Personalised Journey Planning

Personalised journey planning (PJP) is a highly targeted measure to achieve reductions in car use. Personalised journey planning works with individuals (usually across a specified geographical area) to provide information on alternatives to the car for the trips that they make, and encourage use of those alternatives. Personalised journey planning falls under the umbrella of public awareness campaigns (Smarter Choices in the UK and sometimes Travel Smart elsewhere). These campaigns can range from passive advertising to a wide audience to PJP. It is also possible to implement multiple Smarter Choices simultaneously, such that each enhances the performance of another, e.g., advertising can support a PJP programme.

There are a number of steps on the way to achieving a reduction in car use, which can be tackled through a PJP programme. These include problem awareness, accepting responsibility, perception of alternatives, evaluation of alternatives, making a choice, experimental behaviour and habitual behaviour (TAPESTRY, 2003). It should also be noted that having made a change, habitual drivers can relapse into old travel patterns. Relapse may occur if individuals do not feel supported, they feel they are making changes in isolation, the alternatives they are using do not adequately meet their needs or involve too much effort, or they perceive that the need to use cars less has receded. Such relapses may not be permanent. Individuals can cycle through the stages of change several times. The change may be longer lasting each time until it becomes habitual.

Demand impacts resulting from PJP may be small initially (although this depends on other policy instruments), but are incremental over time as more campaigns are implemented. Contributions to achieving policy objectives are therefore mainly positive.

Terminology

Personalised journey planning (PJP) programmes are designed to support individuals and households in reducing their car use by providing information on alternatives to the car tailored to individuals and the trips they make. Such programmes are usually implemented within defined geographical areas, e.g., the whole of a smaller town, or district of a city. In the case of cities, the programme is often targeted at districts with good alternatives to the car in the first instance, and may be followed by a roll out over time across the whole city. PJP fits into the spectrum of travel awareness campaigns designed to increase individuals’ awareness of alternatives to private car use, and encourage modal shift. Awareness campaigns can range from blanket advertising (e.g., television, radio, bill boards, backs of buses – all forms of passive communication) to PJP, which is highly interactive. It is also possible to run both, such that the advertising supports the PJP (and vice versa). The term Travel Smart is sometimes used in specific reference to PJP regardless of who implements it. TravelSmart is also a brand of PJP referred to as IndiMark in some applications (Brog and Schadler, 1999 and see case studies included here).  In Australia Travel Smart is also an umbrella for a variety of linked travel awareness activities (e.g., PJP, school travel activities such as walking buses, and company travel plans). In the UK Smarter Choices is the umbrella term for such travel awareness activities.

Personalised journey planning is also referred to as personalised travel planning or individualised marketing.

The process of changing behaviour

There are a number of steps on the way to changing behaviour (see the Transtheoretical Model also known as the Stages of Change Model - Prochaska & Di Clemente, 1992) that can be summed up as making individuals aware of the need to change, making individuals aware of the options available to them, facilitating change, and encouraging the maintenance of new behaviours. The TAPESTRY (TAPESTRY, 2003) project expanded these stages to seven more specific stages for the purposes of changing travel behaviour:

1. Awareness of problem,
2. Accepting responsibility,
3. Perceptions of options,
4. Evaluation of options,
5. Making a choice,
6. Experimental behaviour,
7. Habitual behaviour.

It should also be noted that having taken on board the need to change and/or actually made a change, habitual drivers can relapse into old ways of thinking and behaving. Relapse may occur if individuals do not feel supported, they feel they are making changes in isolation and therefore making no difference to the problem, the alternatives they are using do not adequately meet their needs or involve too much effort (in terms of planning, physical effort, or stress of using the alternative mode), or they perceive that the need to use cars less has receded. Such relapses may not be permanent. Individuals can cycle through the stages of change several times (Sutton, 2001). The change can be longer lasting each time until it becomes habitual.

Mechanisms that can be useful at each stage and how PJP can be used to implement them are outlined in mechanisms for change.

Mechanisms for Change

Stage of Change	Mechanisms
Problem awareness and accepting responsibility	Blanket advertising re negative impacts of car use. More targeted communications, e.g., leafleting or adverts targeting a specific audience, which should make the link between individual behaviour and negative consequences of car driving. Community and media discussion can also have an influence. PJP projects can be used as a vehicle to provide targeted information, as well as a basis for running community events and discussions.
Perception and evaluation of options (making individuals aware of alternatives, and selling them)	More targeted advertising of alternatives available to make individuals aware of these. Communications need to be positive about alternatives, and position them as positive in comparison with other options, including the car. This might include an advertising campaign for walking, or promoting bus services along a corridor. New alternatives, incentives and/or disincentives can be introduced and advertised at this stage. PJP provides information on alternatives appropriate to an individual’s specific journeys, and often includes incentives such as free trial public transport tickets or bicycle hire. PJP can be implemented in conjunction with new or improved walking, cycling or public transport facilities and services.
Making a choice and experimental behaviour (facilitating change)	Highly targeted communications are appropriate at this stage, ideally at the individual level. PJP is highly relevant as it can include home visits or telephone calls to discuss individuals’ travel needs and provide detailed information on alternatives to the car for journeys people are making. This supports making a choice and trying out new travel behaviours, e.g., catching the bus or cycling to and from work. It would be appropriate to combine this stage of PJP with the implementation of new alternatives, incentives and/or disincentives if they have not already been introduced.
Habitual behaviour (maintenance)	To reinforce experimental behaviours and make them habitual, communications should be targeted at those who have made changes, and should ideally address individuals and the specific changes they made. Letters of encouragement and reminders about changes people said they would try; progress reports to show how much difference individuals have made, what changes others have made, and progress in terms of improvements resulting from reduced car use across a community, and rewards and further incentives are ideal at this stage. PJP is an ideal mechanism through which to provide such support since it can build on the one to one communications in the previous stage.

The initial awareness raising, and assessment of alternatives stages are unlikely to result in substantial change in levels of car use, although one or two innovative and/or already environmentally conscious individuals may change at the initial stages. Anable (2005) was able to identify six clear market segments for travel behaviour change amongst a sample of travellers making leisure trips. These market segments were thought to be applicable to other journey purposes (see Anable (2005) market segmentation of “day trippers”). “Car-less crusaders” (4% of the cohort) are perhaps most likely to change in the early stages of an awareness and behaviour change campaign. To achieve more substantial change, more targeted marketing is needed to help those with no concept of using alternatives to the car make changes in their travel habits. An effective way of doing this is to identify individuals who are willing to make changes to their travel habits, find out what journeys they make and provide information on specific alternatives available for those journeys. This process is known as PJP to reduce car use. When providing information on specific alternatives, PJP can promote other policy instruments, as well as providing standard information on walking, cycling or public transport as appropriate. Examples of policy instruments that can be promoted through PJP include ride sharing schemes or the introduction of a guided bus. PJP can also suggest, trip chaining, carrying out multiple activities in one location, and telecommunications (e.g., telecommuting or Internet shopping) to reduce car mileage.

