High Performance Buses: Cost Benefit Analysis DRAFT · Castalia is a part of the worldwide Castalia...

Confidential

Copyright Castalia Limited. All rights reserved. Castalia is not liable for any loss caused by reliance on this document. Castalia is a part of the worldwide Castalia Advisory Group.

High Performance Buses:

Cost Benefit Analysis

DRAFT

Report to the Ministry of Transport

December 2015

Confidential

Table of Contents

1 Summary and Introduction 1

2 Central Scenario Assumptions 2

3 Scenarios of Change 8

3.1 Baseline 8

3.2 Change in Market Capture by HPB Bus Variant 9

3.3 Max Rear Axle Loading Allowance (for Double Decker Buses) 12

3.4 Width Restrictions and Allowances 14

3.5 ESA Power Factors 16

Tables

Table 1.1: Results of Scenario Net Benefits 2

Table 2.1: Annual Market Size Estimates 3

Table 2.2: Market Growth rates 3

Table 2.3: Urban Bus Market Size Estimate 3

Table 2.4: Bus Operating Parameters 4

Table 2.5: Key Bus Variants and Capacity Assumptions 4

Table 2.6: Urban Bus Standing Capacity 4

Table 2.7: Load Factors for InterCity Bus Configurations 5

Table 2.8: Load Factors for Urban Bus Configurations 5

Table 2.9: Distribution Weighted Average ESA/km 6

Table 2.10: Current Market Share Capture of Intercity Bus Variants 7

Table 2.11: CBA assumptions (that are different from Freight CBA) 7

Table 2.12: Power factors 7

Table 3.1: Scenario A1 HPB Final Market Share 8

Table 3.2: Scenario A1 Costs and Benefits 9

Table 3.3: Scenario B1 Final Market Share 10

Table 3.4: Scenario B1 Costs and Benefits 10

Table 3.5: Scenario B2 HPB Final Market Share 11

Table 3.6: Scenario B2 Costs and Benefits 11

Table 3.7: Scenario C1: Costs and Benefits 12

Table 3.8: Scenario C2 Costs and Benefits 13

Confidential

Table 3.9: Scenario C3 Costs and Benefits 14

Table 3.10: Scenario D1: HPB Final Market Share 14

Table 3.11: Scenario D1: Costs and Benefits 15

Table 3.12: Scenario D2: HPB Final Market Shares 15

Table 3.13: Scenario D2: Costs and Benefits 16

Table 3.14: Scenario E1 Costs and Benefits (Power Factor of 2.5) 17

Table 3.15: Scenario E2 Costs and Benefits (Power Factor = 5.5) 17

Figures

Figure 2.1: InterCity Bus Trips by Loading Frequency 6

Figure 2.2: Urban Bus Trips by Loading Frequency 6

Figure 2.3: InterCity, Charter and Urban Bus ESAs Relative to ESAs of Truck Fleet 8

Figure 3.1: Scenario A1 HPB Market Share over Time 9

Figure 3.2: Scenario B1 HPB Market Share over Time 10

Figure 3.3: Scenario B2 HPB Market Share over Time 11

Figure 3.4: Scenario C1: Bus Trips by Loading Frequency 12

Figure 3.5: Scenario C2 Bus Trips by Loading Frequency 13

Figure 3.7: Scenario C3 Bus Trips by Loading Frequency 14

Figure 3.8: Scenario D1: HPB Market Share Over Time 15

Figure 3.9: Scenario D2 HPB Market Capture Over Time 16

Confidential

Acronyms and Abbreviations

CBA Cost Benefit Analysis

ESA Equivalent Standard Axle

HPB High Performance Bus

HPMV High Performance Motor Vehicle

MOT Ministry of Transport

NPV Net Present Value

NZTA New Zealand Transport Agency

VDAM Vehicle Dimensions and Mass

WOF Warrant of Fitness

Confidential

1

1 Summary and Introduction

The Vehicle Dimension and Mass (VDAM) Project is revising the rules that set the weight limits and dimensions for vehicles travelling on New Zealand roads.

