HIGH-SPEED RAIL FOR REGIONAL TRANSPORT: A CASE STUDY FOR SICILY

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1 HIGH-SPEED RAIL FOR REGIONAL TRANSPORT: A CASE STUDY FOR SICILY Francesco Russo, Giovanna Chilà, Giuseppe Musolino, Corrado Rindone Department of Computer Science, Mathematics, Electronics and Transportation Mediterranea University of Reggio Calabria, Reggio Calabria (Italy) phone: , fax: giuseppe.musolino@unirc.it PROGRAMME COMMITTEE: Rail THEME: Planning and economics of heavy rail passenger transport Keywords Regional high-speed rail, accessibility, travel demand, spatial location of activities. 1. INTRODUCTION Regional high-speed railways are attracting ever-increasing attention. Newly available technologies for rail infrastructure, railway control systems and rolling stock are available on the market ensuring the feasibility of this transport system. Given the reduction in costs of such supply components, breakeven between costs and revenues may be reached more easily than in the past. In 2009 the US government promoted investments in passenger high-speed railway systems in order to reduce traffic congestion and pollution. The main European countries have proposed various technical and management solutions to implement high-speed railway for passengers, freight or mixed components of mobility. In the literature high-speed railways have been proposed at the regional level, where a region may be defined as an area including one or more countries (or states) or an area which is a part of a country. In this context we refer to the second meaning. However, to our knowledge there has been no analysis of the progressive effects on mobility and on the socio-economic structure deriving from a temporal progression of interventions to implement regional high-speed railway systems. This paper presents an approach to analyse the potential effects of progressive development of a high-speed passenger railway system in a regional context. Effects on passenger mobility and the socio-economic structure are estimated through a system of models. Intervention definition is based on a transportation plan that is a product of a planning process consisting of different planning dimensions (space, time and study-in-depth) and interactions among subjects involved ( FHA and FTA, 2007; Russo and Rindone, 2007). In this study, space (regional) and study-in-depth (practicable) dimensions are fixed, while time dimensions to implement a high-speed railway are considered. Progressive realisations of interventions generate progressive benefits for users and the community. The analytical approach adopted in this paper is in line with Italian Transport Ministry guidelines (2007) (Figure 1). Interventions are designed on the basis of mobility needs satisfaction that affects definition of the following: Association for European Transport and contributors

2 managerial and normative strategies specified in planned transport services; non-material and material structural strategies specified in planned transport infrastructures. As regards the spatial scale, mobility needs have to be specified for the following distance segments: short distance mobility, that includes urban and metropolitan mobility needs; regional mobility, that includes intraregional mobility needs; middle distance mobility, that includes interregional and national mobility needs; large distance mobility, that includes European, Mediterranean, international and intercontinental mobility needs. In this paper we focus on regional mobility needs. Mobility needs satisfaction Services planning (Managerial and Normative) Infrastructures planning (Non-material and Material) Figure 1 Analytical approach (Source: Italian Transport Ministry, 2007) The planning process starts by analysing the regional transport system in its current configuration through surveys. To quantify the effects associated to interventions on mobility and socio-economic system, a system of simulation models is proposed and applied both for the current and scenario mobility. An architecture of a system of models able to forecast these effects is required. The system of models should include the following elements: a supply network model, able to simulate the performance of supply elements, such as travel times and accessibility; a demand model, able to forecast variation in user choices, such as transport mode, destination and emission; a land-use transport interaction model able to forecast the spatial location of socio-economic activities. Our analytical approach is applied to study effects arising from the new supply configuration of the regional public transport system in Sicily (Italy, UE). We analyse a new regional mobility model, whose main component is a high-speed railway supplying inter-city passenger services. This mobility model is developed according to the Regional Transportation Plan (Sicily Regional Authority, 2004). To design a new configuration of the regional railway system in Sicily, a time-line of planned interventions is proposed. Interventions consist in creating new services, new rail facilities and new rolling stock. Planned interventions will be out stepwise to bring about a progressive reduction in travel times. The paper is structured in the following sections. In section 2 the literature on simulation models and on studies about effects of high-speed railway system is reviewed. Section 3 presents the architecture of a system of models, able to predict the effects of interventions on mobility and socio-economic system. Section 4 reports an application to Sicily, starting from a survey of current regional mobility. Interventions generate effects distributed in time: at the operative scale, interventions produce short-term effects that involve regional mobility in the path dimension; at the tactical scale, interventions produce medium-term effects that involve regional mobility in terms of mode and distribution. Strategically, Association for European Transport and contributors