Anable (2005) market segmentation of day trippers:

Non-car owners Car-less crusaders (4% of cohort) Reluctant riders (3% of cohort) Car owners Malcontented motorists (30% of cohort) Complacent car addicts (26% of cohort) Die hard drivers (19% of cohort) Aspiring environmentalists (18% of cohort)

PJP to reduce car use can be the sole constituent of a local authority travel awareness campaign, or it can be combined with other measures. Darlington, one of the UK Department for Transport’s Sustainable Travel Demonstration Towns, implemented a range of sustainable travel measures, including PJP, as a coherent package over five years. By 2004/2005 the following measures had been implemented: a baseline survey for monitoring purposes, school travel plans to promote walking and cycling, workplace travel plans, a ride sharing scheme, ‘A Town on the Move’ awareness campaign, community street audits, cycle network audits, a town wide PJP programme, location specific bus information, and a programme of promotional events (Darlington Borough Council, 2005).

Technology

A PJP project is not dependent on technology. However, technology can aid the collection and processing of an individual’s travel data. Travel diaries are normally used to collect data on individuals’ journeys. In most examples, these are paper diaries, but it would be possible to use laptops, PDAs or the Internet. It may also be possible to use global satellite positioning (GPS), but so far as the author is aware, there are no examples of this in the PJP context. Once data is collected, it is necessary to identify car journeys an individual is making that it would be possible to undertake by other modes, or in different ways, e.g.., trip chaining or trip substitution. It is then necessary to check personal details such as mobility problems to ensure the recommended alternative is suitable and find any appropriate public transport journey itineraries. For monitoring purposes, it is necessary to record details (mode, distance and number of journeys) of journeys an individual is making before and after recommendations are made, for comparison. Travel diaries are again often used to collect after data. Clearly all of this is possible by hand, but it is extremely time consuming. Thus, use of a programmable database is recommended. GIS mapping functionality may also be informative to identify routes between origins and destinations, and feasible modes, as well as presenting information to participants.

Why introduce personalised journey planning (PJP)?

Reducing car use is a common transport strategy in light of the high levels of car dependence in developed countries and the negative impacts of car use. These include atmospheric and noise pollution, severance, land take and congestion, which can have negative economic impacts, especially with regard to CO2 emissions and climate change. There are a variety of carrot and stick measures which can be used to reduce car use, including low car housing, travel information centres, bus service management, cycle routes (these are all pull measures), urban road charging, parking controls and traffic management and restraint (these are all push measures).Measures designed to push drivers out of their cars are often very unpopular amongst the general public and hence, politicians as well. Travel information centres, bus service management and provision of cycle routes pull drivers out of cars. However, they are not always successful. Facilities are obviously improved for existing users, which is one objective of such policies, but modal shift is often small because car drivers are unaware that new facilities exist and/or cannot see how they could fulfil their travel obligations by modes other than the car. Where introduction of new facilities is particularly high profile, i.e. it is given a high media presence in the catchment area through advertising to the relevant market sectors, there can be noticeable modal shift, but the level of transfer could still be increased by providing journey specific information to individuals through PJP.

Further to this, use of PJP can make reducing car use more acceptable to the general public. Personalised journey planning is a pull measure specifically adapted for each individual. Thus, participants are more likely to feel that the programme is relevant to them, not a facility provided for users of alternative modes, and thus respond positively.

Demand impacts

The impacts resulting from PJP are on the demand for car travel and demand for alternatives. Most often that is an increase in the demand for public transport, walking and cycling, but it could also include increased use of ride sharing, car clubs, telecommuting and shopping from home. This will therefore contribute to transport policy objectives seeking to reduce congestion and the associated negative impacts.

Responses and situations
Response	Impact on vehicle kilometres	Expected in situations
		Personalised journey planning does not seek to change departure time, although it may be a secondary consequence of modal shift.
		Personalised journey planning does not seek to change routes, although it may be a secondary consequence of modal shift.
		Where the personalised journey planning seeks to encourage greater use of more local facilities. Greater use of local facilities may also be a secondary consequence of modal shift.
		Where this is the chosen means of reducing car use. Journey purposes can be linked into a trip chain, suppressed or substituted with teleshopping/working etc.
		Where participants respond to information provided regarding alternatives with behaviour change in the form of modal shift.
		Where modal shift and/or reduction in number of journeys is a sufficiently high proportion of car journeys made to make owning a car (or a second household car) uneconomic.
		Personalised journey planning does not promote moving house, but in the long term committed individuals may move closer to frequent destinations or corridors where it is possible to walk, cycle or use public transport. Most likely when moving house for other reasons.

	= Weakest possible response		= Strongest possible positive response
	= Weakest possible negative response		= Strongest possible negative response
	= No response

Short and long run demand responses

Where a PJP campaign is successful in creating new travel habits there is potential for noticeable long term demand responses. Firstly, individual change is likely to be cumulative. As the individual becomes familiar with using alternatives to the car, it becomes easier, and therefore feasible for a wider range of journeys. Additionally, as more people are seen to make these changes, others are likely to follow.

However, it should be noted that change in travel behaviour is unlikely if it is not economically viable for the individual concerned. Particularly committed individuals could divert funds from other expenditure, but this is rare. Thus, if there are no financial incentives to change, such a response is unlikely. Such incentives do not necessarily require local authority expenditure; it can merely be a case of highlighting the savings to be made from reducing mileage and thus, fuel consumption, for example. However, as choice of personal transport often has consequences for an individual’s image, other members of their household, and sometimes employers, the decisions may not be made on a purely objective economic basis. Maintaining a certain image associated with car use, escorting other members of the household or family, and conforming to established work patterns may be considered to justify continued use of a car, even where total travel expenditure is greater than it would be if car use were reduced.

The demand responses in terms of reducing number of journeys and changing mode are dependent on the options available to individuals. For example, working from home would not be an option for an individual working for an employer who does not allow such practices and ride sharing is unlikely to be a response where there is no ride sharing scheme. The table here is completed on the basis of a homogeneous environment where all options being available.

Demand responses
Response	-	1st year	2-4 years	5 years	10+ years
	-
	-
	Change job location
-	Shop elsewhere
	Compress working week
-	Trip chain
-	Work from home
-	Shop from home
	Ride share
-	Public transport
-	Walk/cycle
	-
	-

	= Weakest possible response		= Strongest possible positive response
	= Weakest possible negative response		= Strongest possible negative response
	= No response

Level of response

The impacts on price elasticity of demand caused by the implementation of a PJP campaign will vary according to the success of the programme and the context in which it is implemented. A programme that promotes all alternatives available equally will have different impacts from one which is targeted at increasing cycling rates. Thus, the type of trip, type of traveller, price elasticity of related goods and services and whether the elasticity accounts for short term or long term demand responses are important influential factors in the calculation and interpretation.