The costs and benefits of rules that affect the freight component of the heavy vehicle fleet have been assessed in a previous Castalia report ‘Vehicle Dimensions and Mass Review: Framework for Options Assessment & Draft Rule Change Cost Benefit Analysis’.

This report considers the costs and benefits of changes to the rules for the bus fleet. We use scenario analysis to understand the costs and benefits of changes in the rule.

The central scenario is the assessment of the net benefits of the proposed changes. It contains assumptions that are common across all scenarios, while other scenarios vary specific assumptions from the central scenario to provide insights on the possible outcomes of different policy choices or assumptions.

Each scenario combines assumptions and outcomes on bus market size and growth expectations, the expected passenger task, operating costs and other assumptions. The scenarios deal with the following variations:

A higher or lower number of high performance buses (HPB) in the fleet over time

Allowing higher rear axle weight limits on the buses

Allowing a high performance bus to be 2.55 metres wide (rather than 2.5 metres)

Assessing the outcome for harder or softer pavements

Results for the Central scenario are positive

The Central scenario shows a positive net benefit of $346.3 million NPV. This is a result of a gain in share by HPBs leading to productivity improvements that are over and above increased road wear and other costs.

Scenario results show the Central result is sensitive to key assumptions:

The overall share that the HPBs achieve in the fleet is an important variable and the most influenced by policy choices. A small share reduces the net benefit and a high share increase the net benefit.

Increasing rear axle weight limits to 18 tonnes reduces the net benefit as pavement wear outweighs productivity gains. Smaller increases show a net benefit, however.

Width restrictions are important as the assumption is that most available buses are 2.55m wide. Not allowing this width is expected to severely restrict availability and increase the price of buses, resulting in a lower share for HPBs.

The result is sensitive to pavement strength. The softest pavement assumption shows a negative return. Conversely, the highest benefit is when pavement strengths are increased. The result remains positive for all reasonable assumptions about pavement wear.

Confidential

2

Table 1.1: Results of Scenario Net Benefits

Scenario Variant Net Benefit ($ million, NPV)

A. Central 1 – Central 346.3

Variances to Central Scenario

B. Market Share of HPBs 1 – High share +42.3

2 – Low Share -261.4

C. Max Rear Axle Loading 1 – 16.7t +35.6

2 – 17t +20.9

3—18t -43.5

D. Width restrictions 1 – supply restricts share to 20%

-88.7

2 – Supply unrestricted and grows to 70%

+172.2

E. Pavement Strength 1 – Hard roads +214.1

2 – Soft roads -348.3

2 Central Scenario Assumptions

To complete this cost benefit analysis requires assumptions on the following variables:

Market size (intercity and urban)

Operating parameters of buses

Bus types (variants) and capacity

Market share capture by bus variant

Operating costs and power factors for pavement wear

Each of these assumptions is described below.

Market size assumptions for intercity and charters

Market size assumptions are important because they determine the overall size of the passenger task. The passenger task is a combination of the number of buses and the effort that each bus undertakes. The number of buses might be an underestimation for the total number of buses in the fleet, but, if it represents the 80 or 90 percent of effort that the buses undertake then the market size estimate is sufficiently accurate. This is likely because the information that we do have represents the largest participants in the markets. A larger (or smaller) passenger task would scale up (down) the benefits and costs represented in each scenario.

The Bus and Coach Association surveyed their members and asked a series of questions designed to provide a snapshot of the market for intercity bus travel in New Zealand. From this survey we obtained information on member’s views on market size, operating costs, growth and other factors. This information enabled us to extrapolate an overall market size based on firstly our assessment of the market share of bus and coach

Confidential

3

members and secondly the proportion of charter buses (not surveyed) relative to intercity buses (surveyed).

Table 2.1 below provides the annual market size assessment based on this data and associated assumptions. Charter buses are assumed to be two thirds as large a market as intercity buses but travelling at half the kilometre rate per year. The bus and coach members are assumed to be 88 percent of the market.

