XXII SIDT National Scientific SeminarBari, 14-15 settembre 2017Technologies and Methods in Railway Transport

Innovative o-d based rail freight subsidies compensating infrastructural gaps: methodological issues and practical

implementation in Italy

Daniela Tocchi, Vittorio Marzano, Andrea PapolaDepartment of Civil, Architectural

and Environmental Engineering, University of Naples Federico II

Dario AponteRAM - Rete Autostrade Mediterranee

Fulvio SimonelliUniversity of Sannio, Department of Engineering

Motivation and background

• rail freight transport largely acknowledged as potentially cost-effective and environmentally sustainable

• many EU policies and funds to support rail freight and improve performance of EU freight railway network

• Italy:

– up to 2014: dramatic decreasing trend (-50% w.r.t. 2007 traffic)

– since 2015: an integrated set of policies to relaunch rail freight, based on three pillars:

• infrastructure improvements

• regulation/simplification

• incentives

1

Incentive-based policies in Italy

• earlier incentives (2005-2007): L 166/02

• ferrobonus (2010 – to date): to shippers and MTOs

– compensation of 1.08 €/train∙km for new services

– positive impact: +17% increase in rail freight traffic in 2012 w.r.t. 2009

– re-newed by the Italian Government for 2017-2021, up to 2.5 €/train∙km

• sconto pedaggio (2015 – to date): to railway undertakings

– discount of the access charge to the rail infrastructure manager

– based on former state aids to the ex incumbent operator Trenitalia Cargo

– watering-can principle, irrespective of network performances

– up to 2.5 €/train∙km for train services on the entire Italian rail network

– additional incentive to/from South (larger market share of Trenitalia Cargo)

2

An equitable sconto pedaggio

• research question: watering-can distribution not leading to equitable market conditions for railway undertakings

– performance of the Italian freight rail network very heterogeneous amongst o-d pairs

– railway undertakings receive the same incentive irrespective of the infrastructural gap with respect to EU standard

• 750 metres, 2000 tons, PC80 gauge

• proposition of an equitable sconto pedaggio:

– an o-d pair basis incentive

– proportional to the infrastructural gap on the o-d pair with respect to the performance of the EU-standard freight train

3

An equitable sconto pedaggio: definition

INFRASTRUCTURAL CHARACTERISTICS

permissible train weight (wtk)

maximum train length (ltk)

loading gauge (gtk)

slope (stk)

current scenario

cwunittk= ctot

tk/captk

EU standard scenariocwunti,opt

tk = ctot,opttk / capopt

tk cwunittk

• ctottk total cost to operate the train t on the path k

• captk train payload capacity

• performance of a freight train of type t (e.g. intermodal) on path k

OPERATIONAL CHARACTERISTICS

number of locomotives nloc

locomotive weight wtloc

locomotive length ltloc

freight railcar total weight wtcar

unladen weight wutcar

freight railcar length ltcar

unit weight cost

4

Infrastructural gap and proposed incentive

• proposed unit incentive per o-d pair:

inckmtod = min{ ∙cdunit,gap

tod , ∙km}

EU regulation on cap for incentives

• weight cost units (€/ton):

– cwunit,gaptod = minkKod{cwunit

tk}– minkKod{cwunit,opttk}

• distance units (€/train·km)

– cdunit,gaptod = cwunit,gap

tod ∙ cap*tk/tdod

• tdod , travel distance between o and d

• cap*tk ,capacity of path k* minimizing the cwunit

tk cost

public budget constraint

5

Calculation of train capacity

Calculation of corresponding:

• maximum number of freight railcar

• candidate train weight

Hypotesize max length ltk = lk

Consistency with weight upper bounds :

• maximum permissible weight per axle

• slope and power traction (# locomotives )

Yes length is the limit

Calculate payload capacity

No weight is the limit

Consistent with maximum permissible

weight, calculation of:

• corresponding number of railcars

• maximum train length

Necessary condition for train t to operate on k: gk gtmin

6

Calculation of train costs

• cost of train driver(s) cdriv = ndriv∙ttk∙ch

driv

– number of drivers ndriv

– chdriv hourly cost rate

• cost of locomotives cloc= nloc∙ttk∙ch

loc

– chloc hourly cost of locomotive

• cost of rolling stock ccar= ncars(ltk)∙ttk∙ch

car(gk)

– ncars(ltk) number of railcars allowed by train length ltk

– chcar(gk) hourly cost of rolling stock

• energy consumption and toll payment cnetw =km(wtk)∙tdk

– tdk = vt∙ttk travel distance between o and d along k

• other fixed costs (shunting costs, fixed administrative costs, etc.) cfix

ctottk = [ndriv∙c

hdriv + nloc∙c

hloc + ncars(ltk) ∙ch

car(gk) +km(wtk)∙vt]∙ttk + cfix

7

Quantification of the incentive

• the proposed incentive requires calculation of shortest unit path costs in the current and optimal scenarios

• a non-additive shortest path problem:

– total cost ctottk and capacity captk based on performance of worst link for

each of the relevant infrastructural characteristics (path-based costs)

• possible approaches:

– brute force: enumerating all paths for each o-d pair and then calculating the corresponding train capacity and costs, practically infeasible also for small-size networks

– more efficient solution algorithms …

• key aspect: homogeneous infrastructural characteristics across links of the network imply homogeneous train performances irrespective of the specific path k …

• … thus additive shortest path algorithms can be applied8

Shortest path calculation

Rationale:

1. discretize relevant infrastructural characteristics according to a limited number of thresholds:

– L set of nl train length thresholds (as example nl=5 thresholds L≡{750 m, 600 m, 500 m, 400 m, 300 m})

– G set of ng loading gauge thresholds

– S set of ns slope thresholds

– W set of nw permissible weight thresholds

2. define a set containing all n=ng∙nl∙ns∙nw combinations of thresholds

– the generic combination i defines an appropriate bound for infrastructural characteristics

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Quantification of the incentive

3. identify subset AiA of links of the network with at least the characteristics defined by i

4. hypotesize homogeneous characteristics defined by i for all links in Ai

5. calculate the lowest unit cost paths on Ai via standard additive shortest path algorithms

• iterating across yields the global shortest unit path cost with the corresponding best infrastructural performances

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Algorithm

• ꓯ # locomotives (nloc)

• Step 1 – calculation of shortest paths and unit costs in the current scenario

• Step 2 – calculation of the optimal cost and of the infrastructural gap

• Repeat Step #1 for the EU standard combination of infrastructural characteristics

• Step 3 – quantification of the incentive

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Case study: Italy (baseline 2015)

PIC WEB

PIC WEB

SUPPLY MODEL

(TransCad)

TRAIN O-Ds

12

Case study: Italy (baseline 2015)

operational costs

• cost of train driver(s): ndriv=2 (according to the Italian regulations); chdriv=25 €/h (gross yearly salary of

55.000 €; 2200 working hours/year)

• cost of locomotives: chloc=22.83 €/h

• cost of rolling stock: chcar=0.36 €/h for a standard railcar; ch

car=0.43 €/h for a low-loader railcar

• energy consumption and toll payment:km=3.26 €/train∙km (toll accounts for 2.82 €/train∙km);km is

assumed independent of the train weight

• fixed costs: 2200 €/trip for shunting in origin and destination; 200 €/trip for administrative costs

160 combinations of infrastructural

characteristics

• length: nl=5, set L≡{700 m, 600 m, 500 m, 400 m,

300 m}

• loading gauge: ng=4, set G≡{PC80, PC45, PC22,

PC00}

• slope: ns=4, set S≡{10‰, 15‰, 21‰, 50‰}

• weight: nw=2, set W≡{8.0 tons/m, 2.0 tons/m}

intermodal train characteristics

• locomotive:

• mass wtloc=106 tons

• length llloc=18 m

• freight railcar:

• total weight wcar=50 tons

• unladen weight wutcar =17.5 tons

• length lcar=20 m

13

Case study: implementation in Italy

• 90% of o-d pairs: infrastructural gap lower than 0.20 €/TEU∙km• only apparently low: ~ 200 €/TEU for a 1000 km o-d pair

14

Case study: implementation in Italy

smart incentive

mean st. dev. M€/year

0-49 12% 0.14 0.23 23.28

50-99 5% 0.10 0.08 10.18

100-199 12% 0.14 0.27 23.29

200-499 12% 0.13 0.20 18.16

500 and more 58% 0.10 0.05 48.58

total 100% 0.14 0.22 123.49

infrastructural gap [€/TEU km]# trains/year

per o-d pair

# trains/year

% distribution

• o-d pairs clustered by # trains/year

cost of the “intermodal divide” of railway transport

in Italy with respect to the ideal standards of the EU

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Conclusions and research prospects

• an o-d equitable incentive to railway undertakings:

– operational

– dynamic: adjustable on a yearly basis to account for ongoing network improvements

• main challenge: non-additive costs → ad hoc procedure to calculate shortest paths

• research prospects:

– embedding demand-side effects: modal split effect and generated demand effect

– as objective function to maximize the modal shift

16

XXII SIDT National Scientific SeminarBari, 14-15 settembre 2017Technologies and Methods in Railway Transport

Thanks for your attention

Calculation of train capacity

• maximum number of freight railcar

• candidate train weight

–

• consistency with weight upper bounds:

– wtk wk∙ltk

– wtk wtk(nloc, sk)=t(sk) ∙ (nloc)

• (Yes) w*tk min{wk∙ltk , t(sk)∙(nloc)}

• (No) wtk = min{wk∙ltk , t(sk)∙(nloc)}

• number of railcars

• maximum train length

• train payload capacity

– Captk=wtk -ncars wucar -nloc wloc

tcar

tloclockcars

l

lnln int

w*tk = nloc∙wtloc +ncars∙wtcar = nloc∙wtloc +

tcar

tloclock

l

lnlint ∙wtcar

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