Supply impacts

There will not be an increase in the supply of road space. Where a PJP campaign works with existing alternatives to car use, there will be no change in the nature of supply, merely a change in the way the existing supply is used. Where a PJP campaign accompanies infrastructure measures such as the introduction of bus rapid transit, the supply impacts will be greater.

Financing requirements

The cost of a PJP campaign can be significant, especially where a local authority buys in services from an outside organisation. The cost is a factor of the number of individuals targeted, the amount of publicity material and information leaflets involved, the design of the survey (nature of travel diaries used, and possibly questionnaires) the level of technology used to process data and how much needs to be bought in specifically for the project. High levels of technology utilisation may not be more expensive than employing staff to process diaries by hand. Despite potentially high costs, the PJP aspect of the Travel Smart programme in Perth, Western Australia has been shown to be cost effective.

The following figures compare the total cost of the Travel Smart programme in South Perth with that of introducing a new bus service. The whole programme includes a PJP campaign, as well as wider publicity and initiatives. The public transport figures are derived from the first four months of monitoring of the Transperth (public transport) electronic ticketing system undertaken throughout the large scale roll out of Travel Smart between February and June 2000.

	New Bus Service	South Perth Travel Smart
Capital Cost	$1.43 m	$1.28 m
Gross Operating Cost	$3.2 m	$0.03 m
Patronage	870,000 pa	302,400 pa
Revenue	$1.84 m pa	$0.314 m pa
Return	$0.55	$1.99

Source: Department of Transport Western Australia (DTWA), (August 2000) Travel Smart, A Cost Effective Contribution to Transport Infrastructure.

The return is based on a 10 year time span with the following assumptions:

• No decline in the effect of Travel Smart®
  
• Patronage, costs and revenue for the new bus service remain constant (DTWA, 2000).

It is noted that the bus services in "South Perth have sufficient capacity to absorb the expected increase in patronage" (DTWA, 2000).

DTWA (2000) note that the point of the comparison “is not to say that this new bus service should not be implemented but that Travel Smart is an effective programme that should be included in public transport capital works assessments.”

Assessment of recent UK Sustainable Travel Demonstration Towns indicates a cost in the most expensive exampleof £16.13 per head for the Smarter Choices measures implemented (DfT, 2009) – these included PJP. Where a Smarter Choices scheme is a rolling programme over a number of years “it is assumed that the costs of the scheme increase by 2.0% per annum” (DfT, 2009). This is calculated on the basis of urban population forecasts, and assumes Smarter Choices measures involve the whole urban population of a town or city.

Expected impact on key policy objectives

Urban road charging encourages people to change their car travel behaviour. It firstly encourages them to change the timing and location of their car journeys from congested and environmentally sensitive times and places, e.g. peak hours in city centres, to less congested, less sensitive times and places. Secondly, it encourages them to reduce their overall level of car-use, either by switching from the car to other transport modes or by reducing the amount they travel. Therefore, its main contributions will be to objectives concerned with efficiency and environment. It will also generate substantial revenue, which can potentially be used to finance other elements of a transport strategy (May et al, 2005).

Contribution to objectives
Objective	Scale of contribution	Comment
		By reducing delays and improving reliability. Contribution may be greater where the campaign is accompanied by infrastructure and/or service alterations which make using alternatives to the car more attractive.
		By reducing community severance.
		By reducing air and noise pollution, and pressures on green space and environmentally sensitive sites
		PJP alone will do little as it targets car drivers. In the short term where PJP is accompanied by improved/new provision for alternatives low income car users may benefit if they no longer need a car. In the very long term social pressure to own a car may decrease if the image associated with using alternatives and the practicalities of doing so improve.
		By reducing traffic levels.
		By freeing up potentially productive time currently lost in congestion
		The figures above indicate positive economic outcomes locally, but they do not factor in reduced tax revenue from fuel sales

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Expected impact on problems

In as much as the key problems caused by road transport are often the result of excessive car use, a successful PJP campaign has the potential to have significant impacts. However, where reducing car use is perceived by the public as socially unacceptable (or ‘untrendy’), the impacts are likely to be small. As reducing car use becomes more acceptable over time, impacts may increase cumulatively.

Contribution to alleviation of key problems
Problem	Scale of contribution	Comment
Congestion-related delay		Contribution may be greater where the campaign is accompanied by infrastructure and/or service alterations which make using alternatives to the car more attractive.
Congestion-related unreliability		Contribution may be greater where the campaign is accompanied by infrastructure and/or service alterations which make using alternatives to the car more attractive.
Community severence		By reducing traffic volumes
Visual intrusion		By reducing traffic volumes
Lack of amenity		Where increased walking and cycling results from the campaign there may be greater use of local facilities, which will sustain and possibly increase their supply.
Global warming		By reducing traffic-related CO2 emissions
Local air pollution		By reducing emissions of NOx, particulates and other local pollutants
Noise		By reducing traffic volumes
Reduction of green space		By reducing pressure for new road building and city expansion
Damage to environmentally sensitive sites		By reducing traffic volumes
Poor accessibility for those without a car and those with mobility impairments		There is no direct impact, but where increased demand for public transport results from a campaign, quality and volume of supply may increase.
Disproportionate disadvantaging of particular social or geographic groups		PJP targets car drivers, but in the longer term increased demand for alternatives may result in increased supply, which could benefit other social groups.
Number, severity and risk of accidents		By reducing traffic volumes
Suppression of the potential for economic activity in the area		By improving the efficiency of the local road network through reduced congestion, especially where combined with other measures, including those that lock in reduced congestion.

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Expected winners and losers

One would not expect everybody to benefit equally from any transport measures. However, a PJP campaign does not force anybody to change their travel habits, thus there is more potential for winners than losers.

Winners and losers
Group	Winners/Losers	Comment
Large scale freight and commercial traffic		High value journeys - less time spent in congestion the greater the vehicle utilization - relatively small proportion of journey distance in urban conditions.
Small businesses		Where these are local and reduced car use encourages use of local amenities. On a wider scale they are likely to benefit from reduced congestion.
High income car-users		High income associated with high value of time and thus continued car use for high value journeys. These journeys will benefit from reduced congestion.
People with a low income		Where they are able to make fewer car journeys and thus save money.
People with poor access to public transport		Where increased demand for alternatives results in increased quality and volume of supply.
All existing public transport users		Reduced congestion will the reliability of existing public transport. Plus, where increased demand for alternatives results in increased quality and volume of supply.
People living adjacent to the area targeted		They may benefit from reduced congestion and improved or increased public transport supply.
People making high value, important journeys		These journeys may still be made as solo drivers, but reduced congestion will result in valuable time savings.
The average car user		Where they are able to travel more efficiently, saving time and money. Plus getting more exercise through walking and cycling, and experiencing the community benefits which accrue from these modes.