Table 2.1: Annual Market Size Estimates

InterCity Survey Data

2015 # of InterCity Buses # 150

2015 Total InterCity Bus km km 19,884,750

2015 Average km/InterCity Bus Km/yr 132,565

Charter Bus Estimation

2015 # of Charter Buses # 100

2015 Total InterCity Bus km km 6,628,250

2015 Average km/Charter Bus km/year 66,283

Source: Survey of Bus and Coach Association members, September 2015

An assumption for the rate of growth in the intercity bus market is required as the passenger task is assessed over a 30-year time frame in the analysis. In the short run, industry assertions and expectations are used to grow the market, while assumptions revert to GDP growth rates over the long run.

Table 2.2 below describes the assumptions used for market growth rates:

Table 2.2: Market Growth rates

Time Period Growth rate (%)

Short run industry projection 1-3 yrs 3.3

Medium run industry projection 4-10 yrs 2.3

Long-run assume same as GDP growth >10yr ~2.1

Source: Survey and Castalia

Urban Bus Market Size Estimate

The urban bus fleet is modelled based on a survey of a large bus operator and extrapolated across the remaining market. Table 2.3 below provides these estimates:

Table 2.3: Urban Bus Market Size Estimate

Urban Bus Estimation

2015 # of Urban Buses # 1,289

2015 Total Urban Bus km km 57,996,000

2015 Average km/Urban Bus km/year 45,000

Confidential

4

Source: NZBus Survey Results

Operating parameters of buses in the intercity and urban markets

The operating factors of each bus determine the share of effort that each bus undertakes of the overall task. The weight of each bus influences the other CBA parameters including road wear, safety and emissions.

Table 2.4 below describes the key operating parameter assumptions used:

Table 2.4: Bus Operating Parameters

Operating parameter InterCity Urban

Productivity growth (i.e. # of kms per bus)

assumed constant (i.e. at maximum)

assumed constant (i.e. at maximum)

Average passenger weight 77kg 77kg

Average baggage weight per passenger 10kg 0kg


Key bus variants and capacity assumptions

The configuration of the bus is a crucial element in understanding the load factors placed on the road, in particular, but also the share of the task that the bus can perform. We have identified four key bus variants that perform the majority of the current task, and are expected to be available to varying degrees under different scenarios in the future. These variants are the standard single decker variants available now, including single and double rear axles. The other two options are double decker variants with either two double tyre axles at the rear, or, a single and a double tyre axle at the rear. We have not at this point modelled a single rear axle double decker.

Table 2.5 below describes the carrying capacity assumptions for different bus configurations.

Table 2.5: Key Bus Variants and Capacity Assumptions

Bus type variant Max Seating per Bus Average Passengers per trip

Capacity factor

Single Deck 2axle [1s-1d] 38 23.98 63.1%

Single Deck 3axle [1s-1d-1s] 50 31.56 63.1%

Double Deck 3axle [1s-1d-1s] 80 50.49 63.1%

Double Deck 3axle [1s-2d] 80 50.49 63.1%


Table 2.6 below describes the assumptions regarding the maximum standing capacity for a bus at peak times.

Table 2.6: Urban Bus Standing Capacity

Bus type variant Max Standing Capacity per Bus

Single Deck 2axle [1s-1d] 18

Confidential

5

Single Deck 3axle [1s-1d-1s] 25

Double Deck 3axle [1s-1d-1s] 32

Double Deck 3axle [1s-2d] 32

Source: NZBus

The carrying capacity assumptions drive the following load factors shown below in Table 2.7.

Table 2.7: Load Factors for InterCity Bus Configurations

BUS Tare Mass (t)

Max Mass (t)

Average Bus Payload

Average mass

Max Rear Axle Load

ESA at 0%

ESA at 100%

Single Deck 2axle [1s-1d]

10.6 13.9 2.09 12.69 9.04 0.67 1.98

Single Deck 3axle [1s-1d-1s]

15.5 19.85 2.75 18.25 12.90 1.53 4.11

Double Deck 3axle [1s-1d-1s]

17.7 24.66 4.39 22.09 16.03 2.60 9.79

Double Deck 3axle [1s-2d]

17.7 24.66 4.39 22.09 16.03 2.05 7.72

Table 2.8 below describes the configurations for the urban fleet.

