Method for an economical assessment of urban transport systems

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Transportation Research Procedia 37 (2019) 282–289 www.elsevier.com/locate/procedia st 21st EUROWorking Working Group Transportation Meeting, EWGT 2018, September2018, 2018, 21 EURO Group onon Transportation Meeting, EWGT 2018, 17th 17-19 – 19th September 21st EURO Working Group on Transportation Meeting, EWGT 2018, 17-19 September 2018, Braunschweig, Germany Braunschweig, Germany Braunschweig, Germany

Method for an economical assessment of urban transport systems Method for an economical assessment of urban transport systems Assadollah Saighaniaa*, Carsten Sommeraa Assadollah Saighani *, Carsten Sommer

Chair of Transportation Planning and Traffic Systems, University of Kassel, Mönchebergstraße 7, 34125 Kassel, Germany Chair of Transportation Planning and Traffic Systems, University of Kassel, Mönchebergstraße 7, 34125 Kassel, Germany

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Abstract Abstract This paper presents an intermodal method for identifying municipal expenses and revenues in the transport sector and allocates This an intermodal method for identifying municipal expenses and revenues in the transport sector and allocates them paper to the presents urban transport systems: pedestrian, bicycle, car, truck traffic and local public transport. The method is based on full them to the urbanintransport systems: pedestrian, bicycle, truck traffic and local publicsystems transport. Theon method is based on full cost accounting, that the total transport-related costs arecar, allocated to the urban transport based a top-down-approach. cost accounting, in that on thethe total transport-related costs arekeys allocated to the urban transport basedengineering on a top-down-approach. The method is centred development of allocation and attribution factors basedsystems on scientific findings. For The methodeconomic is centredcomparison, on the development of allocation keys and on important scientific engineering findings. For a complete various assessment methods areattribution presented,factors taking based the most transport-related external a complete economic comparison, assessment methodschange are presented, taking theand most important external effects into account (accident costs,various air pollution costs, climate costs, noise costs health benefitstransport-related in walking and cycling). effects into account costs, air pollution costs, climate change costs, noise costs and health in walking and cycling). The external effects(accident have been based on existing national and international methods, which arebenefits monetised with corresponding The external effects have been on existing national and international which are monetised with corresponding (accepted) cost factors from the based appropriate scientific literature. The method methods, allows cost transparency and determines economic (accepted) costcan factors appropriate scientific literature. The method allows costoftransparency determines indicators that servefrom as a the basis for discussion and decision-making in the allocation funds for theand different urbaneconomic transport indicators that canthat, serve as a be basis fordirectly discussion andout decision-making allocation of funds fortransportation the different urban transport systems. Besides it can used to seek goal indicatorsininthe urban development and planning. With systems. Besides that, ithere, can be directly seek out goal will indicators and transportation planning. With the approach presented forused the first timetomunicipalities be ableintourban havedevelopment a complete overview of their transport-related the approach presented here, foreffects, the firstdifferentiated time municipalities be transport able to have a complete overview their transport-related revenues, expenses and external each bywill urban system. This results in an of additional and important revenues, and transportation external effects, differentiated eachstep by urban system. results in ansector’. additional and important instrumentexpenses for strategic planning and a next on thetransport road to ‘true costsThis in the transport instrument for strategic transportation planning and a next step on the road to ‘true costs in the transport sector’. © 2019 The Authors. Published by Elsevier Ltd. © 2018 The Authors. by Elsevier B.V. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The under Authors. Published by Elsevier B.V. Peer-review responsibility of the scientific of the 21stofEURO Group on Transportation Meeting. st Selection and peer-review under responsibility of thecommittee scientific committee the 21Working EURO Working Group on Transportation Meeting, Peer-review the scientific committee of the 21st EURO Working Group on Transportation Meeting. EWGT 2018,under 17th –responsibility 19th Septemberof2018, Braunschweig, Germany. Keywords: Cost Transparency in Transport Sector; Cost Allocation Method; Economy of Urban Transport Keywords: Cost Transparency in Transport Sector; Cost Allocation Method; Economy of Urban Transport

