Transportation Demand Management Policies Research Articles

Measurement of public acceptance of TDM policies using combination of public policy acceptance (PPA) and value belief norm (VBN) approach

One strategy to overcome the problem of imbalance between the demand and supply of road transportation that causes congestion is to apply transport demand management (TDM). TDM is a series of transportation policies aimed at achieving sustainable transportation by reducing the use of private vehicles and prioritizing public transport and/or non-motorized vehicles. The level of public acceptance of TDM largely determines the success of TDM implementation. Through the Value Belief Norm Theory approach, it can be seen that public acceptance of TDM policies will be influenced by how high the norm of community partiality towards the environment. The level of public acceptance of a TDM regulation can also be measured by the Public Policy Acceptance (PPA) Model. The results of the study proved that acceptance of TDM strategy implementation was quite significantly influenced by the pro-environment attitude of the community. The PPA model result showed that people tend to be skeptical of the implementation of TDM policies.

Acceptability of transportation demand management policy packages considering interactions and socio-economic heterogeneity

The Transportation Demand Management (TDM) policies will not be authorized if they have not enough public acceptability. In this study, policy packing is proposed as a way to alleviate the unacceptability of coercive (push) TDM policies that have considerable effectiveness (e.g., cordon and parking pricing) by using some non-coercive (pull) TDM policies (e.g., transit development). Furthermore, in addition to the main effects, the interaction effects of TDM policies on the acceptability of two policy packages are addressed. Policy package (I) includes cordon pricing and reduction of transit access time, and Policy package (II) contains parking pricing and reduction of transit access time. A Random Parameter Ordered Logit (RPOL) model is developed based on a choice experiment designed for car commuters of Tehran, Iran. Results confirm that while reducing transit access time have a significant interaction effect with cordon pricing on the acceptability of Package (I) it has not a significant interaction effect with parking pricing on the acceptability of Package (II). Furthermore, the heterogeneity of respondents' cars value and the presence of free parking at the workplace can significantly affect the acceptability of Package (II). This study also addresses the effect of respondents’ trip and socio-economic characteristics on the acceptability.

Expanding the VBN theory on succeeding the transportation demand management policies

The growth of the car fleet has caused many problems, such as environmental problems, uncontrolled energy consumption, and traffic congestion. To resolve the issues caused by transport-related activities, transportation planners should implement policies that reduce car use and move forward to sustainable transportation. The prerequisite of the efficiency of the policies that reduce car use is the acceptance of them by the entire community members. Previously a few studies have tested individuals’ environmental attitudes using the Value-Belief-Norm (VBN) theory. This research aims to analyze and examine car use reduction policy using a comprehensive VBN and Norm-Activation-model (NAM) theories to consider more variables and provide a model with more analytical capability. To address this issue, 500 questionnaires were filled by travelers’ in Tehran, Iran, in the restricted traffic area to describe their behavior. The result shows that the biospheric value significantly affects car use reduction policy, associated with considerable environmental concerns. Besides, it was found that a high ascription of responsibility (A.R.) appeared as the strongest predictor of the policy. The findings have represented initial support for the VBN theory and revealed that the theory could explain the car use reduction policy’s Intention, according to Tehran’s respondents’ environmental behavior. This study’s findings can assist policymakers in adopting appropriate policies to reduce car use based on environmental advantages and could target biospheric values and ascription of responsibilities.

Transportation demand management policy efficiency: An attempt to address the effectiveness and acceptability of policy packages

As private car usage has negative effects, such as traffic congestion and air pollution, the effectiveness of Transportation Demand Management (TDM) policies could be considered as any reduction in car usage. However, the efficiency of TDM policies could be addressed by a combination of their effectiveness and public acceptability. Policy packaging is treated as a way to get more benefits from a set of policies in form of a package. Therefore, to improve the efficiency of a package containing a push TDM policy, which is usually effective but not acceptable, introducing a pull policy that is generally acceptable could be of interest. This research aimed to evaluate the efficiency of two packages of TDM policies containing a push policy (either cordon or parking pricing) and a pull policy (transit system development). Therefore, 535 working-purpose car commuters were interviewed to examine the trade-offs between the acceptability and effectiveness of each package. According to the results, although the transit development policy causes a 1.52% reduction in car usage, it significantly affects the acceptability of cordon pricing and transit development package. Finally, a discussion is provided regarding how to use the policy packages to achieve the highest potential effectiveness at a specific level of acceptability.