	= 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 no legal restrictions.
Finance		Support for awareness campaigns is relatively inexpensive, but does need to be sustained.
Governance		The only restrictions relate to the need for public transport operators to contribute information.
Political acceptability		There may be resistance to using measures which have no immediate impact on the ground.
Public and stakeholder acceptability		The main barrier is public resistance to change in response to such campaigns.
Technical feasibility		Some requirements arise for data collation on travel patterns and opportunities.

= Minimal barrier

= Most significant barrier

Case sudy A: Travel Blending®

Context

Travel Blending® is a personalised journey planning (PJP) programme implemented by Steer Davies Gleave consultancy. Travel Blending® has been implemented internationally, including Sydney and Adelaide in Australia, Leeds and Nottingham in the UK and San Diego in Chile. Australian examples are presented here.

“The Travel Blending® Program was initially developed as part of a major public initiative called ‘Clean Air 2000’ which aims to reduce pollution caused by car travel in Sydney prior to the year 2000 Olympics. …After the pilot study had been completed in Sydney, the Department of Transport in South Australia (TransportSA) initiated a trial which took place in Adelaide” (Rose and Ampt, 2001). Travel Blending® in Adelaide is known as ‘TravelSmart’ Adelaide. As a PJP programme, Travel Blending® emphasises the “How to rather than … [the] Should do” (Rose and Ampt, 2001).

Travel Blending® consists of two one week travel diaries completed by all members of participating households. Individual participants were recruited through the workplace; the individual then co-opted the rest of their household. The first travel diary allowed:

• the amount of travel to be quantified,
• the pollution generated to be calculated,
• consideration of household interactions which result in travel,
• generation of targeted suggestions about how to reduce car use.

The second diary:

• identified change in travel behaviour,
• facilitated feedback to participants,
• monitored the impact of Travel Blending®.

Travel diaries recorded “all travel outside the home with details obtained of destination, place and purpose, start and end time of each trip, travel mode and for car driver trips, the odometer reading at the start and end of the trip” (Rose and Ampt, 2001). The diaries covered seven days as week day and weekend journeys can be very different; people may be more able to travel blend at the weekend than during the week, or vice versa. It was found that people did complete the full seven day diaries; possibly because they included a built in reminder system (Rose and Ampt, 2001).

Travel Blending® does not merely promote replacing motor vehicle travel with other modes or means of communication, it encourages “thinking about activities and travel in advance (i.e. in what order can activities be done, who should do them, where should they be done etc.), and then blending modes (i.e. sometimes car, sometimes walk, sometimes public transport etc.), or blending activities (i.e. doing as many things as possible in the same place, or on the same journey [i.e. trip chaining]), or finally blending over time (i.e. making small sustainable changes over time on a weekly or fortnightly basis)” (Rose and Ampt, 2001). The key message is “to blend travel choices in a manageable but sustainable way to reduce motor vehicle use … [whilst] allowing people to participate in the same activities that they currently undertake” (Rose and Ampt, 2001).

Further information regarding the detailed design of Travel Blending® can be found in Rose and Ampt (2001).

Impacts on demand

Rose and Ampt (2001) report details of the Sydney pilot study in qualitative terms due to the small sample size, and the Adelaide study in quantitative terms.

Sydney

• One individual who previously drove to the [train] station every day, started to catch the bus one day per week. This represented a 12 km reduction in distance travelled per week, and two fewer cold starts. The individual also reported that the change was sustainable in the long term.
• One individual who exhibited no change between diary one and diary two organised a group of friends travelling to the countryside to travel in two vehicles instead of three. This saved 600km of motor vehicle travel.
• One individual increased walking and ride sharing trips.

The above households changed their travel patterns as a result of Travel Blending®. Two others made fairly dramatic changes because one of their vehicles was off the road. Other participants had plans to change in the longer term, including:

• Occasionally cycling to a friend’s instead of being escorted by car, by her mother,
• Organising a car pool for children’s Saturday morning sport,
• Travelling to work by bus one day per week,
• Considering access to public transport when moving house in the near future, so that the household can ‘survive’ with one rather than two cars.

Adelaide

The Table A1 below indicates the changes in car use as a result of Travel Blending®. The results of a Z test to test the hypothesis that the means are equal for diary one and diary two, against the alternative hypothesis that the mean for diary two is less than that for diary one are also included.

Table A1  Travel Behaviour Change Amongst Adelaide Travel Blending® Participants

Travel Behaviour Change Amongst Adelaide Travel Blending® Participants
	Diary 1	Diary 2	Change	Z test result
Car driver trips/person	14	10.80	-3.2	-2.17*
Car driver kilometres/person	146	114.8	-31.2	-1.69*
Total hours in car/person	7.2	5.3	-1.9	-3.18*

*Significant at a 5% significance level, critical Z value = -1.64.
Source: Rose and Ampt (2001)

Rose and Ampt (2001) produced aggregate results for the population as a whole (see Table A2) by including non-participants in the analysis. This was done by assuming “that each person who refused to participate in rounds one and two travelled in the same way as the average for all persons in diary one (i.e. before they had received feedback) in both rounds, and that any person who participated in dairy one and not diary two was assumed to have made no change between the two diaries” (Rose and Ampt, 2001).

Table A2  Estimates of Aggregate Reductions in Car Use

Estimates of Aggregate Reductions in Car Use
	Diary 1	Diary 2	Change	%Change
Participants
Car driver trips	2572	1988	-584	-22.7
Car driver kilometres	26856	21131	-5725	-21.3
Total hours in car	1325	977	348	-26.2
Total people approached
Car driver trips	3089	2669	-420	-13.6
Car driver kilometres	32251	28534	-3717	-11.2
Total hours in car	1603	1310	-293	-19.3

Source: Rose and Ampt (2001)

Impacts on supply

Travel Blending® has had no impacts on either the supply of road space or public transport infrastructure.

Other impacts

Changes in participants' opinions and attitudes are reported for the Sydney study (Rose and Ampt, 2001). These are:

• "Unanimous agreement that the Travel Blending® Program resulted in increased awareness of the use of the motor vehicle and its associated environmental consequences for people of all ages. The tailored feedback was given as the major reason for this."
  
• "One individual who did not reduce her car travel … said that "I started valuing my trips in the car". This respondent came to appreciate the role the car played "as an important tool to communicate" and for the access it provided for speciality shopping and leisure activities."
  
• Another "participant said "I used to consider convenience and cost when making travel decisions now I consider three things: convenience, cost and environment."

