_SERVICES_REPORT_FINAL.pdf for health agencies and local authorities. Available at: Shimrat, M. (1962). Algorithm 112: Position of point rela- http://www.gov.scot/Resource/Doc/935/0085701.pdf tive to polygon. Communications of the ACM, 5(8), 434. Emele, C. D., Oren, N., Zeng, C., Wright, S., Velaga, N., Nel- doi:10.1145/368637.368653. son, J., Norman, T. J., & Farrington, J. (2013). Agent-driven Transport Systems Catapult. (2016). Mobility as a service: variable pricing in flexible rural transport services. In J. Cor- Exploring the opportunity for Mobility as a Service in chado, J. Bajo,J.Kozlak, P. Pawlewski, J. Molina,V.Julian, R. the UK. Transport Systems Catapult, July. 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Journal

Journal of Intelligent Transportation SystemsTaylor & Francis

Published: Mar 4, 2018

Keywords: constraint relaxation; flexible transport system; rural transport; subsidy; surcharge

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