3 interventions produce long-term effects that involve regional mobility in terms of emissions and the spatial location of socio-economic activities. Final considerations are presented in section LITERATURE REVIEW This section is divided into two parts. The first part recalls main simulation models that allow the quantification of effects associated to transport interventions on mobility and socio-economic system. In the second part, studies about effects of high-speed railway system are reported. 2.1 Simulation models Simulation models of transport and socio-economic systems generally include: a supply network model, able to simulate the performance of supply elements; a demand model, able to forecast variation in user choices; a socio-economic activities location model able to predict the spatial distribution of socio-economic activities. Among supply models we refer to network models, with a graph and cost functions. A general formulation of a (congested) network model consists of a path costs vs. link costs consistency and of a path flows vs. link flows consistency relationships. For private systems graphs may be primary vs. dual and link cost functions may be aggregate vs. disaggregate. A classification and a general description of supply models for private systems is reported in Cascetta (2001). For transit systems we refer to network models based on topological-graph structure, in order to represent the spatial organisation of the physical and functional elements of the system (Nuzzolo and Russo, 1997; Russo et al., 2002; Nuzzolo et al. 2003). In this approach three different sub-graphs are defined (infrastructural sub-graph; service sub-graph; access/egress sub-graph). Sub-graph services may be represented by two different approaches (Nuzzolo et al., 2003): the aggregate line-based approach usually represents high frequency and low regularity services; the disaggregate runbased approach usually represents low frequency and high regularity services and the characteristic element is the run with explicit representation of time (diachronic network). Demand models are a fundamental tool for most problems in the planning and management of transport systems. Travel demand is usually expressed by origindestination matrices, whose elements represent the number of users, belonging to a socio-economic segment, travelling from each origin to each destination in a defined time period by each mode of transport. Several mathematical models to simulate travel demand are proposed in the literature. These are based on different assumptions and can be subdivided in relation to different elements. In most cases, these models belong to discrete choice models (Domencich and McFadden, 1975; Ben Akiva and Lerman, 1985; Cascetta, 2001). Usually, discrete choice models are derived under assumption of utility-maximizing behaviour by the decision maker and are applied according to a static approach, even though in the literature other approaches can be considered, as dynamic and sequential (Russo and Chilà, 2008). Demand models assume the socio-economic system as constant. So, at strategic scale, the effects of supply modifications on level and spatial distribution of socio- Association for European Transport and contributors

4 economic activities is simulated by means of land-use transport interaction models. Different modelling approaches are present in the available literature, which are generally grouped into three main categories: spatial micro-economic, spatial interaction and spatial accounting models. A detailed state-of-the-art on land-use transport interction models is reported in Russo and Musolino (2008). 2.2 Studies about effects of high-speed railway systems Studies concerning effects of railway projects on mobility and on level and spatial distribution of socio-economic activities are mainly oriented to identify and estimate effects of national high-speed railways projects. Among the others, we recall some papers estimating the effects of the japanese Shinkansen (Ueda and Nakamura; 1989; Koike at al., 2000; Yao and Morikawa, 2005), the french TGV (Bonnafous, 1987), the Sidney-Canberra corridor in Australia (Hensher, 1997); the high-speed rail in Spain (Coto-Millan et al., 1997; Lopez-Pita et al., 2005; Inglada and Coto- Millán, 2004); the Dutch Maglev project (Oosterhaven and Elhorst, 2003); the highspeed railway in Italy (Cascetta et al., 2008). Effects of regional high-speed railways have been studied since few years ago such high-speed railways in Sweden (Froidh, 2005), France (Torchin et al., 2008) and Kent (Pownall et al., 2008). From the literature review some general considerations may be drawn. The highspeed railways projects, generally, improve accessibility with positive impacts on connecting different regional areas, on (re)-distributing population and employment and on reducing regional discrepacies in development. In other words, high-speed railways act as catalyst for regional development. But, they do not balance regional development unless integrated planning is undertaken to ensure that such a balance is achieved. There is a lack of representation of the deployment over time of effects on mobility and on socio-economic system, given that the railway projects were realized step-by-step over several-years time periods. Moreover, while in the literature experiences effects generally spread over the regional boundaries, involving also inter-regional mobility; in Sicily effects of the high-speed railway project on mobility and on socio-economic system may reasonably considered bounded inside the island area. 3. PROPOSED MODEL SYSTEM ARCHITECTURE In this section we present an architecture of a system of models able to predict the effects of interventions regarding the regional public transport system on mobility and socio-economic system (Figure 2). The system of models includes a supply network model to simulate the performance of supply elements such as travel times and accessibility; a demand model to predict variation in user choices (such as path, modes, destination and trip choice); a socio-economic activities location model to predict the spatial distribution of activities (population and employment). The system of models has a hierarchical structure, where each choice in the hierarchy is executed conditionally upon the higher level choices; the higher level choice is influenced by the expected maximum (dis)utility (logsum term) of lower level choices. The proposed system of models supports estimation of three types of effects: shortterm effects that involve path choice; medium-term effects that involve mode and destination choices; long-term effects that concern the choices of making a trip and Association for European Transport and contributors

