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2012

RCGSIDM 11ID60R20 Pranav Mishra

[TRAVEL DEMAND MANAGEMENT] MEASURES, BEHAVIOURAL IMPACT AND USER RESPONSE

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Table of Contents

1. Abstract 2

2. Introduction 3

3. What is TDM 4

4. TDM measures and strategies 5

5. Packages of TDM measures 7

6. Impact of TDM measures on user behavior 11

7. Expected car use response to TDM measures 15

8. Conclusion 18

9. Further research areas 19

10. References 20

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ABSTRACT Traffic congestion and the cost of providing mobility are compelling issues to planners, decision makers and members of both the business community and the general public. Transportation, and the degree of efficiency with which it is accomplished, affects us all. Therefore we are constantly in search of solutions to our transportation problems that will give us not only increased mobility, but also greater economic productivity and a cleaner environment. In light of these concerns, recent years have shown increased interest in measures which affect the demand side of the transportation equation. Because the resources to continue to meet transportation needs through infrastructure expansion are strained, and because travel trends suggest a worsening in the supply/demand balance, it has become necessary to see if increasing the efficiency of the travel demand itself can contribute to our efforts to improve mobility. Travel Demand Management -- or TDM, as it is popularly known -- describes a wide range of actions that are geared toward improving the efficiency of travel demand. Much has been said, studied, and written about this subject. There is much controversy and speculation as to the strength, role, and validity of TDM solutions. This uncertainty has probably led to misunderstandings of the role and potential of TDM, and therefore, a lower yield from TDM approaches than appears to be possible.

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Introduction Transportation system is one of the most critical services that keeps the community running. They allow mobility to peoples and goods from one location to almost any other location in an urban area. In rural areas the connectivity is comparatively lesser. But nonetheless, in an increasingly changing world, they connect us as a city, a region and a nation. The transportation system, however, is becoming a huge concern for its day to day operation. These concerns relate to many different issues: congestion on roads seemingly at all hours of the day and specially during peak hours, degrading environment and poor air quality because of vehicle emissions. The main reason for these concerns lies in the fact that most of the communities have grown tremendously over the past few decades. Increase in the income of urban area population caused a corresponding increase in number of private vehicles using road network. Whereas growth in suburban areas also led to the same as there is no alternative public transport is well established. For years, the solution to the rising levels of congestion was to build new and bigger roads. This encouraged still more growth to occur in these areas of now higher and better accessibility, which once again resulted in increased congestion. Although road improvements will continue to be an important strategy for providing mobility, many communities no longer have the financial resources to build many new roads, would likely face serious environmental problems, and/or encounter strong public opposition. In many of these areas, local officials and employers are turning to a new approach for providing transportation mobility that does not suffer from these problems-- Travel Demand Management (TDM).

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What is travel demand management (TDM)? TDM are the measures which affect the demand side of the transportation equation. Because the resources to meet transportation needs through infrastructure expansion are strained, and because demand-supply balance is going to worsen further, as evident from current travel trends, it has become necessary to find a way of increasing the efficiency of the travel demand to improve mobility into the existing imfrastructure. If applied efficiently and judiciously, these results in more efficient use of existing transportation systems. These programs are designed to maximize the people-moving capability of the transportation system by increasing the number of persons in a vehicle, or by influencing the time of, or need, or cost to travel. To accomplish these types of changes, TDM programs rely on incentives or disincentives to make these shifts in behavior attractive. The primary purpose of TDM is to reduce the number of vehicles using the road system while providing a wide variety of mobility options to those who wish to travel. The application and the implementation of TDM alternatives can occur at different levels under the direction of a variety of groups. One level of application found in many parts of the country is at individual employer sites. If there is a situation or location, where there are many employers grouped together, the employers become the important implementers of the TDM actions. Another level of application is on an area-wide basis where government agencies often direct the initiative. In this type of application, the primary focus of the TDM program is to affect as many travelers as possible within an area-wide travel system. However, experience has shown that the effectiveness of area-wide TDM programs depends greatly on the type and level of participation of employers. Hence, participation of public offices and large employers in effective and successful application of these measures is crucial to meet the ultimate goal of providing improved mobility.

