New Rail Services

This measure was updated by INSTITUTE FOR TRANSPORT STUDIES (ITS) in 2014 under the CH4LLENGE project, financed by the European Commission.


New rail services on existing lines can provide new opportunities for people to travel or improved opportunities to travel by providing more direct services and so reducing the generalised cost of travel. Other interventions include regular and clock face timetables, service integration and reliability improvements.  They can be implemented to reduce travel time for existing users, to attract passengers from car use, and hence reduce congestion and environmental intrusion, to improve accessibility and to encourage economic regeneration.

By comparison with bus service improvements, rail service changes are relatively expensive and can take significantly longer to implement. However, they are likely to have a greater impact on attracting car users, and hence wider efficiency and environmental benefits.

Empirical evidence on such improvements is limited and often dated, but confirms the expectations that they can reduce car use and improve accessibility and efficiency.  Predictive analysis of clock face timetables suggests that they can increase patronage, reduce travel costs and attract car users without increasing financial costs.

Description

New rail services on existing lines can provide either new opportunities for people to travel or improved opportunities to travel by providing more direct services and so reducing the generalised cost of travel. In the UK examples of the latter include Hull Trains direct Hull to London service, whilst examples of the former tend to be based on services to and from new rail stations that have been opened on existing lines.

New rail lines offer new opportunities for people to travel and, hence, increase the geographical accessibility of the rail network. By default new rail lines will contain new stations. The large capital costs of new rail lines mean that by and large they tend towards small scale extensions of existing lines to major traffic generators (e.g. Manchester Airport ), although occasionally they can be a lot more substantial, e.g. Heathrow Express line and the Argyle Line in Glasgow.

Upgraded rail lines can involve the electrification of current track, the alteration of its alignment, constructing passing loops or increasing capacity in certain areas. The main reasons to upgrade tend to be to enable faster trains to operate on an existing rail line, to increase the capacity of the current rail line and to improve the reliability of current train services on the existing rail line.

Other Types of Service Level Changes

There are a number of other service level changes which have been identified by TRB (2003 author) and TRL (2004). These include:

  1. Regular Interval & Clockface Timetables – The former involves the implementation of a timetable that schedules services to arrive at a station or bus stop, at regular intervals, e.g. every 20 mins. The latter schedules services to arrive at the station or bus stop at the same time past the hour, e.g. 10 minutes past and 30 minutes past the hour. The reasoning behind these service patterns is that they should be easy to remember and will, in some cases, help minimise transfer times (Shires et al, 2003). They are very prevalent in Switzerland, the Netherlands, Austria and Germany.
  2. Combined Service Frequencies – This approach involves mixing stopping and express services on the same route to cater for different types of travel needs.
  3. Reliability Improvements – If a service is experiencing reliability problems, the operator may change the service schedule to ensure that this doesn’t happen.

Terminology

A change in service frequency will impact upon passenger demand in a number of ways, however in terms of terminology there are three which perhaps need to be clarified and result from a change in service frequency.

Schedule Delay Time – This is the difference between when a passenger would most like to travel and the actual time of travel. This could involve the time spent waiting at home or at work before walking to the station. The estimation of schedule delay time depends upon when passengers would ideally like to travel, the timetable and passengers’ preferences for arriving early or late. As service headway (time between two particular trains normally calculated as 60mins/number of trains per hour) increases it is likely that this element of generalised cost (the monetary and time cost of a journey) will be of greater importance than scheduled wait time.

Schedule Wait Time – This is the time spent waiting at the station and is usually taken to be a function of the service headway and service reliability. Where services are frequent and at regular intervals, passengers are assumed to arrive at the station at random and are therefore assumed to wait on average a time equal to half the service headway. Where services are infrequent, it is assumed that passengers time their arrival at the station to coincide with the arrival of the station.

Excess Wait Time – This is additional time spent at a station when the passenger has been unable to board the first train due to overcrowding. This component is largely beyond the control of the passenger and is a function of demand and the capacity of the service.

