Travel Demand Management Measures Research Articles

ANALYSING THE POTENTIAL OF TELECOMMUTING AS A SUBSTITUTE FOR COMMUTE TRAVEL

Earlier research had identified association between telecommuting and commute travel. Telecommuting is considered as a travel demand management measure in mitigating travel especially work trip to the central business district. However, whether it acts as an effective travel demand management measure is still remain to be seen. This paper investigates potential of telecommuting as a travel substitute especially for work related trips. The analysis of travel substitution as a result of practicing telecommuting was made based on stated preference of the employees in the selected business organizations by questionnaire survey. The survey was administered in two major cities namely Kuala Lumpur and Johor Bahru in Malaysia. Work trip components include commute trip and vehicle-km. Telecommuting frequency between 1 and 3 days per week was considered for this study. The analysis revealed that the commute trip reduction from stated preferred telecommuters was not more than 10% of the total commute trips.

Institutional constraints on transport policymaking: the case of company cars in Israel

Transportation analysis emphasizes the necessity to internalize the transport externalities of car usage through taxation. Yet taxation decisions are often made with non-transport goals in mind. In such cases, transport policies are made ‘by the way.’ This paper examines such a case: Israel’s taxation policy on company cars. It shows that current taxation policies result in increasing numbers of company cars and growing numbers of transport users who are not sensitive to the marginal cost of car use and make excessive use of the car. As a result, a significant portion of Travel Demand Management (TDM) measures cannot affect this group. The Israeli case of company car tax reform demonstrates the problematic effect of a policy that does not take its overall consequences on other policy fields into account and thereby impairs efforts to reduce the negative impacts of the transport system. Also, it demonstrates the importance of institutional aspects of transport policymaking.

Travel Demand Management Targeting Reduced Private Car Use: Effectiveness, Public Acceptability and Political Feasibility

The private car is fast, comfortable, and convenient. However, worldwide massive car use causes serious environmental problems. Although breakthroughs in clean automobile technology may be under way, reducing car use seems necessary in order to achieve a sustainable transportation system. Several travel demand management (TDM) measures have therefore been proposed and some have been implemented with this aim. The article reviews research addressing the question of how effective, acceptable to the public, and politically feasible such measures are. The conclusion is that noncoercive TDM measures alone are unlikely to be effective in reducing car use. Therefore, coercive TDM measures such as increasing cost for or prohibiting car use may be necessary but are difficult to implement because of public opposition and political infeasibility. If combined with noncoercive TDM measures providing attractive travel alternatives and communicating the benefits of car‐use reduction to the public, coercive TDM measures are likely to become more effective, acceptable, and politically feasible.

A Strategic Niche Analysis of Urban Road Pricing in the UK and Norway

Traditional transport policies of road expansion entail a relatively simple system of actors and processes around which expertise, knowledge, and skills which has built up over many decades. Some of the more radical Travel Demand Management measures, including urban road pricing, involve a complicated set of institutions, processes, people and procedures. Road pricing schemes often get delayed or abandoned due to controversy, disagreements, unanticipated problems and a whole host of other delaying factors. If they are implemented, they tend to be diluted and consequently become less effective. Strategic Niche Management (SNM) has previously been used to provide guidelines on the implementation of innovative transport technologies through setting up protected experimental settings (niches) in which actors learn about the design, user needs, social and political acceptability, and other aspects. Here SNM is modified to cover a policy approach through the analysis of road user charging case studies in the UK and Norway. A detailed analysis of the road user charging schemes in Bergen, Oslo, Durham and London is presented. Key factors identified include the role of stakeholder and user networks, the existence of a project champion, understanding the motivations and expectations of stakeholders and users, learning with regards to the regional context, and the change in perceptions associated with acceptance. Comparison between the four cases shows different approaches emerging from each country in implementing and ‘marketing’ of the policies. The paper concentrates on approaches such as: the purpose for introducing the policies, the involvement of users in the planning process and, the use of revenues for either providing alternative transport modes or financing road infrastructure. Key factors identified using the SNM framework include the role of stakeholder and user networks, the existence of a project champion, understanding the motivations and expectations of stakeholders and users, learning with regards to the regional context, and the change in perceptions associated with acceptance. This type of analysis could prove useful for transport planners envisaging the implementation of road pricing projects.