Table 2.8: Load Factors for Urban Bus Configurations

BUS Tare Mass (t)

Max Mass (t)

Average Bus Payload

Average mass

Max Rear Axle Load

ESA at 0%

ESA at 100%

Single Deck 2axle [1s-1d]

10.6 14.91 2.09 12.45 9.69 .67 2.68

Single Deck 3axle [1s-1d-1s]

15.5 21.28 2.75 17.93 13.83 1.53 5.43

Double Deck 3axle [1s-1d-1s]

17.7 26.32 4.39 21.59 17.11 2.60 12.72

Double Deck 3axle [1s-2d]

17.7 26.32 4.39 21.59 17.11 2.05 10.02

Assumptions must also be made regarding the loading of the bus per trip. These are shown below in Figure 2.1:

Confidential

6

Figure 2.1: InterCity Bus Trips by Loading Frequency

The distribution is skewed right and the mean equals the bus weight at its average capacity factor.

For the urban bus fleet, we have assumed a bimodal distribution to reflect the two peaks in a normal working day. Figure 2.2 below depicts this assumption.

Figure 2.2: Urban Bus Trips by Loading Frequency

Distribution weighted average ESA/km are detailed in Table 2.9 below (note ESA function of weight to 4th power).

Table 2.9: Distribution Weighted Average ESA/km

Exponent Intercity Buses Urban Buses

Average ESA from F.Dist

Single Deck 2axle [1s-1d] 1.459 1.367

Single Deck 3axle [1s-1d-1s] 3.021 2.769

Double Deck 3axle [1s-1d-1s] 6.577 6.454

0%

5%

10%

15%

20%

25%

14

-15

15

-16

16

-17

17

-18

18

-19

19

-20

20

-21

21

-22

22

-23

23

-24

24

-25

25

-26

% o

f Tr

ips

Total Loading(tonnes)

Assumed BUS Trips by Loading Frequency

Double Decker Single Deck Bus

Confidential

7

Double Deck 3axle [1s-2d] 5.184 5.087

Market share capture by bus variant

The market capture over time by bus variant is the key variable that policy can influence. The current assumed position is described below in Table 2.10:

Table 2.10: Current Market Share Capture of Intercity Bus Variants

Current Capture of InterCity/Charter Bus Passenger Demand

Current InterCity Assumed Composition

Current Urban Assumed Composition

Single Deck 2axle [1s-1d] 10.0% 50%

Single Deck 3axle [1s-1d-1s] 85.0% 50%

Double Deck 3axle [1s-1d-1s] 5.0% 0%

Double Deck 3axle [1s-2d] 0.0% 0%

Operating costs and power factors

The Freight study already completed documents many of the base assumptions in the CBA and fleet models. Variations are noted in Table 2.11 below:

Table 2.11: CBA assumptions (that are different from Freight CBA)

Operating Cost $ per km (excl labour)

Single Decker 1.73

Double Decker 2.08

Labour Cost $ per km

Single Decker 0.50

Double Decker 0.50

The road consumption cost is measured in $/ESA. The assumption is the same as used in the Heavy Vehicle analysis ~ NZD 0.3/ESA

Power factors represent the consumption (damage) of roads as weight increases. A higher factor represents more damage (a softer road). The ESA power factor used is 4.0. This represents an average use of all roads. If only local roads were used a power factor of up to 7.0 could be contemplated and if only State Highways were used a power factor of down to 2.5 could be contemplated. Table 2.12 below describes the power factors and their uses.

Table 2.12: Power factors

Application Power factor Central Scenario

Minimum (State Highways only) 2.5 No

Average (mix of all roads) 4.0 Yes

Maximum (soft local roads only) 7.0 No

Confidential

8

The total ESAs on the networks grow as the fleet changes and the market grows. This is shown below in Figure 2.3 as bus ESAs grow from 7 percent to 12 percent of total ESAs.

Figure 2.3: InterCity, Charter and Urban Bus ESAs Relative to ESAs of Truck Fleet

3 Scenarios of Change

The following scenarios and variations have been modelled:

Baseline (A1)

Change in market capture of each bus variant (B1, B2)

Maximum rear axle loading allowance changes (C1, C2, C3)

Changes in width restrictions and allowances (D1, D2)

Softer and harder pavement assumptions (the impact of using different ESA power factors (E1, E2))

These results of these scenarios are described below.