Without knowing more about the desired departure times of passengers it is difficult to accurately estimate schedule delay time and excess wait time and for this reason it is common to find scheduled wait time as the sole representative of service frequency in the specification of generalised cost, e.g. half of the headway = (30 mins/number of trains per hour).

Technology

It is much easier for bus services to implement changes to their current service levels on a daily, weekly or monthly basis, than for other more technical public transport systems such as rail and air which have to wait several months. Both rail and air operate on or from highly specialised infrastructure, where safety procedures are strictly adhered to. As such there is a high level of interaction between all services that mean changes to one service have considerable knock on effects to the network as a whole. For these reasons any changes in service levels have to be co-ordinated at a network level following discussions with all affected service operators. As such changes to service levels can take several months to be approved and implemented.

Why introduce changes to service levels?

Changes to service levels tend to be implemented for the following key reasons:

  1. Improve the quality of service for existing customers - An increase in service frequency will reduce the schedule waiting time, the schedule delay time, excess wait time and overcrowding levels for existing customers. This will reduce the generalised costs associated with trips and help to maintain the existing customer base and in some cases generate additional trips.

    An extension of service hours reduces the likelihood of a passenger being stranded and increases the opportunities to access particular goods and services. As such it is seen as an improvement of service quality by existing passengers and will help to maintain present patronage levels and generate further passenger trips.
  2. Improve the quality of service to attract additional customers – Just as an increase in service frequency will help retain existing public transport passengers, so an increase in service frequency will help attract additional passengers by reducing the generalised cost of public transport travel vis a vis private travel. Similarly an extension to the hours operated will increase the opportunity to travel and make public transport a real alternative for a wider range of journeys.
  3. To be cost effective – Many transport operators will offer different levels of service throughout the week to minimise their operating costs. Typically services tend to be lower in off peak periods (Monday to Friday), evenings and weekends.
  4. To meet a social welfare criterion – Additional services may be operated to help achieve some kind of social aim such as overcoming social exclusion, improving levels of accessibility and achieving modal switch away from car (so reducing accident and environmental impacts).

Demand impacts

When service levels change they influence the level of demand for public transport. In general, all other things being equal, an increase in service levels will increase patronage, whilst a decrease in service levels will reduce patronage. The size and direction of the change in demand following a change in service levels can be expressed in terms of a service elasticity and is defined as,

Service Elasticity = (Percentage Change in Demand)/(Percentage Change in Service Level)

For example, if the service elasticity of demand with respect to service frequency is 0.4, and all service frequencies were to increase by 10% we would expect patronage to increase by 4%. The service elasticity is therefore a measure of the sensitivity of passengers to service levels.

The absolute size of the service elasticity conveys information on the sensitivity of demand to changes in the factor affecting demand and its sign conveys information on the direction of the change. Service elasticities are defined as inelastic if they are less than 1.0 and elastic if they are greater than 1.0.

A wide range of factors influence the size of service elasticity and these are listed below:

  • Service levels – the lower the current level of service the more sensitive passengers will be to service level changes. Size of service level change – the larger the change in the service level the more sensitive passengers will be to the service level change.
  • Income levels – those on low incomes are less likely to be sensitive to changes in service levels and more sensitive to changes in fares.
  • Competition from other modes – strong competition from other public transport operators will make passengers more sensitive to fare changes.
  • Demographic factors – The elderly and school children are more sensitive to changes in service levels.
  • Journey purpose – travellers commuting to work tend to be less sensitive to service level changes, whilst leisure travellers are more sensitive.
  • Urban vs Rural – passengers tend to more sensitive to service changes in rural areas compared to passengers in urban areas.
  • Area - passengers tend to be less sensitive to service level changes in metropolitan areas compared with non- metropolitan areas.