1. Introduction 1. Introduction Passenger transport and goods traffic are an important basis for social participation and the prosperity of the PassengerThe transport andbenefits goods for traffic are an important basis social participation and theOnprosperity the population. resulting individuals and society are for considerable and undisputed. the other of hand, population. The resulting benefits for individuals and society are considerable and undisputed. On the other hand, urban transport results in costs, both for the planning, construction, maintenance, administration and operation of urban transport infrastructure results in costs, thepublic planning, construction, administration operation urban transport andboth for for local transport services. maintenance, The amount of expenses andand revenues thatofa urban transport infrastructure and for local public transport services. The amount of expenses and revenues that a * Corresponding author. Tel.: +49 561 804 3279 * Corresponding Tel.: +49 561 804 3279 E-mail address:author. [email protected] E-mail address: [email protected] 2352-1465 © 2018 The Authors. Published by Elsevier B.V. 2352-1465 2018responsibility The Authors. of Published by Elsevier B.V.of the 21st EURO Working Group on Transportation Meeting. Peer-review©under the scientific committee Peer-review under responsibility of the scientific committee of the 21st EURO Working Group on Transportation Meeting. 2352-1465  2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the 21st EURO Working Group on Transportation Meeting, EWGT 2018, 17th – 19th September 2018, Braunschweig, Germany. 10.1016/j.trpro.2018.12.194

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municipality incurs for urban transport are also unknown as well as its allocation to the various transport systems. Many municipal resources are used jointly by several transport systems. For this reason, the share of car traffic, for example, in the costs of road constructions or winter road maintenance is not directly identifiable. Furthermore, the transport-relevant positions are allocated to multiple accounting documents in a municipality or in the city budget to several sub households. In times of decreasing financial resources in public budgets, the costs of urban transport systems and their relationship to each other play an important role. A first step towards more transparency in public budgets was made possible with the introduction of municipal ‘double-entry’ bookkeeping in Germany. For the first time, this resulted in a uniform accounting system for the city administration and the municipally owned companies. In addition, motorised traffic has negative effects on humans and the environment in the form of accidents, air pollution, noise pollution and greenhouse gases. These negative external effects are defined in the economy as external costs (Aberle, 2009). 2. Literature overview and aim of the study For half a century now, transport policy has been discussing the extent to which modes of transport should pay for the costs they cause. Since 1969, the infrastructure costs (costs for the construction, maintenance and operation of transport infrastructure) and their allocation to specific vehicle groups have been calculated at regular intervals for German federal highways on the basis of the report by (BMV 1969). The Council of the European Community prescribed the framework conditions and requirements for the calculation of infrastructure costs in the member states for the first time in 1970 (EC Directive 1108/70, 1970). With the introduction of the (EU Directive 1999/62/EG) a truck toll (based on scientific studies) has been applied in German federal highways since 2005 (Rommerskirchen et al., 2002; Rommerskirchen et al., 2007; Korn et al., 2014). In other European countries, in the USA (FHWA, 2006) and in Australia (NTC Australia, 2005), infrastructure costs are also calculated at regular intervals (see, e.g. Switzerland (BFS, 2003) and Austria (Herry and Sedlacek, 2003; Prognos and ZIV, 2018). As in Germany, the national calculations of infrastructure costs are essentially based on fully allocated cost studies and have an official character. The aim of fully allocated cost studies is to achieve recovery of total costs. The most common approach used in these studies is a top-down-approach where the total costs are split up into different categories which are allocated to vehicle types by using different allocation factors. As a result of the introduction of the (EU Directive 2011/76/EU, 2011 Annex IIIa), users (vehicles) can also be charged for traffic-related external costs caused by air pollution and noise pollution. For the first time, the European research project (UNITE, 2003) developed a comprehensive methodological concept covering the costs of transport infrastructure and operation, as well as environmental, climate, accident and congestion costs for all modes of transport and all EU states. For years, discussions have been going on in Germany about the costs of transport (for all modes of transport) and its financing via the state levels and the payments made by users (taxes, fees). These discussions more often demand a higher financing of the infrastructure by its users (‘user financing’). In Switzerland, official statistics on the costs and financing of transport are regularly methodologically further developed and published at regular intervals (BFS, 2015). An international comparison shows that the ‘Swiss statistics’ are most detailed in terms of covering all relevant cost categories (transport infrastructure, accident costs, environmental and health costs), integrating relevant modes of transport (road, rail, public transport, air transport) and reporting on the administrative levels (federal, cantonal, municipal). In Germany, a research project titled ‘Economic Comparison of Transport Modes’ was carried out on behalf of the German Environment Agency (Link et al., 2017; Bruns et al., 2018). For this purpose, a comprehensive analysis of the financial flows for the various modes of transport (revenues and expenses of the public sector and public transport companies) was first prepared in (Link et al., 2017). Building on this, in (Bruns, et al. 2018) an attempt was made to allocate transport-related revenues and expenses to the various means of transport. So far, environmental, climate, accident and congestion costs have not been considered in the study. For urban transport (municipality) literature contains only a few assessments, but these differ greatly in terms of methodology and definitions. (Dobeschinsky and Tritschler, 2006) analysed the transport-related municipal costs of the city of Stuttgart. Positions that could not be fully allocated to a specific transport system, were estimated by experts based on percentage shares. The ICLEI-Study is also based on percentage shares by expert estimates, whereby only passenger car traffic is considered (ICLEI, 2001). The Least Cost Transportation Planning Method (LCTP) examines the economic and ecological effects of different transport systems on the basis of a system cost assessment (Bracher