Examining the Nonlinear and Synergistic Effects of Multidimensional Elements on Commuting Carbon Emissions: A Case Study in Wuhan, China

Understanding the specific effects of multidimensional elements of a built environment, transportation management policies, and the socio-demographics of travelers associated with commuting carbon emissions is significant for planners in promoting low-carbon and healthy urban development through transportation and land use and urban management policies. Most of the existing studies focus on the complex mechanisms affecting commuting behavior, but the relevant elements and specific mechanisms affecting commuting carbon emissions have not received sufficient attention. This study uses a random forest approach to analyze residential travel data from Wuhan, China. The results show that built environment and transportation demand management policies are critical to commuting carbon emissions, and that there is a non-linear association between multidimensional factors and commuting carbon emissions in Chinese cities. In addition, the study examines the synergistic effects of built environment and transportation management policies on commuting carbon emissions among different built environment elements. The results of the study provide valuable insights for planners in formulating low-carbon city and transportation development policies.

Social Marketing Applications and Transportation Demand Management: An Information Instrument for the 21st Century

Concern has been expressed by planners and policy-makers that the “add capacity” strategy used in building more roads to resolve traffic-induced problems is no longer a feasible option. This article explores private transport behavior in understanding how users can be persuaded to adopt a more blended approach (i.e., integrating car, public transportation, and alternative modes on a daily basis). The research methodology adopted focus groups and travel diaries in presenting a number of social marketing message appeals aimed at inducing a change in participants’ travel behaviors. While weaknesses are identified in the social marketing materials, this research concludes that social marketing as a stand-alone intervention program is not capable of persuading people to alter their overdependency on car use. Nonetheless, participants did acknowledge that the messages were informative and helpful in educating them on transportation issues. The research suggests that social marketing programs could be of value as information instruments in support of transportation demand management (TDM) policies. Such programs can function as an effective channel of communication in building dialog and garnering wider public support of demand management policy and in delivering important transportation messages directly to commuters.

Learning-Based Model for Evaluating the Impact of Neighborhood Design on Travel Behavior

This research developed an agent-based model that evaluates the impact of neighborhood design on travel behavior while accounting for habit formation, social interactions, various levels of information provision, and awareness of transport and land use system changes. The developed model employs a framework that integrates random utility maximization theory with reinforcement learning concepts to account for the bounded rationality and knowledge learning process. Moreover, the model utilizes the diffusions of innovations theory to simulate how agents propagate information across family members and co-workers. It also adds a time dimension to the modal shift process, which could be used to indicate the relative duration to reap the full benefits of proposed scenarios. The model was applied to a neighborhood in Kelowna, British Columbia, Canada, to assess the impact on travel behavior of the SMARTer growth principles. The results showed that retrofitting non-motorized networks has more impact on modal shift than retrofitting road networks. This implies that infrastructure investments related to providing more accessibility for non-motorized users may be more socially and sustainably profitable than investments in policies targeting auto users. In addition, the results revealed that land use policies led to higher modal shift to non-motorized modes compared to retrofitting the transportation network, which highlights the importance of integrating land use and transportation planning. Similarly, the results demonstrated that transportation demand management policies can provide a positive stimulus to commuters to maintain familiarity with active transportation (AT) modes, which led in the presented case study to an increase in AT modal share.

The Evolvement of Rail Transit Network Structure and Impact on Travel Characteristics: A Case Study of Wuhan

The expansion of the rail transit network has a positive impact on travel characteristics under spatial and temporal constraints by changing accessibility. However, few empirical studies have examined the longitudinal evolution of the impact of accessibility and travel characteristics. In this paper, a model of the Wuhan rail transit network is constructed and the evolution of the spatial pattern of accessibility over different periods is analyzed. The correlation of accessibility with rail transit travel characteristics is studied longitudinally to provide theoretical support for rail transit construction and traffic demand management. The study shows that: (1) Wuhan’s rail transit network has evolved from a tree to a ring, improving the operational efficiency. (2) The accessibility of Wuhan’s rail transit network has evolved into a circular structure, showing a decreasing trend away from the city center. (3) The change of accessibility greatly affects travel characteristics. The higher the accessibility, the higher the traffic volume, and the lower the travel frequency, the more residents travel during peak hours, and the shorter the travel distance. These findings are useful for gaining insight into public transportation demand in large cities, and thus for developing reasonable transportation demand management policies.