Whilst these factors can be discussed in isolation it is likely that more than one of them will exert an influence at the same time. In general terms TRL (2004) reports a short run service frequency elasticity with respect to bus of around 0.4 and a long run elasticity of 0.7, with slightly higher figures for rail. These figures relate to mainly UK based evidence whereas the TRB report (2003) is based mainly on US evidence. The latter reports general service elasticities of around 0.5 in the short run, with most recent studies tending to group their observations around 0.3 and 1.0. The former figure tends to represent studies that are based on central city urban locations and the latter on suburban systems that have undergone well thought out expansion in a growing economy where public transport is well regarded. The expected responses and situations to changes in service levels are outlined below. We note that the extent of modal switch between train and car will be dependent upon the service cross elasticity between each mode. Cross elasticities measure the change in demand for one mode as a result of the change in one of the factors associated with another transport mode (mainly fare/cost or service frequency). The size of the cross elasticity will therefore depend upon how demand for car will alter (and therefore how demand for train will alter) due to a change in train service frequencies.

Responses and situations
Response Reduction in road traffic Expected in situations
A change in service levels is likely to affect people’s schedule delay time and so departure time, but is unlikely to affect car use.
Unlikely to affect people's routes.
If new service to new destinations were introduced then destinations may well alter.
Likely to generate more bus trips from existing users and new users.
Service improvements are likely to make train a more attractive mode of travel and so attract car users.
Likely to affect second household cars more.
Most likely to move house for other reasons.
= Weakest possible response = Strongest possible positive response
= Weakest possible negative response = Strongest possible negative response
= No response

In the short run passengers facing a change in service levels can either switch modes or not travel. In the long run the number of options increases to include, switching destinations, changing jobs, changing homes, purchasing a car etc.

Short and long run demand responses

In the short run passengers facing a change in service levels can either switch modes or not travel. In the long run the number of options increases to include, switching destinations, changing jobs, changing homes, selling a car etc.

Demand responses
Response 1st year 2-4 years 5 years 10+ years
 
 
 
 
 
 
= Weakest possible response = Strongest possible positive response
= Weakest possible negative response = Strongest possible negative response
= No response

Supply impacts

Altering service levels will have a direct effect on the fixed, the semi-variable and the variable costs experienced by transport operators. These are outlined in Whelan et al (2001) below.

(a) Variable costs are costs that vary directly and immediately with output. For example, fuel costs vary directly with vehicle kms operated, crew costs may vary directly with vehicle hours etc.

(b) Semi-variable costs are costs that only vary partially with output. For example, vehicle maintenance is partly related to the extent that vehicles are utilised but there is some element of maintenance that will need to be undertaken irrespective of how intensively the vehicle is utilised. Similar arguments hold true for vehicle depreciation.

(c) Fixed costs are costs that do not vary immediately with output. That is, they cannot be varied in the short run. These costs include buildings and general administration.

Transport services are not divisible and so neither are the costs associated with them. For example, if a train operator wished to increase a train service from 4 trains per hour to 5 trains per hour in the morning peak period (7am till 9 am) it would not simply be a case of hiring an additional train and driver for that two hour period. The additional train would have to be either purchased or leased on a permanent basis and the driver hired as either a part time or full time employee. The fixed cost element of an increase in service would therefore be substantial, i.e. the purchase costs, vehicle insurance, vehicle taxes, depot costs, maintenance costs. In practice an operator might choose to increase the service level throughout the day on one particular route, or might increase the service level of one route during the peak and another during the off-peak.

Financing requirements

The financing of an increase in service levels will tend to come from two main sources, the fare box and support from local/transit authorities. The make up of the funding will largely be decided by who makes the decision to increase service levels and the rationale for that increase. If the decision is made by the transport operator on purely commercial grounds then the operator will expect fare box revenue to cover the financing of the service increase. If a decision is taken by a local/transit authority to increase service levels on social grounds (e.g. to reduce social exclusion) then the costs of providing those services are likely to be met by a combination of fare box revenue and operating subsidies from local/transit authorities. These costs are also likely to vary according to the degree and/or type of regulation that is in place.