Contribution to objectives
Objective	Scale of contribution	Comment
		The reductions in car use will have contributed to an efficiency improvement.
		The reductions in car use will have contributed to a liveability improvement.
		The reductions in car use will have contributed to a reduction in environmental impacts.
		There was no discernable impact on equity and social inclusion.
		There was no discernable impact on safety.
		Efficiency improvements will support economic growth.
		The cost of implementing Travel Blending® was not published, but it is thought to be substantial.

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Case Study B: Travel Smart®

Context

Travel Smart® is a registered trademark of the Western Australian Department of Transport (TransportWA), used as a branding for voluntary travel behaviour change programmes. Travel Smart® informs and motivates people to use alternative modes to the car, including ride sharing and alternatives to travel (e.g. teleaccess). Like Travel Blending®, Travel Smart® does not constrain mobility. Travel Smart® as a brand encompasses a variety of attitudinal and behaviour change measures, personalised journey planning (PJP).

The Travel Smart® PJP was developed by SocialData under the name Indimark®. Travel Smart® PJP starts by identifying individuals who are prepared to think about reducing their car use through telephone surveys. Those completely resistant to the idea do not receive any further communication. Those who already use alternatives a lot receive some form of reward, which is found to increase use of alternative modes further. Those who are prepared to think about reducing their car use and participate provide information about their journeys and receive targeted suggestions to reduce their car use. This is done through the post or a home visit where appropriate (Brög and Schädler, 1999).

A pilot study was undertaken in South Perth in 1997, with approximately 400 randomly selected households. The pilot comprised a benchmark survey in August 1997, intervention in September/October 1997 and an evaluation survey in November 1997. A second and third evaluation survey was undertaken in September 1998 and February 2000 respectively.

A large scale application also occurred between February and June 2000, but that is not reported in detail here. Monitoring of the large scale application was also undertaken using the electronic bus ticketing system in the area subject to PJP.

Impacts on demand

The percentage changes in travel behaviour resulting from the pilot study are presented in Table B1.

Table B1 Percentages Travel Behaviour Change from Travel Smart®

Percentages Travel Behaviour Change from Travel Smart® Pilot
	November 1997	September 1998	February 2000
Car as driver trips	-10%	-11%	-10%
Public transport trips	21%	No change	No change
Cycle trips	91%	No change	No change
Walking trips	16%	24%	16%
Car km travelled	-14%	-17%	-*

Source: Department of Transport Western Australia (2000). 
*No figure avilable.

The fare box monitoring undertaken with the large scale application revealed a 27% increase in bus patronage between the period March to June 1999 and the same period in 2000. Over the wider network, there was a 1.5% increase in patronage, thus the net increase of 25% was attributed to Travel Smart® PJP.

Impacts on supply

The implementation of PJP through Travel Smart® did not affect the supply of road space or public transport infrastructure. It is possible that supply of public transport services may increase in response to demand.

Other impacts

The Travel Smart® analysis notes a number of cross cutting benefits. Many of these fall within the contribution to objectives below, but additionally, there are preventative health outcome due to increased levels of physical activity.

Contribution to objectives
Objective	Scale of Contribution	Comment
		The reductions in car use will have contributed to an efficiency improvement.
		The reductions in car use will have contributed to a liveability improvement.
		The reductions in car use will have contributed to a reduction in environmental impacts.
		Should the increased demand for public transport result in increased supply there will be a positive impact on equity and social inclusion. This will be greater if the increased supply is through new routes.
		There was no discernable impact on safety.
		Efficiency improvements will support economic growth.
		The cost of implementing Travel Smart® is not published, but it is thought to be substantial.

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Case Study C: Indimark® in Germany

Context

Brög and Schädler (1999) report Indimark® in Europe, which takes the same form as that developed for Travel Smart® in Australia, described above. Following the Australian success, the ‘Switching to Public Transport’ demonstration project was initiated in Europe (in Germany) by the International Association of Public Transport (UITP). Indimark® was in this case applied with the specific aim of increasing public transport patronage, and has since been adopted by a number of operators as part of their marketing strategy. Many applications in Europe have included upwards of 2000 participants, one the largest being in Leipzig, where there were 75,452 participants.

Impact on demand

Like the Travel Smart® results, those in Germany (see Table C1) indicate that changes are sustained over two years. Even where there is a slight reversal in changes in travel behaviour, there is still less car use and more public transport use two years on than before intervention.

Table C1  Changes in modal share following introduction of Indimark®

	München			Bremen			Köln-Mülheim			Wiesbaden			Nürnberg			Kassel
	B	A	1yr	B	A	1yr	B	A	1yr	B	A	1yr	B	A	1yr	B	A	1yr
Walk, bicycle	50	48	46	42	41	40	33	31	30	28	27	27	27	29	26	25	23	23
Motorised private transport*	22	19	18	31	30	30	36	34	35	43	41	41	44	38	40	48	44	46
Passenger	6	6	6	9	9	10	11	10	10	12	13	13	15	10	13	19	16	15
Public transport	22	27	30	18	20	20	20	25	25	17	19	19	14	23	21	8	17	16

*includes motorcycles and scooters.
B – before Indimark; A – immediately after Indimark, 1yr – one year after Indimark 
Source: (Brög and Schädler, 1999).

Impact on supply

Again, implementation of PJP does not change the supply of road space or public transport. However, there may be increases in public transport supply resulting from increases in demand, especially since the Indimark® reported here was implemented to increase patronage.

Other impacts

Indimark® resulted in an improved image of public transport amongst the target group. Perceptions also improved amongst a control group, but by a much smaller degree.

Source: (Brög and Schädler, 1999).

Participants who received a 'test ticket' (a free ticket that could be used for trial public transport use) reported improved perceptions of public transport and increased intentions to use public transport. However, a trial of test tickets in one German city, without prior contact and dialogue indicates that experience alone does not change behaviour. The dialogue is essential.

Source: (Brög and Schädler, 1999).

Additionally, in an Austrian application of IndiMark®, one city public transport operator sent out conventional, untargeted information packages to a group, in addition to the Indimark® group. The results suggested that conventional information has little impact on public transport patronage, but that Indimark® does have an impact. [For “follow” read “following” in this diagram.]

*Car driver and motorcycle journeys
Source: (Brög and Schädler, 1999).

Contribution to objectives
Objective	Scale of Contribution	Comment
		The reductions in car use will have contributed to an efficiency improvement.
		The reductions in car use will have contributed to a liveability improvement.
		The reductions in car use will have contributed to a reduction in environmental impacts.
		Should the increased demand for public transport result in increased supply there will be a positive impact on equity and social inclusion. This will be greater if the increased supply is through new routes.
		There was no discernable impact on safety.
		Efficiency improvements will support economic growth.
		The cost of implementing Indimark® is not published, but it is thought to be substantial.