Acceptability of travel demand management measures: The importance of problem awareness, personal norm, freedom, and fairness

Acceptability of travel demand management (TDM) with the aim of reducing private car use is modeled following a hierarchical set of beliefs. In a two-part model, pro-environmental orientation, problem awareness, personal norm, and willingness to reduce car use are linked to beliefs about to which extent the specific TDM measure is perceived to influence freedom to choose travel mode, own reduction of car use, effectiveness, fairness, and subsequently acceptability. Data were collected through a mail survey in Sweden, and the model was tested in a sample of car users for three TDM measures; improved public transport, an information campaign, and increased tax on fuel. First, the models were tested and modified in a randomly selected sub-sample ( N = 462 ), then the modified models were validated in the remaining sub-sample ( N = 460 ). We conclude that problem awareness and personal norm, in combination with evaluations of specific TDM measures, are underlying the acceptability of TDM measures. Moral considerations and perceived fairness were important for the acceptability of increased tax on fuel, while freedom aspects and problem awareness were of importance for the acceptability of improved public transport. Because acceptability often is important for the implementation of TDM measures, policy makers may draw on these results when attempting to increase the acceptability of various TDM measures.

Understanding the process of adaptation to car-use reduction goals

Using a more controlled experimental setting, the present study follows up two previous studies; a focus group study examining participants’ own proposed adaptations of car use to various travel demand management measures, as well as quantifications of the expected extent of adoption of certain adaptations, and a study of actual behavioural responses to the introduction of a toll ring. An internet survey requiring respondents to state the frequency with which they would adopt various adaptation alternatives when given a small, medium, or large car-use reduction goal was conducted. The frequency with which a particular adaptation is implemented was not only found to vary with size of reduction goal, as expected, but also with trip purpose. The results were interpreted in the light of a cost-minimisation principle of adaptation.

Investigating the Effect of User Behavior Factors and Transportation Control Measures on Day-to-Day Network Evolution and Trip Time Reliability

This paper investigates the day-to-day dynamics in an urban traffic network induced by joint route and departure time switching dynamics in commuter decisions under real-time information. The role of switching inertia, the user's sensitivity to experienced and lagged system attributes, and travel demand management measures on day-to-day evolution are analyzed. A simulation-based day-to-day network analysis framework is developed by incorporating empirically calibrated user behavior models under information. This model can be used to analyze network reliability and stability measures. Because it can model users' responses to information and experience, this framework permits relaxing the assumption that user behavior remains unchanged. Therefore, it can be used to model the transient effects due to various types of system perturbations and shocks. Computational experiments are used to investigate the effect of the aforementioned factors. The findings suggest that trip time variability and lateness propensi...

Investigating the Effect of User Behavior Factors and Transportation Control Measures on Day-to-Day Network Evolution and Trip Time Reliability

This paper investigates the day-to-day dynamics in an urban traffic network induced by joint route and departure time switching dynamics in commuter decisions under real-time information. The role of switching inertia, the user's sensitivity to experienced and lagged system attributes, and travel demand management measures on day-to-day evolution are analyzed. A simulation-based day-to-day network analysis framework is developed by incorporating empirically calibrated user behavior models under information. This model can be used to analyze network reliability and stability measures. Because it can model users’ responses to information and experience, this framework permits relaxing the assumption that user behavior remains unchanged. Therefore, it can be used to model the transient effects due to various types of system perturbations and shocks. Computational experiments are used to investigate the effect of the aforementioned factors. The findings suggest that trip time variability and lateness propensity increase under high congestion. Under joint switching dynamics, a significant deviation from equilibrium is observed even after nearly 2 months. Departure time switching behavior appears to exert a greater influence than route switching on day-to-day dynamics, and transportation control measures can improve trip time and network reliability. These results have important implications for congestion mitigation strategies, network reliability assessment, and evaluation of intelligent transportation system technologies.

Public attitudes towards policy measures for reducing private car use: evidence from a study in Sweden

Abstract In an internet survey, a random sample of 291 university employees living in Gothenburg, Sweden, reported their beliefs and evaluations of the consequences of implementing three travel demand management (TDM) measures varying from less to more coercive. The results showed that respondents differentiated amongst the TDM measures in terms of each measure's expected consequences and that, when combining these beliefs with evaluations, a statistically significant proportion of variance was accounted for in attitudes to the TDM measures. Environmental concern modified several of the effects of consequences on attitudes towards TDM measures, as well as influencing overall attitude. The general and practical implications of these findings for improving attitudes to such policies are also discussed.