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TDM alternatives & strategies At the level of the employment site, typical TDM alternatives to single occupant vehicles include:

● Carpools and vanpools; ● Public and private transit, including buspools and shuttles; ● Non-motorized travel, including bicycling and walking.

TDM programs can also include alternatives to influence time of travel during a day, or if trip occurs at all. These efforts are usually classified as "alternative work hours", These include:

● Compressed work weeks, in which employees work a full 40-hour work week in fewer than the typical 5 days; and

● Flexible work schedules, which allow employees to shift their work start

and end times (and thus travel times) to less congested times of the day. A special kind of alternative which influences where work occurs and how often a trip is made is telecommuting. Telecommuting programs allow employees to work one or more days at home or at a "satellite work center", which is often closer to their homes and thus does not require a longer trip into the primary work location. At the area-wide level, most of these same types of TDM alternatives are applicable. In addition, public agencies on area-wide concerns can supply:

● Service improvement to transit service that provide savings in cost and travel time.

● Provision of preferential lanes on serving the, which provide time saving to

those using ride-sharing. TDM strategies include:

● Improvements in alternative modes of transportation; ● Financial or time incentives for the use of these alternative modes; ● Information dissemination and marketing activities to promote these

modes; and ● Supporting services that make the use of alternatives more convenient or

that remove psychological impediments to their use. Examples of TDM strategies include:

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● Financial/time incentives, for example preferential parking for ride-sharers,

subsidies for transit riders, and transportation allowances;

● Parking management programs;

● Priority treatment for ride-sharers, for example, provision of preferential entry and exit to parking lots; and

● Information and marketing, such as on-site availability of transit schedules, periodic prize drawings for ride-sharers; and guaranteed ride home programs.

● Application of cost surcharges or subsidy measures designed to make the relative cost of single occupant vehicle use higher than that for high occupancy vehicles.

○ A typical example of area-wide cost surcharges would be parking surcharges placed on parking lots that would provide a differential cost structure for single occupant vehicles versus ridesharers.

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The Packages of TDM Measures To address the problems, a package of TDM measures is required that:

● Influences land use planning policy and practice leading to more sustainable, less car dependent settlement patterns.

● Facilitates drivers who would like to reduce their car use, particularly for trips to

work and to school; and

● Strongly discourages unnecessary car use in certain areas where alternatives are available.

The package of measures also needs to be capable of implementation in the short to medium term. To achieve this, a package of measures is being considered which is best described in three groupings: Measures that can be implemented through the planning system – This include measures from long term spatial planning to development control for individual developments to regional parking restraint measures; Measures to promote travel demand management - incentive measures including car sharing, flexible working, individual marketing and all measures to encourage people to change their travel behavior in favor of less driving. Typically, these measures would be packaged into a Travel Plan for an individual site or group of sites; and Fiscal measures – measures that introduce financial penalties to discourage car use. Managing Travel Demand through the Planning System The measures proposed for implementation through the planning system are diverse and wide ranging. They aim to achieve promote land use and transport integration at the strategic level and local level by:

● Consolidation as far as practicable of population growth in existing built up areas, where accessibility to work, leisure and other destinations by foot, cycle and public transport is generally better;

● Location of major trip-intensive land uses in areas well served by public transport or in areas that will be well served by public transport in future;

● Relating the scale of urban centers to public transport accessibility;

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● Regional maximum parking standards, and the relation of maximum permitted parking provision to the scale and density of new developments to current and future public transport accessibility, and to the scale and proximity of the nearest centre;

● Providing a mix of local services within walking distance of their surrounding neighborhood;

● Designing all new developments with walking, cycling and public transport in mind;

● Relating maximum permitted parking provision for new developments to existing and future public transport accessibility.