Expected impact on key policy objectives

Contribution to objectives

Objective

Scale of contribution

Comment

  Increase in public transport service levels will reduce the waiting times & overcrowding experienced by existing passengers. Public transport becomes a more attractive mode of transport and will encourage car users to switch, helping reduce traffic congestion.
  No impact expected.
  Increase in service levels will lead to some mode switching from car and so help reduce air and noise pollution.
  New services may be focused in particular areas currently not served by train or to new destinations that better meet users’ needs.
  Increase in service levels will lead to some mode switching from car and so help reduce accidents.
  Some stimulus from greater accessibility.
  Additional capital and operating costs.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Expected impact on problems

Contribution to alleviation of key problems

Problem

Scale of contribution

Comment

Congestion

An increase in service frequency will help combat unreliability for public transport users. Mode switching unlikely to have a major impact.
Community impacts No impacts expected.
Environmental damage By reducing car traffic emissions of NOx, particulates and other local pollutants.
Poor accessibility An increase in the service will increase the range of services, goods and opportunities open to people without a car.
Social and geographical disadvantage An increase in the service coverage will increase the range of services, goods and opportunities open to people in less well served areas.
Accidents By reducing car traffic.
Economic growth Some stimulus from greater accessibility.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Expected winners and losers

Winners and losers

Group

Winners/Losers

Comment

Large scale freight and commercial traffic

High value freight journeys - less time spent in congestion the greater the vehicle utilization, however a relatively small proportion of the journey distance is in urban conditions. Service increase reduces traffic congestion so is beneficial.

Small businesses

Service increase - encourages trips to non local areas.

High income car-users

High incomes associated with high value of time and thus continued car use for high value journeys. These journeys will benefit from reduced congestion. A service increase reduces traffic congestion so is beneficial.
People with a low income Unlikely to have car access. An extension of the service will increase the range of services, goods and opportunities open to them.
People with poor access to public transport If changes in service levels are restricted to existing services then no impact. However, if new services are implemented serving different areas then a very positive impact.
All existing public transport users Service increase - will lead to reduced generalised costs of travel (e.g. reduced waiting and overcrowding) & more opportunities to travel if the service is extended.
People living adjacent to the area targeted Service increase - they may benefit from reduced congestion and improved or increased public transport supply.
People making high value, important journeys Reduced generalised costs of public transport and reduced congestion will result in valuable time savings. A service increase reduces both so is beneficial.
The average car user Reduced congestion will result in valuable time savings. A service increase reduces both so is beneficial.
= Weakest possible benefit = Strongest possible positive benefit
= Weakest possible negative benefit = Strongest possible negative benefit
= Neither wins nor loses

Barriers to implementation

Scale of barriers
Barrier Scale Comment
Legal

There are usually few legal barriers to increasing service levels, but there may be regulatory problems if more than one operator is involved.

Finance Finance is a significant barrier, since new rail services typically require additional rolling stock.
Governance / The governance barrier depends critically on the regulatory structure.  There will be little problem if all rail operations are under the same management which is responsive to public policy requirements.  But division of responsibility between government and operator or between operators can pose significant problems. 
Political acceptability Provision of new services will typically attract political support provided that finance and governance issues can be resolved.
Public and stakeholder acceptability New services are unlikely to attract public opposition, and stakeholders are likely to be supportive provided that governance issues can be resolved.
Feasibility The main technical problems are likely to be signalling capacity and the resulting availability of train paths.
= Minimal barrier = Most significant barrier

Mass Transportation Demonstration Projects in Massachusetts (1962-64)
Frequency and Service Hours Enhancements in Santa Clarita, California
Appraisal Framework and Results for Testing A Regular Interval Rail Timetable (Shires et al, 2003)

 

Mass Transportation Demonstration Projects in Massachusetts (1962-64)

Context

Between 1962 and 1964 the Mass Transportation Commission of the Commonwealth of Massachusetts (MTC) conducted a number of mass transit service improvement and fare reduction experiments. The experiments centred on Boston and its inner suburbs, and involved bus operators, other than the Massachusetts Transit Authority (MTA), throughout the states and commuter railroads that served Boston.