5 location of residential and economic activities. SE i,... Location choice Disutility s O i, SE i Emission choice Accessibility Long-term D j, (O i, SE i) Destination choice LOGSUM m.. M m (O i, D i, SE i).. P k (M m, O i, D i, SE i) Mode choice Path choice LOGSUM p Disutility k Medium-term Short-term Supply Legend: model, data, active connection, non-active connection i, zone i; j, zone j; SE i, population and employment in i; O i, origin in i; D j, destination in j; M m, mode m; P k, path k, LOGSUM, log sum term, disutility s, location disutility of sector s. Figure 2 Model system architecture 3.1. Supply network model Supply models are represented by a network model, composed by a graph and cost functions. Different supply models are specified for private and transit systems. For private systems, cost functions adopted for extra-urban roads and highways are reported in Russo (2005). For transit system supply models, three different subgraphs are constructed: the infrastructural sub-graph, service sub-graph and access/egress sub-graph. The cost function for the service sub-graph related to the bus (or rail) services is specified as: t od,bus(rail) =min{t od,bus(rail) c } c where c is an index representing a generic run from origin o to destination d in the period of reference; t od,bus(rail) c is estimated from Association for European Transport and contributors

6 t od,bus(rail) c =L od /v bus(rail) +t w,bus(rail) +t transfer,bus(rail) in which L od is the minimum distance between the province of origin o and that of destination d, calculated on the transit network; v bus(rail) is the average speed for the bus mode; t w,bus(rail) is the waiting time at bus stops; t transfer,bus(rail) is the transfer time at bus stops. We suppose for both bus and rail modes a number of transfers equal to 1 and a t transfer equal to 20. For bus and rail modes, the waiting time in the mobility scenario is estimated as: t w,bus(rail) = δ / φ bus(rail) where φ bus(rail) is the service frequency. δ, a parameter that ranges between 0.5 and Travel demand models (short and medium-term) Short and medium-term effects are predicted by means of a multi-step behavioural travel demand model, including: a path choice model; a mode choice model; a distribution model; an emission model. The path choice model in the private system (car) allows the path with the minimum travel time to be chosen, for each pair of origin, o, and destination, d. Path choice is simulated through a DC-Logit model proposed in Russo and Vitetta (2003). The path choice model, for the transit system, is specified according to the frequency-based approach, which considers services in terms of sets of runs (lines). In this case, scheduled run times are not considered explicitly, but we refer to line headways, or to their inverse (service frequencies). Therefore we are unable to explicitly calculate attributes for users in relation to each single run, but we can refer only to their average values in relation to lines. This approach allows us to calculate the probability to choose each line (Nuzzolo et al., 2003). The mode choice model is a behavioural model, simulating user choices among car, bus and rail alternatives. For each alternative, systematic utility is specified as: car mode V car,od = β tod,car t od,car bus mode V bus,od =β tod,bus(l od /v bus )+β tw,bust w,bus +β Ntransfer,busN transfer,bus +β busbus where N transfer,bus is the number of transfers for bus mode bus is a constant specific alternative for bus mode rail mode V rail,od =β tod,rail(l od /v rail )+β tw,railt w,rail +β Ntransfer,railN transfer,rail +β railrail Association for European Transport and contributors