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et al., 2002). The LCTP considers the transport system as a virtual ‘company’ providing a ‘mobility service’. The ‘mobility service’ described in the study is provided by various actors, resulting in a combination of user costs (e.g. fuel costs, vehicle maintenance costs) and municipal costs. As outlined in the literature overview, there is currently no intermodal and standardised method which allows an economic comparison of urban transport systems in a municipality. Therefore, the aim of the study is to develop and apply a consistent method that allows an economic comparison of urban transport systems in a municipality and gives indicators for a sustainable financial viability of urban transport. This results in an additional and important instrument for strategic transportation planning and a next step on the road to ‘true costs in the transport sector’. 3. Methodology 3.1. Method for a business economic comparison In the newly developed allocation method, municipal expenses and revenues in the transport sector are recorded and then allocated to the different urban transport systems, truck (vehicles > 3.5 tons), car (vehicles ≤ 3.5 tons), bicycle, pedestrian traffic and local public transport, on the basis of the polluter-pays-principle (Saighani et al., 2017). The method is based on full cost accounting, in that the total transport-related costs are allocated to the urban transport systems (top-down-approach). All expenses and revenues resulting from the planning, construction, operation, administration and maintenance of transport systems in a municipality and its own companies (including the corresponding transport companies) are taken into account. Expenses and revenues include not only the consumers’ participation but also the investment position. For example, the devaluation of transport infrastructure is accounted by means of household recorded depreciation costs over the entire life usage. Essential for a business economic comparison is an inventory of the complete transport infrastructure attributed to the responsibility of each municipality (inter alia road and light rail system networks). Excluded are federal highways, private roads and roads outside the administrative boundaries of the city. Public grants and subsidies from the state, the federal authorities and the European Union are deliberately ignored in order to allow a transparent and unadulterated comparison of urban transport systems in a municipality. The process flow of the business economic allocation method is illustrated in Fig. 1. In the following the different steps of the method will be described step by step.