In summary, new development should be oriented towards non-car use and should underpin existing centres of activity. In addition, new development that is likely to attract a large number of people should be highly accessible by public transport, cycle and on foot. Measures to Promote Travel Demand Management The application of incentives, marketing initiatives or other practical measures to promote travel demand management has been considered in terms of their potential to reduce car use for journeys to work and education. The measures focus on the workplace, schools, information and technology (IT) applications and the possible role of marketing. Potential components of workplace travel plans, or Mobility Management Plans, may include:

● Establishing databases to assist ridesharing; ● Developing car pooling schemes; ● Providing feeder services to nearby rail or bus services; ● Putting in place on-site measures to make cycling and walking safer and more

attractive, e.g. footpaths, cycle lanes, crossings, secure cycle parking; ● Providing incentives to use non-car modes; ● Introducing staggered or flexible working hours so that employees can avoid

travel in the peak hour; ● Allowing compressed working weeks so that employees work a four day week, or

nine day fortnight, but a longer day; ● Promotion of working at home or working at another site to employers and

assistance or technical support with implementation; ● Reducing the amount of car travel undertaken for work purposes by increasing

the use of telecommunications; ● Introducing travel allowances and reimbursements that encourage non-car travel

as a replacement for the current arrangements in some organizations which act

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as a financial incentive to unnecessary use of cars for commuting and business trips; and

● Restricting parking, e.g. giving priority for parking to ride sharers or individuals with certain needs - many successful travel plans are driven by a shortage of on-site parking.

In the longer term, employers’ recruitment policies can also be included in the workplace travel plan. For example, employers can target employment in local areas, particularly those served by public transport. Employees can also be recruited with the understanding that free parking is not provided. Additionally, a long term workplace travel plan can ensure that any future relocation of the workplace is to a site that is accessible by non-car modes. School travel plans are designed to overcome the barriers for pupils to walk, cycle or take public transport to school. The basic aim of school travel plans is to arrest the rapid growth in travel to school by car. School travel plans may include some or all of the following measures:

● Working with teachers, pupils and families to address perceptions, fears and practical difficulties in overcoming reliance on the car and agreeing a school policy to actively promote sustainable school travel;

● A toolkit of practical measures including walking, cycling, training, encouraging bus use, car lift sharing, incentive schemes, curriculum based promotion and managing parking and drop off; and

● Putting in place infrastructure to support the school travel plan and make the route to school safer to walk or cycle and creating a pupil centred front of school environment.

Information technology can be used to alter the ways in which people fulfil their work, services and shopping, rather than changing the mode by which people travel. This is referred to as “virtual mobility”, a term that focuses on how activities can be undertaken without being dependent on physical mobility. The following possible measures are recommended to promote virtual mobility as an alternative to physical mobility. They require working in partnership with other agencies and could not be promoted purely as travel demand management measures.

● Awareness campaigns both for organisations and for the wider public about the possibilities for reducing travel through virtual mobility;

● E-work pilots and programmes, promoting e-work amongst local organisations, including public sector organisations,

● Telework centres - developing “telework centres” as have been developed in and around some US cities;

● E-commerce - promoting online shopping/home delivery amongst local firms and consumers;

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● E-services – continuing to promote the use of online services – government and local authority services, online learning etc and;

Fiscal Measures The two fiscal measures under consideration are a charge on free workplace parking and congestion charging. Congestion Charging All vehicles moving in the charging zone during the hours of operation would need to purchase a licence, which would allow unlimited trips during that period. The charge would not apply at weekends and on bank holidays. A strong preference for morning peak only operation (7am to 10am), so that shoppers and other visitors arriving late morning onwards would not have to pay the charge. Charges on Free Workplace Parking A charge on free workplace parking is considered to be a measure that would be effective, addressing the rapid growth in demand even in non-central areas. The charge could be implemented either by a workplace parking levy or “benefit in kind” taxation policy. With a levy, the employer would pay in the first place and then choose whether or not to pass onto the employee. With a taxation policy, the parking space would be declared by the employer and/or employee as a benefit in kind and would be paid for by the employee. Other Fiscal Measures Other fiscal measures may include an increase in fuel duty, tolls on the regional road user and a road user charge for inbound traffic. We consider all of these options should remain under consideration for the longer term when congestion is likely to be more widespread, or public transport is improved, or additional technological options become available.