7 where N transfer,rail is the number of transfers for rail mode rail is a constant specific alternative for rail mode. We suppose that random residuals are i.i.d. distributed according to a Gumbel of parameter θ m (specified for each model). Hence the probability of choosing mode m, conditional upon travelling between the origin-destination pair, od, p[m/od], is expressed as: p[m/od] = exp (V m /θ m ) / Σ m exp (V m /θ m ) where m is the chosen transport mode; m is the generic transport mode. θ m, logit dispersion parameter. The logsum term related to modal choices and to origin-destination pair, od, LOGSUM M,od, is calculated as: LOGSUM M,od =ln(expv car, od +expv bus, od, +expv rail, od, ) and is introduced in the distribution model. The distribution model is a behavioral model, simulating user choices among a set of destination alternatives, represented by the nine provinces of Sicily. This model is specified for two categories of users: workers and business people. For workers, the systematic utility is specified as: V d =β LOGSUMM,od LOGSUM M,od +β (Emp)tot Emp tot,d + β VO VO d with V d the systematic utility associated to destination d; Emp tot,d the natural logarithm of total employees at destination d; VO d a dummy variable, equal to 1 if origin and destination are the same, 0 otherwise; β LOGSUMM,od, β (Emp)tot, β VO, parameters to be calibrated. For business people, systematic utility is specified as: V d = β LOGSUMM,od LOGSUM M,od + β (Emp)serv Emp serv,d + β VO VO d with V d the systematic utility related to destination d; Emp serv,d the natural logarithm of employees in service sectors at destination d; VO d a dummy variable, equal to 1 if origin and destination are the same, equal to 0 otherwise; β LOGSUMM,od, β (Emp)serv, β VO, parameters to be calibrated. We suppose that random residuals are i.i.d. distributed according to a Gumbel of parameter θ d. Hence the probability of choosing destination, d, conditional upon origin o, p[d/o], is expressed as: p[d/o] = exp (V d /θ d ) / Σ d exp (V d /θ d ) Association for European Transport and contributors

8 with θ d, a logit dispersion parameter. The logsum term related to the distribution model, accessibility Y o, is calculated as: Y o =ln(σ d expv od ) and is introduced in the emission model. The emission model is a behavioral model, simulating the user s choice of making a trip for each province of origin, for two user categories: workers and business people. For workers, w, the systematic utilities are specified as: V x=0/o w =β (Emp)tot Emp tot,o +β NOTRIP V x=1/o w = β Y Y o where V x=0/o w is the systematic utility associated to making no trip (x=0) from origin o; V x=1/o w is the systematic utility associated to making one trip (x=1) from origin o; Emp tot,o is total employees at origin o; β (Emp)tot, β NOTRIP, β Y, parameters to be calibrated. We suppose that random residuals are i.i.d. distributed according to a Gumbel of parameter θ x. Hence the probability of undertaking x trips from origin o for workers w, p w [x/o], is expressed as p w [x/o]= exp (V x/o w /θ x ) / (exp (V x=0/o w /θ x ) + exp (V x=1/o w /θ x )) with x(=0, 1), number of trips from origin o; θ x, logit dispersion parameter. For business people, b, the systematic utilities are specified as (Cascetta, 2001): V x=0/o b =β (Emp)tot Emp tot,o V x=1/o b =β ASA +β Y Y o +β Avr,Inc Avr,Inc + β Hig,Inc Hig,Inc + β Male Male + β Man Man V x 2/o b =β ASA +β Y Y o +β Avr,Inc Avr,Inc + β Hig,Inc Hig,Inc + β Male Male + β Man Man where V x=0/o b is the systematic utility associated to making no trip (x=0) from origin o; V x=1/o b, the systematic utility associated to making one trip (x=1) from origin o; V x 2/o b, the systematic utility associated to making at least two trips (x 2) from origin o; Emp tot,o, total employees at origin o; Avr,Inc, average income (20,000 Euros < Avr,Inc < 40,000 Euros); Hig,Inc, high income (Hig,Inc > 40,000 Euros); Male, 1 if male or 0 otherwise; Man, 1 if manager or 0 otherwise. β (Emp)tot, β ASA, β Y, β Avr,Inc, β Hig,Inc, β Male, β Man, parameters to be calibrated Association for European Transport and contributors