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

For more information see www.brotunnel.no

Case Study D:  TravelSmart in Bristol, UK

The case study reported here is taken from Anable J, Kirkbride A, Sloman L, Newson C, Cairns S and Goodwin P (2004) ‘Smarter Choices Volume 2: Case study reports’, Department for Transport, London.

Context

TravelSmart using the SocialData IndiMark methodology has been implemented in two locations in Bristol, a medium sized city in south west England. The locations were Bishopsworth/Hartcliffe (approximately 5km south of the city centre), and Bishopston (approximately 2.5km north of the city centre). Bishopsworth/Hartcliffe has a high deprivation index, with low car ownership and comparatively high use of public transport. In contrast to this, Bishopston has relatively high levels of car ownership, resulting in a high number of short car trips.

Both applications of TravelSmart involved Bristol City Council, Sustrans and SocialData. For the Bishopsworth/Hartcliffe scheme First Bus also provided information and trial tickets.

TravelSmart (or IndiMark as it is referred to in some parts of Europe) includes a number of distinct phases: “initial contact is made with households which are then segmented into groups according to their use of different transport modes and whether they are interested in making more use of alternative travel modes. Those who would like to use public transport more, or walk or cycle more, are provided with personalised information about transport alternatives. Some of these households receive further support (the “convincing” phase) to encourage walking, cycling or to use public” (Anable et al, 2004).

The initial contact stage in both locations included a target to approach a minimum of 5,000 people in each area. In Bishopsworth/Hartcliffe however, TravelSmart was applied in two rounds, with 2,500 people approached initially, then another 2,500 a year later. This approach was used to allow for “implementation of the 76/77 service showcase bus route, which passes through the area” (Anable et al, 2004). This was done to compare results of TravelSmart without improved public transport with TravelSmart plus improved public transport.

The first round of the Bishopsworth/Hartcliffe scheme started in September/October 2002. 1,192 households (comprising 2,500 individuals) were targeted, of which 1,081 were approached (the rest were uncontactable). 867 households responded, “of which 46% [399 households] expressed an interest in receiving information on alternative travel modes” (Anable et al, 2004). Of these 399 households, 284 received information and further advice/support (52 of whom only received rewards for already using alternatives to the car as much as possible). It is not clear what happened to the other 115 households who had expressed an interest.

At the “convincing” phase a range of incentives were provided to participants including:

• Four week test tickets for First buses in Bristol, and home visits by a First bus driver,
• Discount cards for local cycle shops and advice/training sessions with a qualified cycle trainer (although take up of the later was minimal),
• Discount cards for outdoor shops, walking kits (step-o-meter and local walking group contacts) and advice sessions with a walking expert (although again take up of this later option was low).

Round two of the Bishopsworth/Hartcliffe scheme started in September/October 2003, but response rates were not available to Anable et al at the time of writing.

Costs
The costs for TravelSmart in Bristol are not fully reported, but “the overall budget for the Bishopston campaign…[was] £100,000” (Anable et al, 2004). The costs for Bishopsworth/Hartcliffe are reported to be of a similar order. The Bishopston project contacted 5,364 people resulting in a cost of £18.64 per head (of people approached). However, not all of these 5,364 people will have participated fully in TravelSmart, some will have refused, others will have been using alternatives to the car as much as they felt able already, and just received a reward for doing so.

Impact on demand

Changes in mode choice were monitored through household and individual travel surveys [most likely diaries] sent to a sample of the target group before and after intervention. A control group not contacted as part of the marketing intervention were also surveyed.

Anable et al note that whilst round 1 of the Bishopsworth/Hartcliffe scheme was not affected by the implementation of the 76/77 service showcase bus route, which passes through the area, it was influenced by other wider public transport improvements in the general area that coincided with it.

Results for round 1 of the Bishopsworth/Hartcliffe scheme (see Tables D1 and D2) are reported in Anable et al, 2004.

Table D1  Mode shares before and after round 1 of Bishopsworth/Hartcliffe TravelSmart

	Target group before %	Control group after %	Target group after %
Walking	21	19	21
Bicycle	0	0	0
Public transport	9	11	13
Motorbike	1	1	1
Car passenger	24	23	22
Car driver	45	46	43
TOTAL	100	100	100

Target group received TravelSmart and benefited from public transport improvements.
Control group only benefited from public transport improvements. 

Table D2  Relative change in average number of trips per person per year from round 1 ofBishopsworth/Hartcliffe TravelSmart

	Change in control area	Change in target area	TravelSmart effect
Walking	-13%	-6%	+8%
Bicycle	-	-	-
Public transport	+18%	+46%	+23%
Motorbike	-	-	-
Car passenger	-9%	-12%	-3%
Car driver	+1%	-5%	-5%
TOTAL	-3%	-2%	-2%

The increases in public transport use and reductions in car passenger travel and walking in the control area are thought to be largely the result of public transport improvements. It is thought that the public transport improvements will have influenced the TravelSmart results, particularly the apparent modal shift to public transport apparent in the control group. No evidence is available on the scale of the influence public transport improvements had.

Preliminary results for the Bishopston TravelSmart (see Table D3) are reported in Anable et al (2004) as follows.

Table D3  Bishopston preliminary results

	Modal share
	% of trips per person per year WITHOUT TravelSmart	% of trips per person per year WITH TravelSmart	Relative change
Walking	37	39	+5%
Bicycle	4	6	+33%
Public transport	6	7	+14%
Motorbike	1	0	-100%
Car passenger	15	14	-7%
Car driver	37	34	-9%
TOTAL	100	100	-

Note, relative change figures have been revised.

Anable et al (2004) note that in addition to the public transport improvements that affect both of the TravelSmart areas, a variety of Smarter Choices measures were implemented throughout Bristol, which will have generated a positive synergy with TravelSmart. No evidence on the impact of these Smarter Choices measures is available.

Impact on supply

TravelSmart itself will not have changed supply of road space or any individual modes. However, simultaneous public transport improvements and Smarter Choices measures will have improved the quality of supply of public transport if not the quantity, and will have increased the alternatives to conventional car use available to residents of Bristol.

Other impacts

Increases in walking and cycling resulting from TravelSmart will have positive health benefits for individuals and could if achieved on a large scale and sustained over time result in reduced spending on health services. Given the range of transport improvements being made in Bristol, wider community benefits may also accrue.

Contribution to objectives
Objective	Scale of Contribution	Comment
		The reductions in car use will have contributed to an efficiency improvement.
		The reductions in car use will have contributed to a liveability improvement.
		The reductions in car use will have contributed to a reduction in environmental impacts.
		Should the increased demand for public transport result in increased supply there will be a positive impact on equity and social inclusion. This will be greater if the increased supply is through new routes.
		There was no discernable impact on safety.
		Efficiency improvements will support economic growth.
		The costs are considered to be high when considered across just the small number of people who actually receive help and support through TravelSmart.