Fig. 1: Process flow of the business economic allocation method

Analysis of the budget- and accounting documents (step 1): First of all, all expense and revenue positions are identified from the relevant accounting documents and compiled as an input variable of the method. For this purpose, an in-depth analysis of all expenses and revenues caused by urban transport is required. Essentially, the expenses and revenues of municipal transport companies can be taken directly from the annual reports. In many cases, these totals must be subtracted from amounts that are not directly related to urban transport. Usually the accounting documents

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are published as an overview, so details can only be clarified in direct cooperation with the municipal transport companies. It should also be noted that internal cash flows within the administration have to excluded from the results. For example, this applies to street cleaning costs, if they are paid from the municipal budget to a municipal owned company. In this case, the position is booked three times. In fact, this service is only done once by the municipality itself and therefore causes a one-off expense. If these internal cash flows are not subtracted, then the result is an incorrect cost coverage ratio. State and federal subsidies are not considered or are subtracted, because these subsidies could distort the result of the distribution between the different transport systems if measures for a transport system are funded more frequently or to a higher degree. Attribution of the allocation key for each position (Step 2): In the second step, one of the defined allocation keys is attributed to each of these positions. A basic distinction is made between individual and joint positions. Individual positions can be fully allocated to a transport system because the transport systems are the causers. Joint positions are characterised by the fact that they have to be allocated to several transport systems, because they are caused by more than one transport system (e.g., street cleaning, winter road maintenance, road drainage). For this purpose, the third step develops allocation keys and applies them to the joint positions (step 4). Fig. 2 illustrates the monetary meaning of the individual and joint positions for transport-related revenues and expenses in the city of Kassel. The comparison of transport-related revenues and expenses shows that the expenses for urban transport of approx. EUR 126 million cannot be covered by their revenues of approx. EUR 56 million. The split between individual and joint positions shows that with a share of approx. 45% (EUR 56.6 million) joint expenses have a much higher financial significance than joint revenues of approx. 14% (EUR 7.6 million). In order to allocate these joint revenues and joint expenses to the various transport systems, allocation keys have been developed, based on the polluter-paysprinciple (see step 3 and step 4).

Fig. 2: Shares of individual and joint positions (revenues and expenses) in the city of Kassel, averaged 2009 to 2011

Development of allocation keys (step 3) and allocation of revenues and expenses (step 4): There are different methods for allocating infrastructure costs in the literature (see, e.g. Link et al., 1999; Link et al., 2008). These are also applied in different hybrid forms: (a) differentiation between fixed and variable costs, (b) polluter-pays-principle, (c) initiation-principle, (d) incremental-cost-approach and (e) differentiation between weight-dependent and nonweight-dependent costs. The developed allocation keys in this paper reflect the share a transport system has in the budgetary positions of a specific thematically defined field of application. Using these allocation keys, the monetary values recorded as a joint position can be allocated to the urban transport systems according to their originator. The correct selection of the allocation key depends on which allocation key corresponds to the relevant position according to the polluter-pays principle. The methodological approaches for determining the allocation keys are described below for the purposes of comprehensibility and transparency. Further descriptions are shown in (Saighani, 2018).

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Allocation Key ‘Motor Traffic’: Expenses and revenues caused by both car and truck traffic (e.g. revenues and expenses from traffic control, vehicle registration) are allocated proportionally to the share of the total (motor vehicle) annual mileage. Allocation Key ‘Traffic Area’: The urban road transport infrastructure is jointly used by several transport systems, which means that a clear allocation to a specific transport system is generally not possible. The allocation key ‘traffic area’ is determined by georeferenced data that differentiate the road network according to category groups (VS, HS, ES) or categories of routes (VS II to ES V) by (RIN, 2009). To determine the allocation key 'traffic area', the area of the entire public road transport is classified into various infrastructures (e.g. lanes, cycle tracks, sidewalks) and attributed to the causative or the primarily used transport system (see Tab. 1). For road transport infrastructures used by more than one transport system, a division according to area use and usage-dependence, according to defined and harmonised attribution factors, has been made (see Tab. 1). Tab. 1: Attribution of the areas of road transport infrastructures to urban transport systems on the basis of attribution factors Road Transport Infrastructure Lane surfaces Parking facilities Bus lanes Bus bay Bus and Tram stops Tram tracks not free for motor vehicles Tram tracks free for motor vehicles Raised cycle tracks Shared lane markings not free for motor vehicles Shared lane markings free for motor vehicles Conventional bike lanes Buffered bike lanes Shared side path (combined bicycle and pedestrian) Sidewalks Sidewalks free for bicycles Pedestrian zones Roadside greenery (Nature Strip, Green Strip)