Site-Specific Transportation Demand Management: Case of Seattle’s Transportation Management Program, 1988–2015

A central theme of U.S. transportation planning policies is to reduce single-occupancy vehicle (SOV) trips and promote transit and non-motorized transportation by coordinating land-use planning and transportation demand management (TDM) programs. Cities often implement TDM programs by intervening with new development during the municipal permit review process. Seattle’s Transportation Management Program (TMP) under a joint Director’s Rule (DR) requires a commitment from developers to adopt select strategies from six TDM element categories: program management, physical improvements, bicycle/walking programs, employer-based incentives, transit and car/vanpooling, and parking management. TMP targets new developments and requires some TDM elements, recommends others, and leaves the rest to negotiation. The result is an individualized TMP agreement that is site-specific, reflecting both city policy and developer needs. This case study presents a qualitative analysis of the guiding eight DRs and 41 site-specific TMP agreements in Seattle’s Downtown and South Lake Union (SLU) area since 1988. Overall, a content analysis of TMP documents reveals that the average number of elements adopted in an agreement falls short of requirements set by DRs (34%–61%). Major findings include developer preference toward non-traditional TDM measures such as physical improvement of frontage and urban design features, as well as parking management. High-occupancy vehicle (HOV) elements showed higher adoption rates (59%–63%) over biking/walking programs (< 1%). It is concluded that future TDM policies could benefit if future research includes examining the effectiveness of the range of management options stemming from the real estate trends toward green buildings, tenants’ values in sustainability, and city policy to reduce automobile trips.

Interpretations of Downs–Thomson paradox with median bus lane operations

The Seoul Metropolitan Government has implemented a public transportation priority policy with the introduction of a 121.1 km long of the Median Bus Lane (MBL). Therefore, to analyze the impacts of the introduction of Jongro-gu MBL in January 2018, an effect analysis using the speed and volume of passenger cars and buses in Seoul is conducted in this study. The interpretation of the Downs-Thomson (D-T) paradox demonstrates that the reduction in passenger car mode capacity can increase total social benefits. This study shows that the speeds of passenger cars and buses have reached the deterministic user equilibrium after the MBL introduction, resulting in an increase in total social benefits. Moreover, it demonstrates that the bus priority policies, which gives the right to keep the capacity of buses guaranteed in urban areas, will be effective. The interpretation of the D-T paradox will contribute to the formulation of transport demand management policies.

Traffic Demands Policies Effect on Congestion, Delay and Fuel Consumption

Traffic demands on Jordanian streets have been affected by the increasing human population and the number of vehicles. This study aims to apply transportation demand management (TDM) techniques to improve the level of service (LOS). The study employs both TDM and transportation system management (TSM). In order to investigate what type of strategies to be considered a questionnaire is used. The acceptance degrees of the TDM and TSM groups were measured via the questionnaires using SPSS version 20. The selected policies then are used on a certain location as a study case in Amman city; an intersection is connecting two urban main streets. The used policies have a reduction percentage in traffic demands which is expected throughout an expert panel. The results show that delay and fuel consumption are indeed reduced; however, this does not lead to any considerable improvement in the LOS. The LOS was enhanced when the reduction in traffic demand reached 20% with an increase in capacity achieved by adding 3 new lanes. The fuel consumption and delays were measured to be about 35% less with growth rate of 8% for the coming five years. This study is expected to help popularize TDM policies in place of other solutions so that inexpensive measures can be adopted by the government.

Macro-Scale Evaluation of Urban Transportation Demand Management Policies in CBD by Using System Dynamics Case Study: Isfahan CBD

Nowadays, in modern cities, travel demand management policies are more effective solutions for reducing vehicle traffic than road construction and private transportation infrastructure development. Traditional transportation planning methods that are appropriate for a partial analysis in traffic area zone levels require extensive data collection and only could be used to evaluate and compare a few number of demand management policies with limited criteria. In this paper, system dynamics modelling has been used to evaluate transport demand management policies. System dynamics is a suitable method for long-term macro-scale evaluations of different policies with various indicators, because in this method, causal relationships between variables and their feedbacks are considered as well as its dynamic approach, not needing detailed information in traffic area zones (TAZ) level, and the possibility of evaluating different policies. In this research, encouraging policies like improving the bus and taxi services, completing metro network development, improving bicycle facilities and encouraging to carpool as well as restrictive policies like cordon pricing policies, increasing parking prices, and odd-even policy and also simultaneously applying some of the encouraging policies and effective restrictive policies in the form of a policy package are being investigated in the central business district of Isfahan city. Urban transportation causal loops were conceptualized and the dynamic relations among urban transportation variables were created to develop the pertinent urban dynamics model. Efficacious transportation policies, which will be implemented for ten years, will be ranked in accordance with monitoring three indicators of air pollution, energy consumption and traffic mobility. Respectively, completing metro network development, BRT network development, improving bicycle facilities, cordon pricing, increasing parking prices, improving bus services, improving taxi services, odd-even policy, and encouraging to carpool are the most effective policies in Isfahan CBD. Among combined policies, completing metro network development simultaneously with cordon pricing has been the most effective combined policy to decrease air pollution and energy consumption and to increase traffic mobility in future.