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Case Study E:  TravelSmart in Gloucester, UK

The case study reported here is taken from Anable J, Kirkbride A, Sloman L, Newson C, Cairns S and Goodwin P (2004) ‘Smarter Choices Volume 2: Case study reports’, Department for Transport, London.

Context

TravelSmart has been implemented in Quedgley, a suburb four miles south of the centre of Gloucester, in the UK. Quedgley was chosen over other areas of Gloucester as “it has good local facilities (including primary and secondary schools, a library, and a supermarket), and a good bus service into Gloucester city centre (every 15 minutes)” (Anable et al, 2004). Further, the distance from the city centre made this journey a cycleable length. Combined with the fact that Quedgley has higher than average car use and peak hour congestion on main roads, it was felt that there was real potential for modal shift, especially for short journeys. Other factors that favoured Quedgley as an initial trial area in Gloucester were the fact that bus services were not full to capacity as they were in other locations around the city, car use was relatively unconstrained due to proximity to a motorway junction, and lack of on-street parking problems and general congestion made car use easier than other in other areas of the city which did experience these problems. Given the ease of using a car it was felt that if TravelSmart could work in Quedgley, then it could work elsewhere provided local destinations and real alternatives to the car were available.

In Quedgley, TravelSmart was implemented in two phases, a pilot with 515 people (running April 2001 to May 2002), and a large-scale roll out involving 10,000 (representing all 4,631 households in Quedgley). The project was managed by Sustrans, with the work being carried out by SocialData using their IndiMark methodology.

In addition to the local authorities (Gloucestershire County Council and Gloucester City Council) who commissioned the work, Sustrans and SocialData, a number of other organisations were also involved with TravelSmart in Quedgley: Stagecoach and Swanbrook Transport (both public transport operators), Quedgley Parish Council, Vision 21 (the Local Agenda 21 forum), local cycle retailers and outdoor pursuits shops.

Pilot
The marketing team attempted to contact 515 people, successfully contacting 496 (96%) of those. Approaches are household based and include all individuals (including children) in each household. The 496 people were categorised as follows:

• 51 refused to participate due to privacy concerns or for personal reasons,
• “62 ‘R without’ (regularly use environmentally friendly modes and did not require further information),
• 40 ‘R with’ (regularly use environmentally friendly modes and indicated a need for further information),
• 177 ‘I’ (requested further information),
• 166 ‘N’ (not interested in receiving information on, or making greater use of environmentally friendly modes)” (Anable et al, 2004).

These categorisations are the standard groupings allocated in IndiMark/TravelSmart.

Individuals in the ‘R with’ and ‘I’ groups (217 people) received a “Service Sheet” listing information which they could choose to receive, which they were required to return to the marketing team. 187 (80 households) people returned their “Service Sheet”. Information was then hand-delivered to households in personalised packages. Those in the ‘R’ groups (‘R without’ and ‘R with’) received a gift by way of a thank you for already using environmentally friendly modes.

Large-scale roll out
Following the pilot the large-scale roll out attempted to contact 4,631 households starting in July 2003. Initial contact is usually made by telephone, but in this case insufficient households had their telephone number in the public domain. Households not available by telephone were contacted through the post, but relatively few responded to this approach. Those households who did respond were sent a Service Sheet.

The households not contacted by phone or post (approximately three quarters of the 4,631 initially targeted) were then approached by knocking on doors. For these households the initial contact, Service Sheet and information provision stages were combined into one, as households selected the information they would like there and then, and this was provided on the spot from a supply the marketing teams carried with them. “Of those people at home when the call was made, 90% were interested in receiving information materials – a higher take-up rate than normally expected. Once people could see what was available, they were keen to receive information” (Anable et al, 2004).

Ultimately, of the 4,631 households targeted, 271 were found to be uncontactable due to occupants moving away or having deceased, giving a possible 4,360 contacts. Of these, 93% (4,069) were contacted – a contact rate comparable with other TravelSmart applications.

The contacted households fell into the following categories:

• “‘R without’ 3.5%
• ‘R with’ 13.4%
• ‘I’ 45.0%
• ‘N’ 38.2%” (Anable et al, 2004).

In total 2,120 households received information or rewards for already using environmentally friendly modes; 102 (‘R without’) received rewards only. The information requested most often was bus-stop specific timetables (requested by approximately 70% of households). Walking and cycling information was requested by approximately 50% of households. 977 households requested discount cards (it is not clear what these were for, but they were most likely to be for local cycle and outdoor shops selling goods relating to walking and cycling) and/or a home visit to provide personal advice), and 89 received home visits; 56 related to public transport, 20 related to cycling and 13 related to walking.

Costs and funding
Most of the funding for the large-scale roll out came from the county council, Lottery funding and the UK Department for Transport. Smaller contributions also came from Stagecoach, the city council (in kind), and Vision 21.

The budget for the pilot project was £30,000, comprising £12,000 for the marketing campaign and £18,000 for before and after monitoring surveys. This represented a comparatively high £58.25 per person approached (based on the 515 people approached) when compared with the costs of the large-scale roll out, highlighting the economies of scale achieved through larger schemes.  

The budget for the large-scale roll out was £168,600, comprising:

• £37,600 for before and after monitoring and attitudinal surveys,
• £65,000 for the marketing,
• £30,000 for production of materials, gifts and incentives,
• £9,000 for project management,
• £10,000 for production and dissemination of a project report, and
• £17,000 for local authority costs including contractual and legal costs.

This £168,600 did not include the cost of staff time within the local authorities (for the pilot this was estimated to be £3,000). The cost per person approached was £17 (based on all 10,000 targeted).

Sustrans have estimated that a project targeting 30,000 would cost £30 per household, or £13 per person based on an average household size of 2.3 people. These figures cover the costs of marketing, a before and two after surveys, and promotional materials. The figures do not cover the costs of information materials (as existing materials are usually utilised), or test tickets and public transport related home visits, which are normally provided in kind by the public transport operator.

Impact on demand

Data and key pieces of text directly from Anable et al, 2004.

“Evidence of the effect of the pilot project on car use is based on a ‘before’ survey carried out in September 2001 and an ‘after’ survey in January / February 2002. For both before and after monitoring, a control group from another part of Quedgley was surveyed as well as all those people involved in the marketing exercise. The net ‘before’ survey sample was 871 people (a response rate of 66%); and the net ‘after’ survey sample was 624 people (a response rate of 76%)” (Anable et al, 2004). Results from the pilot are presented Table E1.

Table E1  Mode share before and after for target and control groups

TARGET GROUP				CONTROL GROUP
Before %	After %	Relative change		Before %	After %	Relative change
27	30	+10%	Walking	19	19	0%
2	3	+33%	Bicycle	2	1	-100%
1	1	0%	Motorbike	1	1	0%
43	41	-5%	Car as driver	51	52	+2%
23	20	-15%	Car as passenger	22	22	0%
4	5	20%	Public transport	5	5	0%
100	100	-	TOTAL	100	100	-
2.7	2.7	-	Trips per person and day	2.7	2.7	-

Note, relative change statistics computed for KonSULT by ITS.