Adaptation of Private Car Use in Response to Travel Demand Management Measures: Potential Roles of Intelligent Transportation Systems

Travel demand management (TDM) measures targeting changed or reduced private car use in urban areas prompt individuals and households to choose more efficient car use (chaining trips, car pooling, choosing closer destinations), to suppress trips and activities, or to switch travel mode. We conjecture that these choices are made sequentially over time according to a cost-minimization principle. In general, less costly changes may however be less effective. Several potential ways are proposed in which intelligent transportation systems may reduce the costs of changes or reduction in car use, thus presumably rendering TDM measures more effective.

Mapping the potential consequences of car-use reduction in urban areas

Policy measures managing the demand for private car use are contemplated in urban areas all over the world. A first step in evaluating the effectiveness––as well as the interrelated sociospatial consequences––of travel demand management (TDM) measures is determining how their implementation changes the travel options faced by households in different segments. Geocoded travel diary data from Gothenburg, Sweden, are analysed with the aim of determining the number and type of trips by car to the city centre that would be affected by the introduction of traffic regulations varying spatially and temporally. Logistic regression analyses are performed to identify effects on different trip purposes, as well as individual and household characteristics related to changes in travel options. The possible application of the results within a policy context and to other urban areas is discussed along with the potential implications for research into adaptation strategies adopted in response to the implementation of TDM measures.

Car-user responses to travel demand management measures: goal setting and choice of adaptation alternatives

Travel demand management measures can be used to encourage car users to set car-use reduction goals when experiencing impairments in travel options. In forming plans to reduce car-use contingent on such goals, car users consider a range of adaptation alternatives including more efficient car use, suppressing trips, and switching travel mode. These adaptation alternatives, it may be argued, are implemented sequentially over time according to a cost-minimisation principle. A focus group study was conducted gauging the creativity of car-using households when contemplating adaptation alternatives, followed by an Internet-based questionnaire study in an attempt to obtain quantitative estimates of the size of car-use reduction goals and frequency of implementation of adaptation alternatives. The data revealed that the effects of travel demand management measures and trip purpose on the setting of car-use reduction goals were small. While the cost-minimisation principle seemed to dictate stated choices of adaptation alternatives, further research needs to examine the ways in which the principle must be qualified.

TRAVEL DEMAND FORECASTING AND TDM MEASURES: THE EXAMPLE OF MONTREAL'S SOUTH SHORE, 2001-2021

This paper presents a case study of travel demand forecasting in the Montreal metropolitan area that is based on an extensive study conducted for the Quebec Department of Transportation. The main goal was to determine whether or not there is a need for new infrastructure vs. travel demand management (TDM) measures to solve the problem of growing congestion on Montreal's bridges. Findings from this work show that strong aging trends will have the effect of reducing past tendencies toward rising global mobility and motorization, and diminished demand should be evident by 2011, especially if strong TDM measures are instituted. The combination of various TDM measures could have a prominent effect on future travel demand and appears to be a realistic alternative to installation of new infrastructure.

ESTIMATING BENEFITS OF TRAVEL DEMAND MANAGEMENT MEASURES

In this paper, models for estimating benefits of travel demand management measures are presented. These models consider the uncertainty of travel times emanating from park-and-ride systems and road pricing, and are based on driver behavior studies and dynamic traffic simulation. A test road and railway network in Kyoto-Osaka area, Japan, was used as a case study for the models. Results indicate that commuting drivers can expect both benefits by reducing travel times, as well as reducing variation of travel times by implementing park-and-ride systems.

Analysis of Trip and Stop Duration for Shopping Activities: Simultaneous Hazard Duration Model System

A joint hazard-based model for the analysis of simultaneous (mutually interdependent) duration processes is proposed. The proposed model generalizes independent hazard-based models by accounting for correlations between simultaneous duration processes. Furthermore, the model also permits the use of flexible and variable hazard function parameters to capture realistic features observed empirically in activity duration data (e.g., bimodal peaks). To account for correlated processes (duration processes) that underlie observed stop and trip durations, the proposed model relies on an implicit component of error structure that combines a baseline hazard function (log–logistic distribution) with a mixing (log–normal) distribution. This model is estimated by the simulated maximum-likelihood technique and is used to analyze activity and trip duration for shopping activities. The results highlight the need to account for duration dependence effects in activity–travel durations. Furthermore, hazard-based models that disregard correlation across joint duration processes can provide biased estimates and inaccurate forecasts. Empirical results from San Francisco, California (1996), activity diary data imply that stop and trip durations for shopping activities are positively correlated. The hazard rate profile (shape and intensity) also varies significantly across individuals, suggesting the need for targeted demand management measures. At a substantive level, the results indicate the role of personal, household, and situational attributes on activity and trip duration decisions. These findings and models have important applications in the analysis of activity–travel dimensions of duration and timing and the evaluation of alternate travel demand management measures.