The rail experiments were carried out on the Boston & Maine Railroad (B&M), the New Haven Railroad (NH), with the New York Central Railroad (NYCR) used as a control. The B&M experiment incorporated three phases:

  1. 77% equivalent increase in all services (92% increase in weekday services) & a 28% equivalent reduction in fares (ranging from 12% to 72%).
  2. Retention of phase 1 service improvements and virtual elimination of fares reduction (except for an off-peak reduction).
  3. Service levels adjusted and fare levels remain the same.

The NH experiment had 2 phases,

  1. Total average service level increased by 42% and fares reduced by 10% on average.
  2. Service levels and fares returned to pre-experiment levels, with off-peak fare incentives retained.

Impacts on demand

Rail Experiments

The results in terms of revenue and ridership changes are shown in Table 1.  The key figures to note in terms of service elasticities are those presented for phase 2 when fares were increased.  The increase in patronage was taken by MTC to imply that improvements in service levels were more effective at increasing ridership than were fare reductions.  Overall the additional revenues covered the full incremental cost of the experiment.

Table 1: Massachusetts Rail Headway Changes and Ridership Results

Rail System

Phase 1

Phase 2

Phase 3

B&M

+27% increase in ridership

+37.5% increase in ridership

+44% increase in ridership

NH

+10% increase in ridership

+11.5% increase in ridership

Not applicable

NYCR

-5.9% decrease in ridership

-5.9% decrease in ridership

-5.9% decrease in ridership

Source: Adapted from TRB (2003)

Surveys indicated that the majority of passengers on the commuting trains used to travel by the following modes: own car (63.6%), carpool member (16.9%), and bus (19.5%).

Impacts on supply

No cost figures were reported in the TRB report (2003), however the increase in service levels is likely to have resulted in additional costs from the purchasing/leasing of additional vehicles and hiring of additional operating staff.

Contribution to objectives

Contribution to objectives
Objectives Scale of contribution Comment
  Evidence indicated that a reduction in car use is likely to have contributed to an efficiency improvement by reducing road congestion.
  The reductions in car use are likely to have contributed to a liveability improvement.
  The reductions in car use will have contributed to a reduction in environmental impacts.
  Whilst no direct evidence was presented the increase in services is assumed to have had a sizeable impact upon equity and social inclusion.
  The reduction in car use will have contributed to a reduction in accidents.
  Efficiency improvements will have supported economic growth.
  No information given.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Frequency and Service Hours Enhancements in Santa Clarita, California

Context

Santa Clarita is an outlying suburb of Los Angeles in California (U.S.) with a population of around 150,000 that is served by a metrolink commuter rail service and local bus coverage.  Between 1992 and 1998 there were significant extensions to public transport service hours and service frequencies. These are outlined below:

  • 1992 - Saturday services expanded by 3 hours, i.e. larger operating period.
  • 1992 - Weekday service hours expanded by 2 hours, i.e. larger operating period.
  • 1994/5 - New express commuter bus services added.
  • 1995 - Weekday services expanded on three routes.
  • FY1995/8 - 30 minute all day headways introduced on 4 routes (including 2 on a weekend) and 15 minute peak headways on tow routes.

In addition a 90 minute pass was introduced in 1992, fares raised by 33% in 1993, youth passes rose to $15 from $10 in 1996, and Sunday services introduced on about two thirds of local routes.

Impacts on demand

The increase in both bus miles and bus hours over the five years in question has seen a greater than proportionate rise in ridership.  The lack of statistical smoothing of short run anomalies however, means that not much weight can be placed upon the yearly elasticities. More reliance can be placed on the long run elasticities which are +1.14 for bus miles and +1.55 for bus hours. 