3.1 Baseline

Scenario A1 results

Table 3.1 below describes the bus variant share after 20 years for the baseline scenario A1. In this scenario the dominant double decker variant is the 3 axle, one double version which rises to 35 percent market capture.

Table 3.1: Scenario A1 HPB Final Market Share

Future Capture of Bus Passenger Demand InterCity Urban




0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

0500

1,0001,5002,0002,5003,0003,5004,0004,5005,000

Mill

ion

ESA

s

Total Truck ESAs Total InterCity Charter and Urban Bus ESAs Bus % of Total ESAs

Confidential

9


Figure 3.1 below shows the change in the bus variant share over the period of analysis for the central scenario.

Figure 3.1: Scenario A1 HPB Market Share over Time

Table 3.2 below shows a significant net benefit of $346.3 million NPV.

Table 3.2: Scenario A1 Costs and Benefits

NPV Costs ($m) NPV Benefits ($m)

Productivity 381.7

Road Costs -91.4

C02 Costs 3.3

Health Costs 43.2

Safety Costs 9.5

Total -91.4 437.7

Net Benefit 346.3

3.2 Change in Market Capture by HPB Bus Variant

The rate at which HPB bus variants capture market share of the intercity passenger task over the 30-year time frame is the key variable in determining the outcome. It is also the key influence that policy will have on the outcome. We model two variations to the baseline scenarios that represent a high and a low share for the HPBs.

The exact combination of policy changes now, and in the future, will determine where on this spectrum the outcome will fall. It is likely that the combination of policies in the package will drive the overall direction of market share growth for any particular variant.

0

500

1000

1500

2000

2500

3000

Nu

mb

er

of

Inte

rCit

y, C

har

ter,

an

d

Urb

an B

use

s

Single Deck 2axle [1s-1d] Single Deck 3axle [1s-1d-1s]

Double Deck 3axle [1s-1d-1s] Double Deck 3axle [1s-2d]

Confidential

10

Scenario B1: HPB share high

If the share of the double tyre rear axle variant is increased, then the most favourable outcome results. In this scenario the share of the double rear tyre double rear axle variant reaches 35 percent over 20 years.

Table 3.3 describes this scenario for final share capture below.

Table 3.3: Scenario B1 Final Market Share






This is described over the period of analysis in Figure 3.2 below:

Figure 3.2: Scenario B1 HPB Market Share over Time

Table 3.4 below shows a significant net benefit of $388.6 million NPV (a 42.3 million improvement over the Central scenario).

Table 3.4: Scenario B1 Costs and Benefits

NPV Costs NPV Benefits

Productivity 381.7

Road Costs -49.1

C02 Costs 3.3

Health Costs 43.2

Safety Costs 9.5

Total -49.1 437.3

0

500

1000

1500

2000

2500

3000

Nu

mb

er

of

Inte

rCit

y, C

har

ter,

an

d

Urb

an B

use

s



Confidential

11

Net Benefit 388.6

Variance to Central +42.3

Scenario B2 HPB Share Low

If the share of the double tyre double rear axle variant is zero then the least favourable outcome results. In this scenario the share of the double rear tyre double rear axle variant reaches 0 percent over 20 years and the double axle six tyre variant only reaches 30 percent.

Table 3.5 describes this scenario for final share capture below.

Table 3.5: Scenario B2 HPB Final Market Share






This is described over the period of analysis in Figure 3.3 below:

Figure 3.3: Scenario B2 HPB Market Share over Time

Table 3.6 below shows a small net benefit of $84.9 million NPV.

Table 3.6: Scenario B2 Costs and Benefits


Productivity 98.3

Road Costs -31.0

C02 Costs 1.1

0

500

1000

1500

2000

2500

3000

Nu

mb

er

of

Inte

rCit

y, C

har

ter,

an

d

Urb

an B

use

s



Confidential

12

Health Costs 13.3

Safety Costs 3.1

Total -31.0 115.8

Net Benefit 84.9

Variance to Central -261.4

3.3 Max Rear Axle Loading Allowance (for Double Decker Buses)

In these scenarios we allow the rear axle loading allowance to vary. The central scenario (A1) has a 16 tonne weight allowance. Here we test variations of 16.7 (C1) tonne, 17 (C2) tonne, and then an 18 tonne allowance to understand how this might vary the outcomes. Maximum axle loading is only achieved when a bus is at its maximum carrying capacity.