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Impact of TDM measures on user behavior A TDM measure or a group of TDM measures, when enforced upon the road user, it impacts the normal behaviour of the user. This change in the travel behaviour of the user, that is caused by the different TDM policies aimed at reducing car use, is analysed using behavioural theories. It is important to understand how TDM policies affects peoples travel options with respect to cost, time and convenience, before finding out how users react to these changes. First of all an initial framework is prepared with aim of understanding if TDM measures will affect car use or not? and if it does, how? In the conceptual framework, the TDM measures are assumed to affect trip chain attributes. These attribute changes are proposed to both directly affect people’s trvel choice and indirectly through people setting goals of adjusting to attribute changes. The achievement of such goals is influenced by a variety of relatively static factors. In the framework, travel options are grouped as attributes of trip chain that causes the trip. These attributes are the basic parameters that initiate the trip. The researchers have formed a group of attributes based on the intuition, however, they emphasized on finding out the principles for how trip chains are conceptualised by users. A TDM policy or group of TDM policies are expected to influence these trip chain attributes of target car users. Besides, users others than target users are also likely to respond to the TDM measures and this in turn may change the travel options of the target users, in addition to the effect of TDM measures. In the next step of the framework, it is conceptualised that choice that user makes for travel options have two class of determinants: a group of travel choice formed by the user, and; goal and implementation intention that user form in response to the cost, time and convenience change in the current travel due to TDM measures. This goal setting may also be the result of public information regarding adverse and beneficial effects of TDM. These goals such as reduced car use, reduced travel cost, increased safety etc. and the implementation intention are also influenced by several static factors such as income, family structure, travel pattern, attitude etc. The inplementation intention consist of plan for how to achieve the goals which are set. While making plans user considers all the wide range of possible choices ( car-pooling, telecommuting, staying at home) and also long term strategic changes such as shifting the residence, workplace or selling a car etc. It is expected that among choices, user will start with least costly alternative, and after evaluating these used alternatives, may opt for other costlier ones. For goal setting, it is assumed that men strives to satisfy their needs and desires and they set these needs and desire as their goals. Goals have two primary attributes:

● Content: It has four parts; ○ Difficulty - It refers to the skill required to achieve the goal. ○ Specificity - Whether goal is quantitative aur not.

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○ Complexity - Number of different outcomes ○ Conflict - The degree to which attainment of one goal inhibits the

achievement of another goal. ● Intensity: It is the commitment that user shows to attain the goal. The importance

that user gives to achievement of goal. The process that user employs to acieve the goal.

Figure 1: Proposed conceptual framework

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A relationship between difficulty of goal and performance to achieve the goal has been established as - a difficult and specific goal leads to a better performance than setting the goal which is easier to attain. If user receives feedback of his/her performance, it further boosts his/her motivation to perform better. It is also established that if the goal is not specific, i.e. multiple, distant and too high to achieve, then user may not give enough input for attainment of goal as would have been otherwise. and user may shift his attention to other easily attainable and more productive goal. Over a time period, people perceives a present situation and compare it to his goal. The goal is usually an ideal image that user wants to gain. And if there is any discrepancy between the two, i.e. present state and goal, user starts attempt to reduce the difference. For example, a user sets his goal to be ideal member of his society. For this he would like to be concerned about the problems of their society. They may find environments concern, or road congestion, or safety as the most critical issue. so to be good and valuable member of his society, he decides to reduce his car use, so as to reduce his carbon footprint and help in reducing congestion. At this level, when a person is motivated to reduce car use, the policy makers should implement pull measures to provide alternatives to the car user. And then user may decide upon the alternative measures to be taken such as walking/cycling or public transport. This hypothesized condition may not be always true as some user may find punctuality to be the most critical issue for becoming the valuable member of the society. This perception may lead to increase of car use instead of decreasing, for the same goal. Operational choice - At this stage, say user has decided and now he must change his mode of travel and reduce the car use. He will first look for the alternatives that will bring least changes to his schedules, i.e. maintaining the status quo, and then looking for the cheapest alternative. A further step would be to combine and reschedule the activities so that they are performed at the same time or in sequence. If an activity schedule cannot be maintained, then eliminating or substituting the activity also becomes a option. Though not all activities are possible to be eliminated, this practice can be used mostly for leisure activities like shopping, entertainment etc. Situational factors – TDM measures are assumed to mainly affect travel choice by influencing trip chain attributes and goals, whereas situational factors influences travel choice through disturbances. These disturbances should be sufficiently important to create deviations from desired goal. The environment consists of myriad of disturbances that effects the decision of user in unpredictable way. For example, a man has to go to work. In normal condition he may walk or cycle. Suddenly it begins to rain. This disturbance may lead to deviation of choice away from goals. User may choose to stay at home or drive rather than walking or cycling. But for this decision to be made, this disturbance must be perceived strong enough by the user. Disturbances need not only to be environmental. It may be as an unexpected meeting, behavioral preferences or may be just the convenience factor that leads to change in decision.