The data reported in Table E1 has not been adjusted or weighted. Further analysis of the results are reported in Anable et al (2004), including an adjustment of the target group before data to allow for the fact that changes seen in the control group would most likely affect the target group as well. The after data for the target and control groups is also weighted by trip purpose such that distribution of trip purposes is the same in the before and after data. The after target group data is further weighted to correct for the proportion of ‘I’, ‘R’ and ‘N’ respondents, such that it is the same as observed during the marketing campaign. Such analysis of Travel Smart data is standard practice, but in this case, made little difference to the results.

“Car mileage is also reported to have fallen by 9%, from 21 km per person per day to19 km per person per day. Again, this figure is averaged across the entire target population: that is, it represents the behaviour change for both people who responded and those who did not respond, and for those who requested information and materials as well as those who did not.

Changes in car use were seen across all times of day (both peak and off-peak). Much of the increase in bus use was off-peak, when capacity was already available. There was no information about impacts on weekdays as compared to weekends. The number of activities per day remained the same, and so did the number of trips per day. This suggests that people did not respond to the project by trip consolidation (combining different trip purposes into one journey).

Car use was affected for all journey purposes apart from education: that is, car use
went down for work trips; shopping and service trips; leisure trips; and other trips. Although car use did not go down for education trips, use of environmentally friendly modes appeared to increase. There is some evidence of destination switching, with the ‘after’ monitoring showing an increase in the proportion of trips made within Quedgley, from 43% to 45%” (Anable et al, 2004). With regard to education trips, Anable et al (2004) noted that school travel plan activity in Gloucester may already have impacted on mode choice for education trips.

For the large-scale roll out only preliminary results (see Table E2) were available to Anable et al (2004) as follows.

Table E2  Large-scale roll out preliminary results

	Modal share
	% of trips per person per year WITHOUT TravelSmart	% of trips per person per year WITH TravelSmart	Relative change
Walking	22	25	+12%
Bicycle	3	4	+25%
Public transport	5	6	+17%
Motorbike	1	1	0%
Car passenger	20	19	-5%
Car driver	49	45	-9%
TOTAL	100	100

Note, relative change statistics have been revised.

Impact on supply

TravelSmart itself will not have changed supply of road space or any individual modes. However, increased demand for public transport could result in increased supply in the long term.

Other impacts

Increases in walking and cycling resulting from TravelSmart will have positive health benefits for individuals and could if achieved on a large scale and sustained over time result in reduced spending on health services.

Contribution to objectives
Objective	Scale of contribution	Comment
		The reductions in car use will have contributed to an efficiency improvement.
		The reductions in car use will have contributed to a liveability improvement.
		The reductions in car use will have contributed to a reduction in environmental impacts.
		Should the increased demand for public transport result in increased supply there will be a positive impact on equity and social inclusion. This will be greater if the increased supply is through new routes.
		There was no discernable impact on safety.
		Efficiency improvements will support economic growth.
		The costs are considered to be high when considered across just the small number of people who actually receive help and support through TravelSmart.

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Gaps and weaknesses

The primary weakness in the evidence presented stems from PJP being a relatively recent development. Consequently, there is a scarcity of evidence. This is exacerbated by some reporting of PJP lacking transparency and consistency. The UK Department for Transport (DfT, 2009) cite this lack of robust evidence for recent caution in forecasts of the impacts (in terms of carbon emission reductions) that may result from Smarter Choices (which includes PJP).

 

Contribution to objectives and alleviation of problems
Objective	Travel Blending	Travel Smart Australia	Indimark in Germany	TravelSmart Bristol	TravelSmart Gloucester

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

 

Contribution to alleviation of key problems
Objective	Travel Blending	Travel Smart	Indimark	TravelSmart Bristol	TravelSmart Gloucester
Congestion-related delay
Congestion-related unreliability
Community severance
Visual intrusion
Lack of amenity
Global warming
Local air pollution
Noise
Reduction of green space
Damage to environmentally sensitive sites
Poor accessibility for those without a car and those with mobility impairments
Disproportionate disadvantaging of particular social or geographic groups
Number, severity and risk of accidents
Suppression of the potential for economic activity in the area

	= Weakest possible positive contribution		= Strongest possible positive contribution
	= Weakest possible negative contribution		= Strongest possible negative contribution
	= No contribution

Appropriate contexts

The evidence available suggests that personalised journey planning (PJP) may be more appropriate in urban environments. However, it should be noted that it has been successful in Australian cities, which are often less dense than European cities. Thus, PJP should not be immediately discounted for an area that is not densely developed. However, more evidence on impacts in different area types is needed.

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

Adverse side-effects

There are no significant, discernable adverse side effects.

Anable J, 2005, ‘‘Complacent Car Addicts’ or ‘Aspiring Environmentalists’? Identifying
travel behaviour segments using attitude theory,’ Transport Policy, 12(1), pp 65-78.

Anable J, Kirkbride A, Sloman L, Newson C, Cairns S and Goodwin P, 2004, Smarter Choices Changing the Way we Travel. Case Study Report. Department for Transport, London.

Brog W and Schadler M, 1999, “More Passengers, higher profits for public transport – (im)possible expectation!?”, paper presented at 53rd UITP Congress, Toronto, Canada, May 1999.

Darlington Borough Council, 2005, ‘Local Transport Plan Annual Progress Report 2005,’ Darlington Borough Council, Darlington, UK. [Online] http://www.darlington.gov.uk/dar_public/documents/APR2005 final version.pdf(2006).

Department for Transport (DfT), 2009, ‘Impact Assessment of the Carbon Reduction Strategy for Transport, Low Carbon Transport: A Greener Future’. Department for Transport, London. [Online]http://www.dft.gov.uk/pgr/sustainable/carbonreduction/ia.pdf (03/08/09).

Department of Transport Western Australia, 2000, “TravelSmart: A Cost Effective Contribution to Transport Infrastructure”, at http://www.travelsmart.transport.wa.gov.au/ (as viewed on 24/06/02)

Jones, P M et al, 1998, ‘INPHORMM: A review of current practice in Europe’. University of Westminster, London.

Prochaska JO and Di Clemente CC (1992) ‘Progress in Behaviour Modification’, Vol. 28, pp. 184-218 in Sutton S (2001) ‘Back to The Drawing Board? A Review of Applications of The Transtheoretical Model to Substance Use’,Addiction, Vol. 96, pp. 175-786

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Sutton S (2001) ‘Back to The Drawing Board? A Review of Applications of The Transtheoretical Model to Substance Use’, Addiction, Vol. 96, pp. 175-786.

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