In each scenario we assume that the higher weight tolerance would not alter the passenger carrying capacity, but would instead lead to an increase in the tare weight of buses imported—i.e. more mass or features such as electric engines or air-conditioning. We assume that the higher axle allowance would only affect the intercity and charter buses.

Scenario C1 – Max rear axle loading allowance 16.7 tonne

The percentage of trips undertaken at each weight loading changes as we vary this assumption. This is illustrated in Figure 3.4 below:

Figure 3.4: Scenario C1: Bus Trips by Loading Frequency

Table 3.7 below shows a medium net benefit of $35.6 million NPV relative to the Central scenario.

Table 3.7: Scenario C1: Costs and Benefits


Productivity 67.3

Road Costs -59.1

C02 Costs 0.2

0%

5%

10%

15%

20%

25%

30%

35%

15-16 16-17 17-18 18-19 19-20 20-21 21-22 22-23 23-24 24-25 25-26

% o

f Tr

ips


Assumed BUS Trips by Loading Frequency Double Decker Single Decker

Confidential

13

Health Costs 24.3

Safety Costs 2.9

Total -59.1 94.7

Net Benefit (variance to Central) 35.6

Scenario C2 – Max rear axle loading allowance 17 tonnes

Loading distribution of trips moves to a higher level under this scenario as described in Figure 3.5.

Figure 3.5: Scenario C2 Bus Trips by Loading Frequency

Table 3.8 below shows a small net benefit of $20.9 million NPV.

Table 3.8: Scenario C2 Costs and Benefits


Productivity 67.3

Road Costs -73.7

C02 Costs 0.2

Health Costs 24.2

Safety Costs 2.9

Total -73.7 94.6

Net Benefit (variance to Central) 20.9

Scenario C3 – Max rear axle loading allowance 18 tonnes

The loading distribution of trips is pushed out further with the tare weight of imported double decker buses increasing to approximately 20 tonnes as described in Figure 3.6

0%

5%

10%

15%

20%

25%

30%

35%

15-16 16-17 17-18 18-19 19-20 20-21 21-22 22-23 23-24 24-25 25-26 26-27

% o

f Tr

ips



Confidential

14

Figure 3.6: Scenario C3 Bus Trips by Loading Frequency

As illustrated in Table 3.9, scenario C3 would lead to a small net cost of $43.5 million NPV.

Table 3.9: Scenario C3 Costs and Benefits


Productivity 67.3

Road Costs -137.6

C02 Costs 0.2

Health Costs 23.6

Safety Costs 2.9

Total -137.6 94.0

Net Benefit (Variance to Central) -43.5

3.4 Width Restrictions and Allowances

If width restrictions remain at 2.5 metres rather than the international standard of 2.55 metres there will be a restricted supply of buses. This is modelled in the scenario below as a restriction on the ability of the double axle variants to gain share.

Scenario D1: Width limited to 2.5 metres, supply restricted, share restricted

Final market share assumptions are described in Table 3.10 below.

Table 3.10: Scenario D1: HPB Final Market Share






0%

5%

10%

15%

20%

25%

30%

35%

18-19 19-20 20-21 21-22 22-23 23-24 24-25 25-26 26-27 27-28 28-29 29-30

% o

f Tr

ips



Confidential

15

Figure 3.7 below describes the market share capture over time for this scenario:

Figure 3.7: Scenario D1: HPB Market Share Over Time

Table 3.11 below shows a significant net benefit of $257.6 million, but this is below the baseline.

Table 3.11: Scenario D1: Costs and Benefits


Productivity 284.6

Road Costs -69.9

C02 Costs 2.3

Health Costs 33.8

Safety Costs 6.7

Total -69.9 327.5

Net benefit 257.6

Variance to baseline -88.7

Scenario D2: Width allowed at 2.55 metres, supply increases, share increases

There are limitations to the scenario analysis for this variable because we do not know the long term real effect on supply costs for a width of 2.5 metres. Our estimates are based on outcomes of different shares and described in Table 3.12.