A conceptual analysis of the impact of travel demand management on private car use

A conceptual framework is presented that may be utilized when analyzing changes in household travel arising from the range of potential measures available to policy makers. The proposed framework draws on goal setting theory in order to understand how travel is influenced by the impact various travel demand management (TDM) measures have on time, cost, and convenience of travel options. Travel is understood from a perspective assuming that it is controlled by negative feedback functioning to minimize deviations from goals nested at different levels. The conceptual framework, with its basis in goal setting and control theories, is then applied to understanding strategic and operational choice related to travel as well as habitual travel. Finally, the proposed conceptual framework is used to highlight and focus attention on key research issues that ought to be addressed if our understanding of the impact of TDM measures on household travel, and private car use in particular, is to improve.

Public attitudes to TDM measures: a comparative study

This paper presents the results of a range of data analyses of users’ attitudinal responses to various travel-demand management measures in two case-study cities in the UK: Cambridge and Newcastle upon Tyne. The analyses focus on several important aspects of implementing TDM measures, including the relationship between the perceived effectiveness and public acceptance of alternative TDM measures and how the generated net benefits, in particular the revenues raised from road-user charging and increased parking charges, are used. A number of key issues are identified for the implementation of TDM measures that are both acceptable to the public and also capable of achieving their stated objectives.

The integration of travel demand management and technological measures for reducing the level of road traffic noise

Noise pollution is one of the major environmental damages caused by automobiles. In 1997 of Japan, 4,135 out of 4,772 roadside observatory stations failed to keep environmental quality standards for noise. Since there has been little improvement in the number of stations satisfying environmental quality standards, we need more powerful actions to change this undesirable situation. In this study, we constructed two models, traffic assignment model and traffic noise model, in order to test several policy measures of roads and road traffic for reducing the level of road traffic noise in a consistent way. The model was built on geographical information system (GIS) and it made the model more operational and easily understood. From a series of Sendai City case studies, the installation of drainage asphalt pavement proved an efficient way of decreasing the level of traffic noise. Porous elastic road surface could abate traffic noise considerably and would be a better measure if the cost would be reduced in future. Cordon pricing, as a measure of road traffic, was effective, but it also worsened the situation in the areas outside the cordon line. The construction of the ring road relieved the serious situation in the city center, but still increased the level of traffic noise in the areas around the cordon line since the ring road itself became the major traffic noise source. Finally the effects of the integrated measures of roads and road traffic were tested and confirmed.

Self-reinforcing motorization: can travel demand management take us out of the social trap?

Motorization is a self-reinforcing process, which involves positive feedback. Using a simple model of bi-modal transportation system, it is shown that a transportation system may eventually be dominated by the automobile, or may equilibrate at a grossly inefficient point due to social dilemmas associated with automobile use. Furthermore, in areas with well-developed public transit, road capacity addition can be detrimental not only to the public transit but also to the automotive transportation. Travel demand management (TDM) measures are conceived in this study as mechanisms to prevent the divergence of the motorization process away from a social optimum due to its positive feedback and social dilemmas. A simple model of bi-modal transportation system and a cellular automata model of individuals’ TDM compliance behavior are combined in the study to see how TDM measures that rely on individuals’ voluntary cooperation may be effective. Results of simulation analyses based on the model are presented.

Evaluation of travel demand measures and programs: a data envelopment analysis approach

Traffic congestion in urban as well as suburban areas has increased steadily in the United States despite substantial increases in federal, state and local spending. While no adequate responses to control the growth of congestion have been identified, travel demand management (TDM) has become a recognized policy option. Despite the recognition of TDM measures as a potential option, few methods have been suggested that can critically evaluate the improvements achieved through these measures at individual worksites or can isolate the effects of particular measures. This paper presents such a methodology and applies that methodology to 33 worksites that have TDM programs in effect.