Truck-Traffic

Car-Traffic

(vehicles > 3.5 tons)

(vehicles ≤ 3.5 tons)

p(laTruck,rtype) ----------0.5 * p(laTruck,rtype) ----0.33 * p(laTruck,rtype) 0.33 * p(laTruck,rtype) p(laTruck,rtype) --------0.2

p(laCar,rtype) 1.0 --------0.5 * p(laCar,rtype) ----0.33 * p(laCar,rtype) 0.33 * p(laCar,rtype) p(laCar,rtype) --------0.2

Local Public Transport p(laBus,rtype) --1.0 1.0 1.0 1.0 0.5 * p(laBus,rtype) + 0.5 ----0.33 * p(laBus,rtype) 0.33 * p(laBus,rtype) p(laBus,rtype) --------0.2

BicycleTraffic --------------1.0 1.0 0.67 0.67 --0.5 ------0.2

PedestrianTraffic ------------------------0.5 1.0 1.0 1.0 0.2

The use-dependent and surface-used attribution of lanes is weighted based on the respective traffic volume of the vehicles operating on them and differently determined by type of roads. For this, input variables from two different data sources are needed: (i) lane surface areas from a geographical information system (GIS) and (ii) average daily traffic volumes (dtv) for specific routes and transport systems resulting from the traffic assignment of an urban travel demand model. Based on georeferencing, these two data sets from different sources can be combined in a geographical information system and then analysed. According to (Saighani, 2018), the share of lane surface areas weighted by traffic volume is determined for each motorised transport system and road type according to equation (1).

p(la

mts, rtype

)

 (p(q

kK rtype

mts, k

 la

)  la k )

k

kK rtype

with  q mts, k  q ,  k p(q mts, k )  1 , 0 ,  

(1)

if

qk  0

if

qk  0

and mts  car (veh.  3.5 t)

if

qk  0

and mts  car (veh.  3.5 t)

p(lamts,rtype) … (weighted) share of lane surface area per motorised transport system (mts) and road type (rtype) [-] p(qmts,k)

… share of traffic volume per motorised transport system (mts) and route section (k) [-]

lak

… lane surface area per route section (k) [m²]

qmts,k

… traffic volume per motorised transport system (mts) and route section (k) [vehicles/24h]

krtype mts rtype

… quantity of all route sections (k) per road type (rtype) … motorised transport system (mts) {truck, car, public bus} … road type {main road, residential road}