Table 2: Santa Clarita, CA Local Fixed Route Performance and Log Arc Service Elasticities

Local Fixed

Routes-Year

City

Population

Annual

Bus Hours

Annual

Bus Miles

Annual Bus

Rides

Bus Hours

Elasticity

Bus Miles

Elasticity

FY 1992-93

1993-94

1994-95

1995-96

1996-97

1997-98

123,400

124,000

124,300

124,800

na

na

48,778

53,391

60,028

62,750

66,947

81,216

787,807

1,018,021

1,163,607

1,179,140

1,389,082

1,569,891

769,137

915,869

1,107,587

1,366,537

1,527,253

1,693,173

-

+1.93

+1.62

+4.74

+1.72

+0.53

-

+0.68

+1.42

+15.84

+0.68

+0.84

5 fiscal years

+2% (4 yrs*)

+66%

+99%

+120%

+1.55

+1.14

FY - Financial Year:  * - Calendar years 1992 (122,949 population) through to 1996 (125,153 population)
na - not available
Source: TRB (2003)

Impacts on supply

No cost figures were reported, however the increase in service levels is likely to have resulted in additional costs from the purchasing/leasing of additional vehicles and hiring of additional operating staff.

Contribution to objectives

Contribution to objectives
Objectives Scale of contribution Comment
  No direct evidence was provided, however it is likely that some modal shift has occurred, reducing congestion costs  and improving efficiency.
  No direct evidence was provided, however it is likely that some modal shift has occurred and that this has led to an improvement in liveable streets.
  No direct evidence was provided, however it is likely that some modal shift has occurred, leading to a reduction in environmental externalities.
  The extension of service will have opened up a wider range of services, goods and opportunities to those on low incomes.
  No direct evidence was provided, however it is likely that some modal shift has occurred, leading to a reduction in accident rates.
  No direct evidence was provided to allow a judgement to be made.
  No direct evidence was provided to allow a judgement to be made, but it is thought it will be substantial.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Appraisal Framework and Results for Testing A Regular Interval Rail Timetable (Shires et al, 2003)

Context

This study examined the demand and benefit implications from the introduction of a Taktfahrplan onto the east coast mainline rail route in the UK which runs from London in the South East of England to Aberdeen in the North of Scotland. The Taktfahrplan concept is frequently referred to as a clock face timetable and is based on trains leaving stations at the same time past the hour throughout the operational day. A new cross section demand model capable of modelling access and station choice was developed to incorporate the results of a stated preference exercise which was conducted to estimate what values people placed upon such a timetable. These values were added to the more conventional elements of generalised cost to obtain the changes in demand that would result from the introduction of a Taktfahrplan, e.g. regular clock face departures such as 00, 20, 40 minutes past the hour.

The model forecast the changes in patronage for the 360 O/D pairs for which CAPRI (computer analysis of passenger revenue information) data was available following the introduction of a Taktfahrplan. The forecasts were then subject to an appraisal process broadly comparable to that used by the Strategic Rail Authority (SRA).

Impacts on demand

The impacts on demand that resulted from the introduction of a Taktfahrplan were estimated for the 35 stations outlined in Table 5. The Taktfahrplan element of the timetable adhered to the principles of regular clock face departures in the majority of cases. This meant that departures were evenly spaced and at the same time every hour. In order to simplify the appraisal process only the top ten London routes and top ten non-London routes (ranked according to passenger flows) were chosen for a full appraisal (see table 5).