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Planning prior to setting of goal is considered important component of goal implementation. While setting the goal, people may ignore the obstacles or may fail to realize the level of commitment required to attain the goal. Hence if users plan in advance, the detailed action required for implementation, they are more likely to attain the goal as desired. Planning has also a positive effect on car use reduction. Public information about TDM measures is likely to be more effective if it provides lucrative information i.e. beneficial measures and alternative transport, rather than deterrent or push measures. Personal habits are also believed to be a deterrent for goal attainment. Researchers have found that intentions and attitudes are difficult to enact if interfered by habits. In this case it is not inability of user to look for alternative but it’s unwillingness. Hence types of measures required to form a habit may not be the same as breaking the habit. TDM policies comprising of push measures may be helpful and effective in breaking the habit but may not help in yielding new behavior. A pull measure has potential to attract the user to form a new habit. So it is advised to use both the push and pull measures to achieve significant change in travel behavior. A pull measure may help in forming new habits but not before push measures have been implemented successfully.

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Expected user response to TDM measures As it is evident now that users have different impacts of different measures and hence it

would be proper to say that user response to this impact would be different too, for

different measures. To study this user response i.e. expected car use reduction, three

different scenarios are created with one push measure ( i.e. raised tax on fuel to

discourage use of car ), one pull measure ( i.e. improved public transport with respect to

reduced cost and increased frequency to attract users to use public transport ), and

combination of the two measures ( i.e. one push and one pull measure ).

Various studies have shown that different measures get different responses from the

user. This difference in response is not only with respect to different measures

implemented but also the on the extent to which a measure is implemented. Estimates

of transport elasticity provides information on the extent to which travel demand is

sensitive to price changes and to changes in public transport services. Several studies

have shown that a 10% increase in fuel price causes between 1% – 3% car use

reduction (Dargay, 2007). Furthermore, a 10% increase in bus fare has been found to

lead a 4% reduction in travelling (dargay & Hanley, 2002). Another study suggested that

a 10% increase in service frequency led to an average increase of 5% in ridership

(Evans, 2004).

Though it is expected that push measures have larger impact on the user behavior in

comparison to pull measures but no significant change in reduction in number of car

trips is found in push and pull pricing measures. However, a study showed that a

combination of one push measure and two pull measures led to a slightly higher

reduction in distance travelled by car compared to the measures evaluated individually.

Hence it is important to understand how car user respond to various TDM measures

and the important issue is to compare the behavioral effect of different TDM measures.

Fist thing to be examined is to what extent car users expected to reduce their car use in

response to the TDM measure as it is uncertain whether it is better to constrain car use

or improve alternate modes and also to determine level of structural changes to get

significant deterrence in behavior.

Secondly it is desired to find out, that in response to the TDM measures, which car

reducing strategies would be used by use. The most frequently chosen strategies are, a

more effective car use and change in travel mode. It was expected that change in travel

mode would be the most commonly used strategy in response to the improved public

transport. In response to the increase in tax, cycle/walk is expected to be chosen as

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most effective strategy. For combination of measures, both the strategies are equally

expected to be chosen.

Thirdly, it is desirable to find the factors that are important for car use reduction in

response to TDM measures. These factors are mostly behavioral factors. These are

internal motivation, background factors, personal norms etc. Internal motivation factor

are found to be more important than background factor. We have already discussed

these behavioral impacts on users in the last chapter.

The study was done in two parts in order to separately measure the internal motivation

and background factors in one hand and evaluation of TDM measures on other hand.