9 We suppose that random residuals are i.i.d. distributed according to a Gumbel of parameter θ x. Hence the probability of undertaking x trips from origin o for business people b, p b [x/o], is expressed as with x (=0, 1, 2), the number of trips from origin o; θ x, a logit dispersion parameter. p b [x/o]= exp (V x/o b /θ x ) / Σ x =0, 1, 2 exp (V x /o b /θ x ) 3.3. Activity location model (long-term impacts) The activity location model allows estimation of probabilities of locating in zone o the activity related to sector s conditional upon its consumption in zone d; p s [o/d]: p s [o/d]= exp (V o/d s /θ o ) / Σ o exp (V o /d s /θ o ) where s is a generic sector (residential, economic); θ o, a logit dispersion parameter; V o/d s, a location disutility, which is estimated as: V o/d s = β 1 LOGSUM m,s od + β 2 X o s + β 3 Zone od LOGSUM m od being the transport disutility (logsum term) related to mode choice of sector s from zone o to zone d; X o s, the production of sector s in zone o; Zone od, a dummy variable equal to 1 if o=d and 0 otherwise; β 1, β 2, β 3, parameters to be calibrated. 4. REGIONAL HIGH-SPEED RAIL: AN APPLICATION FOR SICILY In this section the analysis of effects associated to a regional high-speed railway in Sicily is presented. In section 4.1 results of a survey on current regional mobility is reported. In section 4.2 the proposed system of models is applied to estimate effects generated from interventions. 4.1 Current regional mobility Current regional mobility is studied starting from a survey concerning the socioeconomic system, mobility needs, transport services and infrastructures according to the analysis approach depicted in Figure Socio-economic system and mobility needs The island of Sicily lies south of the Italian mainland. It has about 5 million inhabitants and an area of 25,710 km². Palermo, the regional capital, and Catania are the two most populous cities (the former has 662,046 inhabitants and the latter 306,500), with the highest concentration of socio-economic activities. The two cities lie about 200 kilometres apart, and represent the main centres for two sub-regional Association for European Transport and contributors

10 areas (1,661,044 inhabitants for Palermo and 2,113,395 for Catania), which have quite a different economic structure. Agriculture, high-tech, manufacturing and advanced tertiary activities are mainly located in the sub-regional area of Catania, while regional administrative and tertiary activities are concentrated in the subregional area of Palermo. The low level of service of the current regional railway system, expressed by travel times, frequency and number of transfers, results in insufficient mobility satisfaction levels. According to data concerning the frequency of railway use in Sicily, local and intercity railway services are never used by 90% of Sicilian users, which is higher than the Italian average (see Table 1). Table 1 Frequency of railway use (Source: ISFORT, 2007) Local or regional rail Sicily (%) Italy (%) All days Some days per week Some days per month Never Intercity or Eurostar All days Some days per week Some days per month Never Current inter-city travel demand is served mainly by private modes and by bus services, while rail services play a negligible role, as the above data confirm. Moreover, there is little inter-city passenger mobility in relation to overall regional mobility due to low accessibility. This is more evident for inland areas, which experience a condition of relative isolation Transport services and infrastructures Transport services The survey on the current inter-city rail passenger services operating inside the region reveals the existence of low levels of service (LoS). LoS of the regional railway system, in a working day from 4:00 am to 11:00 pm (time period), is expressed in terms of estimated average inter-city travel times, frequencies and number of transfers in three different time periods (corresponding to three different services): all railway runs in the entire time period are considered (from 4:00 am to 11:00 pm) (total services); railway runs in the time period that allow a round-trip connection between the two cities within the same day (round-trip services); railway runs in the time period that allow a round-trip connection between the two cities, with arrival time at destination before am (work-based round-trip services). Analysis was carried out for all cities of the region and focused on the origindestination pair, Catania and Palermo. Data related to the regional railway services Association for European Transport and contributors

11 were taken from the timetable available on the web site of Italian railway company Ferrovie dello Stato (2009). Table 2 reports the results of the analysis in terms of average travel time and frequency, which is calculated as the number of runs provided in the time period considered, related to the regional railway services. od pairs Table 2 Average levels of service. Current scenario Average travel time (h) Total services Runs in the time period a Round-trip services Runs in the time period a Work-based round-trip services Runs in the time period Catania Palermo Palermo Catania Regional connections From Table 2, it emerges that frequencies decrease from total services to workbased round-trip services. This reduction characterizes all inter-city connections inside the region. For instance, for the Catania-Palermo od pair we have: total services with an average travel time of 5.4 hours (300 minutes) and a frequency of 12 runs in the time period considered; round-trip services with the same average travel time and an average daily frequency of 2 runs; work based round-trip services are not present. The above data confirm that current LoS of railway system is not sufficient to satisfy regional mobility needs. Transport infrastructures The rail network in Sicily is about 1,400 km long, which amounts to 8.3% of the Italian rail network. Current infrastructures are lacking: the length of double tracks is lower than the national average (7.9%) (Table 3). Table 3 Sicilian railway infrastructures Single track (km) Double track (km) Total (km) Sicily 1, , North Italy 3, , , Central Italy 1, , , South Italy 4, , , Italy 9, , , Source: Regional Transport Plan (Sicilian Region, 2004) In European and National transport planning, interventions to improve regional railway infrastructures have been programmed. These interventions consist in doubling current tracks and in improving technology such as signalling and communication. The Trans European Network Priority Project to improve the Berlin- Verona-Milano-Bologna-Napoli-Messina-Palermo railway axis concerns Sicily. Association for European Transport and contributors