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The allocation key ‘traffic area’ is calculated from the proportion of the total area attributed to a transport system to the total of all road transport infrastructure areas. Allocation Key ‘Depreciation Costs of the Transport Infrastructure and Maintenance’: The allocation key 'depreciation costs and maintenance' was developed to allocate the depreciation costs of infrastructure and costs for the planning, construction and maintenance of road infrastructure and civil engineering structures (e.g. bridges, tunnels). Both linear and cyclical depreciation costs are considered on the basis of the booked revenues and expenses in the household. To determine the allocation key, the total infrastructure in the urban transport network is recorded in detail (see ‘traffic area’). Then for all infrastructure elements, fictitiously planned road structures and equipment’s are selected, measured and dimensioned according to the currently valid technical regulations. For this purpose, standardised asphalt pavements are dimensioned according to (RStO, 2012) for all road transport infrastructures. The respective type of asphalt mix is selected according to the construction class and the expected traffic volumes from (ZTV, Asphalt 2007). The corresponding surface drainage systems are dimensioned in a simplified manner according to (RAS-Ew, 2005) and other standards. Subsequently, the single layers are priced at unit prices of (f:data, 2016) and depreciated to their replacement costs on the basis of specific useful lives per layer (see, e.g. RPE-Stra 01, 2001; AABV, 2010) using linear depreciation. The international literature contains various methods for weight-dependent allocation of heavy goods vehicles. A detailed overview can be found in (Link et al., 2008). In this paper the depreciation costs of the road transport infrastructure are allocated to the various vehicles on the basis of the 'incremental-cost-approach', based on the concept of 'minimal' roads (see, e.g. FHWA, 2006; INFRAS et al., 2013). Based on this principle, it is assumed in the first step that the costs for the construction of a road, based on the lowest construction class according to (RStO, 2012), fully allocate to vehicles ≤ 3.5 tons (passenger cars). The weight and dimension-dependent additional costs caused by heavy goods vehicles (vehicles > 3.5 tons) are then determined by dividing the specific depreciation costs of the road elements into ‘increments’, which will result from the transition to the next higher construction class. The total of the various increments resulting from a higher construction class according to (RStO, 2012) due to heavy goods vehicles are fully allocated to heavy traffic (public bus and truck). The allocation of the heavy traffic-related incremental costs (public bus and truck) is based on the respective traffic volume on the respective route section. Finally, the allocation key results from the proportion of the fictitiously determined depreciation costs of the allocated road transport infrastructures of a transport system to the total of all fictitious depreciation costs. Allocation Key ‘Street Cleaning’ and ‘Winter Maintenance’: For the determination of the allocation keys ‘street cleaning’ and ‘winter maintenance’, the areas of road transport infrastructures cleaned or cleared by the municipality, or on its behalf, are taken into account. These are weighted according to the frequency of cleaning or prioritisation within the scope of winter road clearance and set in relation to the total area to be cleaned or cleared. The corresponding allocation keys are calculated based on the weighted areas of road transport infrastructures that can be allocated to each transport system in relation to the weighted total area (similar to ‘traffic area’). Allocation Key ‘Street Lighting’: The allocation key ‘street lighting’ is based on fictitiously planned street lighting, which was determined according to the norms (DIN EN 13 201, 2005) using the planning software (TX-Win street, 2010). In this manner, the necessary street lighting is determined for the entire road network and allocated to the transport systems using the attribution factors of the allocation key 'traffic area'. The allocation key results from the relation of the number of lights for a transport system to the total number of lights in the municipality. Allocation Key ‘Traffic Signals’: The allocation key 'traffic signals' is determined based on the actual traffic signals in the road network. The number of traffic signals is weighted based on factors for size and energy consumption and allocated to the various transport systems on the basis of attribution factors. The allocation key results from the quotient of the weighted traffic signals allocated to a transport system and the total number of weighted traffic signals in the municipality. Compilation of transport system specific revenues and expenses (step 5 and step 6): For each position, the calculated allocation keys can be used to allocate revenues and expenses to the various urban transport systems. The first result is the total (annual) expenses and revenues for each urban transport system. Subsequently, indicators were calculated to enable comparisons between the transport systems and for monitoring (see Tab. 2).

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3.2. Taking external effects into account In this paper, the allocation-relevant external effects caused by transport operations are considered: accidents, air pollution, greenhouse gas and noise emissions. The costs resulting from upstream and downstream processes for providing energy for the operation of transport modes (fuel production and electricity production) are not considered. According to (Tinbergen, 1968) these external costs should be internalised directly in the upstream and down-stream processes and not in the transport sector. The external benefits of active mobility of pedestrians and cyclists are also considered in this paper. The determination of the external effects is based on already existent national and international methods which can be monetised with corresponding (accepted) cost factors from literary sources. The external effects are estimated following a cautious estimate of the expected real costs or benefits according to the 'atleast approach'. 4. Results and Conclusion To demonstrate the applicability of the above, the method was used in three cities of different sizes in Germany (City of Bremen, Kassel and Kiel). The results of the practical application of the business economic comparison show that non-motorised transport modes received the lowest financial subsidies in all the cities studied (9% to 20%) and motor vehicle traffic the highest (47% to 56%). The cost coverage ratio ‘Full-Cost’ as an economic efficiency indicator is highest in local public transport (56% to 82%) and lowest in truck traffic (8% to 30%). If the external effects (accidents, air pollution, greenhouse gas and noise emissions) are taken into account in the allocation, it becomes apparent that the largest share of total external costs is attributable to accident costs (44% to 57%) and the lowest to noise costs (4% to 9%). The main part of the external costs of approx. 85% to 92% is caused by motor vehicle traffic (car and truck traffic) and only 8% to 15% by the environmental transport systems (local public transport, bicycle and pedestrian traffic). In a comparison of passenger transport systems, car traffic is responsible for the highest external costs (60% to 79%) and pedestrian traffic for the lowest (1% to 3%). Pedestrians and cyclists not only cause very low external costs, they also generate significantly high benefits (negative costs). The results of the three cities show that approx. 66% to 82% are external costs in truck traffic, approx. 56% to 84% in car traffic and 11% to 37% in local public transport. The results of the method show that for full cost recovery and internalisation of external costs in the city of Kassel a mileage-related charge of 57.2 EUR-cents/vkm for trucks and 12.4 EUR-cents/vkm for passenger cars would have to be levied. Tab. 2 shows selected economic indicators for the city of Kassel. Tab. 2: Results of the economic comparison for the city of Kassel (selected economic indicators) Selected economic indicators Subsidy*(4)