Table 5: Routes Selected for Appraisal

Non-London Routes

Ranking

York-Leeds

1

Leeds-York

2

Newcastle-Edinburgh

3

Newcastle-York

4

Darlington-Newcastle

5

Edinburgh-Newcastle

6

Doncaster-Leeds

7

Scarborough-York

8

Hull-Leeds

9

York-Edinburgh

10

London Routes

Ranking

Leeds-London

1

Newcastle-London

2

London-Edinburgh

3

London-Leeds

4

London-Newcastle

5

York-London

6

Edinburgh-London

7

London-York

8

Doncaster-London

9

Darlington-London

10

Not only do the appraisal tables outline the annual change in rail demand for each of the flows mentioned they also calculate the impacts upon the environment, modal shift and the wider economy. In all but one of the 10 non-London flows the introduction of a Taktfahrplan results in an increase in passenger flows. Around 68% of the additional trips are assumed to come from car, 24% from bus and 8% generated. This results in a considerable improvement in environmental benefits and reduced congestion on the roads. For the non-London flows the picture is more mixed with six of the ten flows recording a reduction in passenger flows and so increases in environmental impacts and traffic congestion. The study notes that this may reflect the greater variability of existing regional flows and that the Taktfahrplan tends to reduce the number of services for certain London based flows compared with the current levels. In particular the long distance London based flows seem to be particularly adversely affected (Edinburgh and Newcastle) compared to those under 200 miles (Leeds, Doncaster and Peterborough).

The picture painted by the top ten London based flows is also at odds with the overall line impacts forecast by the model for all the flows along the east coast mainline. These forecasts showed an increase in passenger flows on 76% of the London based flows and on 77% of the non-London based flows, leading to a line impact appraisal which resulted in a £15.6 million benefit for non-London flows and a £7.2 million benefit for London flows (Table 6).

Table 6: Annual Line Impact Appraisal (£s)

Route Type

(number of services)

User

Benefits

Revenue

Non-User

Benefits

Total

Non-London (314)

8,607,328

3,357,246

3,619,836

15,584,408

London (46)

3,746,527

3,052,665

416,917

7,216,109


Impacts on supply

The impact on supply is minimal as the Taktfahrplan has been designed around the level of engines and rolling stock that currently exists.

Contribution to objectives

The contribution of the Taktfahrplan to the objectives is written from the perspective of the overall line impact appraisal.

Contribution to objectives
Objectives Scale of contribution Comment
  The reduction in car use will have improved efficiency by reducing road congestion.
  The reduction in car use will have contributed to a liveability improvement to the extent that it affects urban travel.
  The reduction in car use will have contributed to a reduction in environmental impacts.
  There was no direct evidence on this issue.
  The reduction in car trips will have reduced the number of accidents.
  The improved efficiency is likely to assist economic growth.
  The Taktfahrplan was implemented at no additional financial cost.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Contribution to objectives and alleviation of problems

Contribution to objectives
Objective Massachusetts Santa Clarita Taktfahrplan
 
 
 
 
 
 
 
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

 

Contribution to alleviation of problems
Problem Massachusetts Santa Clarita Taktfahrplan

Congestion
Community impacts
Environmental damage
Poor accessibility
Social or geographic disadvantage
Accidents
Economic growth
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Appropriate contexts

Appropriate area-types
Area type Suitability
City centre
Dense inner suburb
Medium density outer suburb
Less dense outer suburb
District centre
Corridor
Small town
Tourist town
= Least suitable area type = Most suitable area type

Mackie, P. and Preston, J. (1996) "The Local Bus Market. A Case Study in Regulatory Changes". Avebury.

Mass Transportation Commission, MA, McKinsey & Co., Systems Analysis and Research Corp. and Joseph Napolitan & Associates (1964) "Mass Transportation in Massachusetts". U.S. Department of Transportation, Washington, DC (July 1964).

Oxley, P.R. (1982) "The Effects of the Withdrawal and Reduction of Rural Bus Services". Transport and Road Research Laboratory, Supplementary Report 719.

Preston J.M. (1998) Public Transport Elasticities: Time for a Re-think? paper presented to the Universities Transport Studies Group Conference, Dublin, January, 1998.

Shires, J.D., Johnson, D., Nash, C.A. and Tyler, J.T. (2003) "Appraisal Framework and Results for Testing A Regular Interval Rail Timetable". ITS Working Paper 578, University of Leeds.

Transportation Research Board (2003) "Traveler Response to Transportation System Changes". Chapter Nine, Transit Scheduling and Frequency, TCRP Report 95.

Whelan, G.A., Shires,. J.D, Toner, J.P. and Preston, J.M. (2001) "Modelling Quality Bus Partnerships". Report for DETR.