12 4.2 The planning process and regional mobility scenario The critical elements of the current mobility model have made it necessary to define a new regional mobility model, which has as its main component a high-speed railway with direct inter-city passenger services. The high-speed railway could become completely operative after the purchase of new rolling stock, the design of a new configuration of rail services and the realization of new rail facilities. All these phases may be reasonably performed in a strategic scenario, ensuring an appreciable reduction in inter-city travel times. However, the study envisages a step-wise approach to developing the high-speed railway; an operative scenario is defined by changing some railway service schedules; a tactical scenario is defined where some phases will be carried out (purchase of new rolling stock, design of a new configuration of rail services), resulting in a partial reduction in travel times. The step-wise approach is envisaged to allow expected positive impacts to materialise, even if partially, as soon as possible, and to prevent massive investments translating into benefits for users and the community only after many years. The time phases of interventions to improve the rail system are adopted in accordance with the planning timescale: at the operative scale, interventions concern a change in service scheduling; this intervention affects the path choice component of mobility; at the tactical scale, interventions concern a change in service scheduling and frequency based on purchase of new rolling stock; such interventions affect the distribution, mode and path choice component of mobility; at the strategic scale, interventions concern a change in service scheduling and frequency based on purchase of new rolling stock and realisation of new infrastructures; these interventions affect on emission, distribution, mode and path choice components of mobility and socio-economic characteristics (population and employment). Figure 3 depicts the planned interventions and mutual connections over the three time scales: operative, tactical and strategic. In the following sections further details on interventions at each time scale are provided Operative scale (short-term effects) At the operative scale, the scenario for interventions is as follows: reorganisation of current railway services between Catania and Palermo; current railway services ensure a connection between the two cities in an average time of 300 minutes; after reorganization of rail schedules and stops, the two cities will be 200 minutes apart, with a 33% reduction in travel time (Table 4); railway infrastructures and rolling stock are assumed to be the same as those currently available. Table 4 - Average railway travel time at operative scale Current (minutes) Scenario (minutes) Reduction (%) Palermo Catania % Association for European Transport and contributors

13 Mobility needs satisfaction Service planning (Managerial and normative) Infrastructure planning (Non-material and material) Operative scale P M D E SE Tactical scale P M D E SE Strategic scale P M D E SE Legend P: Path; M: Mode; D: Distribution; E: Emission; SE: Socio-economic changeable component non-changeable component Railway schedule Railway rolling stock Railway infrastructures Figure 3 Planned interventions and relative effects An improvement in the level of railway services is obtained, in terms of travel times, frequency and number of runs. On analyzing the effects on user choices and considering the two user categories (workers and business people), a 2% percentage increase in using rail services for workers and 10 % for business people is obtained. The predicted average travel time on the Palermo-Catania od pair will be 200 minutes, with a reduction in the number of stops from origin to destination of 5 and an elimination of transfers Tactical scale (medium-term effects) At the tactical scale, the scenario for interventions is as follows: reorganization of existing rail services at the regional scale to include two primary lines connecting the three main cities of the region (Catania, Palermo and Messina) and three secondary lines according to the new rail services configuration (Figure 4); acquisition of new rolling stock: for primary lines, specific rolling stock for high-speed rail services (e.g. Talgo); for secondary lines, standard rolling stock for regional rail services (e.g. Minuetto). rail infrastructures are assumed to be the same as in the current situation; this Association for European Transport and contributors