Absolute [Mio. EUR] Relative Subsidy [%] Cost-Modal-Split in Passenger Transport [%] Cost-Coverage-Ratio ‘Full-Cost’ [%] Subsidy per inhabitant [EUR/inh.] Mileage-related subsidy [EUR-cents/vkm] External costs (total) (6) [Mio. EUR] Percentage of external costs [%] External costs per inhabitant [EUR/inh.] (Health) benefit in walking and cycling9 [Mio. EUR] ‚Uncovered‘ costs*(6) [Mio. EUR] Mileage-related costs (total)(5) [EUR-cents/vkm]

TruckTraffic(1) 5.3 8% --13% 27 20.5 9.3 13% 48 --14.6 57.2

CarTraffic(2) 27.3 39% 42% 37% 140 4.0 55.9 77% 286 --83.2 12.4

Local public transport(3) 28.8 41% 44% 56% 147 ---(8) 3.2 4% 16 --32.0 ---

BicycleTraffic 0.5 1% 1% ---(7) 3 --2.5 3% 13 -14.8(9) -11.8(9) ---

Pedestrian Traffic 8.6 12% 13% ---(7) 44 --2.1 3% 11 -60.2(9) -49.5(9) ---

Total 70.7 100% 100% --361 --72.9 100% 373 -75.0 -----

vehicles > 3.5 tons; (2) vehicles ≤ 3.5 tons; (3) Tram and public bus services; (4) results from the difference between expenses and revenues; (5) annual mileage in car and truck traffic was estimated from the respective urban transport demand models (without federal highways); (6) Price status: 2010; (7) are not reported because there are no direct income; (8) mileage-related subsidy (tram and public bus services): 4.1 [EUR/vkm]; (9) are shown negative (negative costs); *averaged between 2009 and 2011; ** without federal highways (1)

The newly developed method can be an important instrument for the implementation of transport policy goals. Therefore, the first step is a complete and cause-related cost allocation by applying the method described here. The results and indicators of the method achieve cost transparency, which can be used as a basis for discussion and decision-making with respect to funds for the different transport systems. Among other things, the method determines specific economic indicators that can be used directly as goal indicators in urban development and transportation

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planning. With the approach presented here, municipalities are for the first time able to have a complete overview of their transport-related revenues and expenses and external effects, differentiated each by urban transport system. Acknowledgement This paper is based on two research projects funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) within the National Cycling Plan 2020 (NRVP). The authors are solely responsible for the content. References AABV (2010): Verordnung zur Berechnung von Ablöseverträgen nach dem Eisenbahnkreuzungsgesetz, dem Bundesfernstraßengesetz und dem Bundeswasserstraßengesetz (Ablösungsbeträge- Berechnungsverordnung- ABBV), Stand 07/2010. Berlin (in German). Aberle, G. (2009). Transportwirtschaft: Einzelwirtschaftliche und gesamtwirtschaftliche Grundlagen (5th ed.). München: Oldenbourg (in German). BFS (2003): Schweizerische Strassenrechnung. Revision 2000. Schlussbericht, Version 2. 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