First a pre-questionnaire was given to identify car users with similar characteristics to

assess their internal motivation and background factors. They were asked if they are

willing to respond to a second questionnaire regarding TDM measures. Those who

agreed to respond were randomly given three separate questionnaires regarding three

scenarios of TDM management. One group evaluated the case where public transport

was improved by reduced rates and increased service frequency. Second group

evaluated the measure where fuel prices were raised to create deterrence of car use.

And third group evaluated the scenario where combinations of these measures were

implemented. In each of the questionnaire, the policy package was described in detail

and possible monetary, time, convenience and environmental benefits of respective

measures were stated.

Before analyzing the expected car use reduction, it was analyzed whether three groups

are similar in their internal motivation and background factors, so that there is no

significant difference between groups.

As the first aim was to analyze the extent to which car use is reduced in response to the

TDM measures, it is found in the study that combination of push-pull measures led to

significant reduction in car use in comparison to improved public transport for weekly

car use. In this case no significant difference is found between raised tax and combined

measure. For annual car use, it was found that combined measure reduces car use to a

greater extent than increased tax. Hence the combined measure displayed the

reduction of car use to a greater extent than individual measures. For long term, no

significant differences in reduction of car use for individual measures were found.

The second aim was to examine the strategies to reduce the car use in response to

TDM measures. From users response it was found that, group evaluating improved

public transport would reduce their car use by switching to public transport only,

especially for shorter distances. But as the distance of travel became larger, the affinity

to reduce car uses decreased, showing preference to travel by car for longer travel

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distances. For the group evaluating raised tax, walking or cycling emerged as the most

preferred strategy for shorter travel distances. For moderate distances some preferred

public transport. One in every five respondent still preferred to use car for travelling. In

response to the combined measure, users preferred both, cycling/walking and public

transport equally for shorter travel distances. For larger travel distances, they preferred

public transport. Respondents planned to reduce 80% of car trips, if measures were

implemented.

The third aim was to identify the crucial background factors important for the car use

reduction in response to the TDM measures. The results of the analysis done on

background factors showed that only number of cars in the household were significant

predictor for expected reduction in car use for improved public transport and combined

measure. It showed that more number of cars in household leads to lesser reduction in

car use. When internal motivation was analyzed, numbers of cars were significant

predictors for improved public transport only. Personal norm to reduce car use for

improved public transport and combined measure and intention to reduce car use for

raised tax emerged as a other significant predictors.

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Conclusion

The various TDM measures are certainly effective in dealing with congestion and can

be very effective in mitigating environmental problems cause by road transport.

However, it is important to understand that success and effectiveness of these

measures, upto a large extent, depends on users perspective. i.e. how users see these

measures, how these measure impact them, and how users respond to these

measures. Since, to improve the public transport, expansion and new construction

might not be the viable option for government in most of the metro cities for the land,

monetary and environmental constraints, TDM may be an effective measure to improve

the situation. As these measures and its effectiveness rely largely on user response, it

is imperative from transportation planners point of view to analyze and understand the

potential impact of measures on user and user’s response to the measures, before

implementing them. From this study it has been found that instead of implementing any

single TDM measure, it is always beneficial to implement a combination of push pull

measures. Both the analyses, i.e. analyses of behavior of user in response to the

measures and analyses of user response for expected car use reduction, put forward

similar outcomes, stating combined push-pull measures to be more effective than

individual measures.

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Further research areas Many conceptual analyses and studies has been done to identify crucial factors of

human behavior and how to influence them to change the travel mode choices. Various

TDM measures are also evaluated against and with each other to analyze their

respective efficiency. There are some further research issue that is needed to be

highlighted for further insight about the impacts of TDM measures on user’s behavior

and response. Some of the identified areas are:

● Pre and post implementation study of TDM measures to study actual results

attained and compare it with expected results to find out the amount of and

factors responsible for deterrence.

● Effect of TDM measures on trip chain attributes.

● Effect of the response of non targeted user on the response of targeted user, by

a TDM measure or group of measures. It is crucial to understand the

interdependencies of factors.

● Identification of situational factors that leads to non-attainment of goals set by

user.

● Influence of TDM measure in breaking the car-use habits of the user.

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http://www.vtpi.org/tdm/ [Accessed on 29 mach 2012]

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