14 scenario entails an improvement in the other regional railway lines after some on going interventions. TALGO Line: (Trapani) Palermo Catania Messina TALGO Line: Palermo Catania Siracusa (Ragusa) MINUETTO Line: Palermo Agrigento MINUETTO Line: Agrigento Caltanissetta Catania MINUETTO Line: Siracusa Messina Figure 4 System of railway services (tactical and strategic scenarios) At the tactical scale, a general improvement in the level of rail service is obtained, in terms of travel times, frequency and number of transfers. On analyzing the effects on user choices and considering the two user categories, a 4.8% percentage increase in using rail services for workers and 24 % for business people is obtained. Specifically, considering the new Palermo-Catania route we obtain a 50% travel time reduction from the current 300 minutes to 150 minutes (Table 5). Table 5 - Average railway travel time reduction at tactical scale Current (minutes) Scenario (minutes) Reduction (%) Palermo Catania % Strategic scale (long-term) At the strategic scale, the scenario for interventions is as follows: improvement in railway services at the regional scale designed at the tactical scale with an increase in frequency and a further reduction in travel times; about 30% increase in rolling stock designed at the tactical scale; improvement in rail infrastructures between Catania and Palermo in terms of track doubling in some sections and implementing new technologies; this Association for European Transport and contributors

15 scenario means an improvement in the other regional railway lines. A significant improvement in the level of railway services is obtained: for the whole region, the number of runs in the reference period increases (+ 268 runs) and total travel time on the network, calculated as a sum of travel times from each origin to each destination, decreases (-179 h). In terms of user choices, we considered two user categories. For workers, we obtained a 6.0 % increase in rail use; for business people, a 30.0 % increase was obtained. Specifically, on the new Palermo-Catania route we obtained a 66.6% travel time reduction from the current 300 minutes to 100 minutes (Table 6). This produces an increase in rail percentage use of about 9% for the first user category (workers), and about 40 % for the second one (business people). Table 6 - Railway travel time at strategic scale Current (minutes) Scenario (minutes) Reduction (%) Palermo Catania % Table 7 reports an LoS estimate of the regional rail system defined at the strategic scale in terms of average travel time and frequency. Characteristics concern workbased round-trip services. From comparison between table 2 and table 7, several improvements in rail services are evident: average travel time improvement for all regional connections (from hours to hours, amounting to a reduction of 48%); the travel time for the Catania- Palermo od pair decreases by about 67%; frequency of work-based round-trip services improves for all regional connections (from 110 runs to 378 runs in the time period, presenting an increase of 240 %); run frequency for the Catania-Palermo od pair increases by about 700%. Table 7 - Average levels of service. Strategic scenario od pairs Average travel time (h) Reduction vs. current scenario (%) Frequency (runs/ time period) Work-based round-trip services Increase vs. current scenario (%) Catania Palermo % % Palermo Catania % % Regional connections % % As regards the (re-)distribution of socio-economic activities generated by the new supply configuration of the regional public transport system, the following considerations may be made. The high-speed railway project is designed to lead to a general increase in the level of service with a consequent increase in accessibility for inter-city connections. This, in turn, would cause a (re-)distribution of population and employment among the different provinces of Sicily. Specifically, a population increase is predicted in the provinces of Agrigento, Caltanissetta and Enna (+3.1%, Association for European Transport and contributors

16 +1.0% and +7.1%, respectively), which are currently relatively isolated from the rest of the region. Similar patterns are forecast for employment location. This means that, due to increasing accessibility, the two main socio-economic attractors of the region, Palermo and Catania, would extend their area of influence to the above three provinces which are poorly served by transit services. 5. FINAL CONSIDERATIONS In this paper an approach to estimate effects associated to progressive interventions to implement a high-speed railway system at regional level was presented. The effects concern passenger mobility and the socio-economic system. The proposed approach is based on simulation models to estimate specific components of mobility and the location of residential and economic activities, which could be influenced by the implementation of progressive interventions. The defined approach and the proposed system of models were applied to Sicily. Future advances of the study presented herein will concern the analysis of effects on other mobility segments, namely national and international mobility, freight mobility and related final segments, mobility for tourism and other services, and integration with urban mobility and relative transit services. In the case of Sicily, the above components are of importance, given the presence of the international airport at Catania, the region s historical and cultural resources and the current low levels of service in urban transit systems in the major cities. REFERENCES Ben-Akiva M., Lerman S. R. (1984). Discrete choice analysis. Theory and application to travel demand, MIT Press, Cambridge, USA. Bonnafous A (1987) The regional impact of the TGV. Transportation 14: Cascetta E. (2001) Transport systems engineering: theory and methods, Kluwer. Cascetta E., Papola A., Pagliara F., Marzano V. (2008). Analysis of the mobility and location impacts of the HS rail link between Roma and Napoli. Proceedings of the European Transport Conference. 6-8 October Noordwijkerhout (Netherlands). Association of European Transport. Coto-Millán P, Banos J, Inglada V (1997) Marshallian demands of intercity passenger transport in Spain: An economic analysis, Transportation Research E, 33, Domencich T., McFadden D.L. (1975) Urban Travel Demand: A Behavioural Analysis. North-Holland Publishing Co. Reprinted Ferrovie dello Stato (2009), (March, 2009) Froidh O. (2005). Market effects of regional high-speed trains on the Svealand line. Journal of Transport Geography Hensher D. (1997), A practical approach identifying the market potential for highspeed rail: a case study in the Sidney-Canberra corridor. Transportation Research Part A 31, Inglada V, Coto-Millán P (2002) Introduction of an innovative product: the high speed rail. In Essays on microeconomics and industrial organization. Coto- Millán (ed), Springer, Physica, Heidelberg, ISFORT (2007), Statistiche regionali sulla mobilità. Association for European Transport and contributors