Table 3.12: Scenario D2: HPB Final Market Shares





0

500

1000

1500

2000

2500

3000

Nu

mb

er

of

Inte

rCit

y, C

har

ter,

an

d

Urb

an B

use

sSingle Deck 2axle [1s-1d] Single Deck 3axle [1s-1d-1s]


Confidential

16

Double Deck 3axle [1s-2d] 5% 0%

Figure 3.8 below describes the market share capture over time:

Figure 3.8: Scenario D2 HPB Market Capture Over Time

Table 3.13 below shows significant net benefits above the baseline of $518.5 million.

Table 3.13: Scenario D2: Costs and Benefits


Productivity 589.6

Road Costs -161.0

C02 Costs 5.4

Health Costs 69

Safety Costs 15.5

Total -161.0 679.6

Net Benefit 518.5

Variance to baseline +172.2

3.5 ESA Power Factors

Two scenarios are modelled relative to the central scenario which used an ESA of 4. Scenario A uses 2.5 representing harder roads and Scenario B uses 5.5 to represent softer roads.

The outcome is very sensitive to these assumptions. However, both 2.5 and 5.5 represent power factors that are an extreme assumption for all kilometres travelled and this sensitivity test shows that it would take an overall power factor of 5.5 to completely negate the benefits of the proposal.

0

500

1000

1500

2000

2500

Nu

mb

er

of

Inte

rCit

y, C

har

ter,

an

d

Urb

an B

use

s



Confidential

17

Scenario E1: Power factor for road damage reduces to reflect harder pavements

Table 3.14 shows the outcome for an ESA power factor of 2.5. This power factor might represent travel solely on highways.

Table 3.14: Scenario E1 Costs and Benefits (Power Factor of 2.5)


Productivity 381.7

Road Costs 122.7

C02 Costs 3.3

Health Costs 43.2

Safety Costs 9.5

Total 0 560.4

Net benefit 560.4

Variance to Central +214.1

Scenario E2: Power factor for road damage increases to reflect softer roads

Table 3.15 shows the outcome for an ESA power factor of 7.0 for 50 percent of the kilometres travelled and 4.0 for the other 50 percent. We do not consider it possible that an entire bus network could operate on ESA 7.0 roads, but, a worst case scenario might have 50 percent of travel on the softest roads (at ESA 7.0), and 50 percent on medium roads (ESA 4.0) giving an overall average of ESA 5.5.

Table 3.15: Scenario E2 Costs and Benefits (Power Factor = 5.5)


Productivity 381.7

Road Costs -439.7

C02 Costs 3.3

Health Costs 43.2

Safety Costs 9.5

Total -439.7 437.7

Net benefit -2

Variance to Central -348.3

T: +1 (202) 466-6790 F: +1 (202) 466-6797 1747 Pennsylvania Avenue NW 12th Floor WASHINGTON DC 20006 United States of America T: +1 (646) 632-3770 F: +1 (212) 682-0278 200 Park Avenue Suite 1744 NEW YORK NY 10166 United States of America T: +61 (2) 9231 6862 Level 1, 27-31 Macquarie Place SYDNEY NSW 2000 Australia T: +64 (4) 913 2800 F: +64 (4) 913 2808 Level 2, 88 The Terrace PO Box 10-225 WELLINGTON 6143 New Zealand T: +57 (1) 646 6626 F: +57 (1) 646 6850 Calle 100 No. 7-33 Torre 1, Piso 14 BOGOTÁ Colombia T: +33 (1) 73 44 26 97 F: +33 (1) 73 44 26 01 6, Rue Duret PARIS 75116 France ------------- www.castalia-advisors.com

High Performance Buses: Cost Benefit Analysis DRAFT · Castalia is a part of the worldwide Castalia...

Documents

Transcript of High Performance Buses: Cost Benefit Analysis DRAFT · Castalia is a part of the worldwide Castalia...