17 Italian Transport Ministry (2007). General Transport Mobility Plan. Guidelines. Koike A., Ueda T. and Miyashita M. (2000), Spatial Computable General Equilibrium Model for passenger transport improvement. Evaluation of Japanese New Shinkansen Project. Presented at World Congress of Regional Science Association International, Lugano. López-Pita A., Teixeira P.F., Casas-Esplugas C., Bachiller Saña A. (2006). Practical experience on the commercial impact of high speed rail services on the competing modes in Europe: In Proceedings of 85th Transportation Research Board, Nuzzolo A., Russo F. (1997), Modelli per l'analisi e la simulazione dei sistemi di trasporto collettivo. Collana Trasporti, FrancoAngeli, Milan. Nuzzolo A., Russo F., Crisalli U. (2003), Schedule-based dynamic assignment models for public transport networks. Collana Trasporti, FrancoAngeli, Milan. Oosterhaven, J. and Elhorst, J. P. (2003) Modelling Interactions between the Economy, the Environment and Transportation at the Local and Regional Level, with an Application to Dutch Maglev Projects. Paper presented at the TRIP research conference on the Economic and Environmental Consequences of Regulating Traffic, Copenhagen. Pownall C., Davies G., Jowsey D., Vickers J. (2008). Making the most of Kent s new High Speed rail service. Proceedings of the European Transport Conference. 6-8 October Noordwijkerhout (Netherlands). Association of European Transport. Russo F., (2005) Sistemi di trasporto merci: approcci quantitativi per il supporto alle decisioni di pianificazione strategica tattica ed operativa a scala nazionale, FrancoAngeli, Milan (Italy). Russo F., Chilà G. (2008) Sequential models for the mobility decisions: experimentation for vehicle holding choices Proceedings of the European Transport Conference. 6-8 October Noordwijkerhout (Netherlands). Association of European Transport. Russo F., Musolino G. (2008). Long-term impacts of urban land use and transport policies: simulation and assessment. Proceedings of the European Transport Conference. 6-8 October Noordwijkerhout (Netherlands). Association of European Transport. Russo F., Rindone C. (2007), Dalla pianificazione alla progettazione dei sistemi di trasporto: processi e prodotti, FrancoAngeli, Milan, Italy Russo F., Rindone C., Cartisano A.G. (2002). A methodology for supply simulation in transit systems: application to an Italian extra-urban area. Proceedings of the European Transport Conference 9-11 September Cambridge (UK). Russo F., Vitetta A. (2003). An assignment model with modified Logit, which obviates enumeration and overlapping problems. Transportation, vol. 30, pp Sicily Region (2004). Regional Transport Plan. turismo/trasporti/ Torchin F., Grilly D., Combes S., Hasiak S., Menerault P. (2008). High speed rail for regional transport: case studies in European countries. Proceedings of the European Transport Conference. 6-8 October Noordwijkerhout (Netherlands). Association of European Transport. Association for European Transport and contributors

18 Ueda T. Nakamura H. (1989) The Impacts of the Shinkansen on Regional Development. Proceedings of the 5th World Conference on Transport Research, Yokohama. FHA (Federal Highway Administration) and FTA (Federal Transit Administration) (2007), The Transportation Planning Process Key Issues, Publication of the Transportation Planning Capacity Building Program, bbook.htm Yao E., Morikawa T. (2005). A study of an integrated intercity travel demand model. Transportation Research Part A 39, Association for European Transport and contributors