Investigating factors affecting the mode choices of commuters in Kuwait city & surrounding urban areas: Strategies for a higher quality and more sustainable public transport system

Abstract This paper reports on the social, cultural, and demographic factors affecting Kuwaiti commuters. The objectives were to 1) investigate the awareness of Kuwaitis of transportation problems, 2) examine the perceptions of Kuwaitis of daily traffic congestion and how it affects them emotionally and physically, and the main objective 3) study the attitudes of Kuwaitis towards using public buses. An online survey was used to examine these factors, and a sample of five hundred transportation system users was obtained. The primary findings showed significant associations between the use of public transport buses and the user’s nationality, gender, age, education, and income level. Men are 2.6 times more likely to use buses, and non-Kuwaiti residents are 6.4 times more likely to use them. In relation to the perceptions of daily traffic congestion, findings indicate that with increase in travel time, commuters, in general, developed more negative feelings, such as exhaustion and stress. A large proportion of the sample population is aware of current local transportation problems and future transportation projects. The results of this study fill a gap in the knowledge of the socioeconomic and cultural factors that influence the success of sustainable public transportation solutions to the traffic challenges found in Kuwait. This knowledge is also crucial to foreign consultants working on planning and transportation projects in the region. It is recommended that officials use this new knowledge on cultural factors to develop integrated land use and transportation plans of the urban areas in Kuwait and to develop more effective and sustainable transportation demand management policies in support of UN Sustainable Development Goals that Kuwait has signed up to pursue.

Strategic Development of Transportation Demand Management in Jordan

The urban population growth and increase in a number of vehicles have affected the travel demand on Jordan Streets. The study aims to apply the Transportation Demand Management (TDM) policies to reduce the traffic flow in urban areas and improve the Level of Service (LOS). A group of a combination between TDM and Transportation System Management (TSM) strategies have been conducted, when TDM strategies were not successful to improve LOS. TSM concept refers to any group of actions that increase the capacity of roads network. Synchro 8 software was used to analyse the intersection conditions as important point, connecting two main arterial street in Amman area. A significant reduction in delay and fuel consumption was measured, but there was no real enhancement in LOS. The LOS was improved, when traffic demand was reduced by 20% and capacity was increased with 6 lanes on each approach for the existing conditions. The percentage of saving in fuel consumption and delay was observed to be around 64% and 63%, respectively for the next 5 years.

Simulation-based optimization for urban transportation demand management strategy

Transportation demand management (TDM) is one of the important methods for solving the problem of increasingly severe urban traffic congestion. This paper proposes a bi-level model to optimize urban TDM strategies based on simulation. The upper level is the TDM strategy optimization model, searching for the optimal TDM strategy. The lower level is a traffic assignment model based on the simulation, assigning traffic flow to multimodal transport networks according to the candidate TDM strategies. A heuristic algorithm is also defined and implemented to optimize TDM strategies. Based on VISSIM simulation, the optimization for TDM strategies proposed in this paper is validated with the research area of Harbor Square–San Ba Square–Er Qi Square in Dalian in China. The results show that the optimization of urban TDM strategies can effectively alleviate urban traffic congestion. It provides a scientific decision basis for urban TDM policy.

Car Ownership Control in Chinese Mega Cities: Shanghai, Beijing and Guangzhou

Three mega cities in China – Shanghai, Beijing, and Guangzhou – have implemented a unique quota policy to control car ownership growth. In this paper, we explore how special characteristics of China’s rapid urbanisation and motorisation contribute to the formulation of this unique policy. These cities, however, have adopted different policy designs. Auction, lottery and a hybrid of these two mechanisms are used in Shanghai, Beijing and Guangzhou respectively. We analyse the design, evolution and effectiveness of these policy measures. We also discuss how these measures can fit with an integrated transportation demand management policy.

교통수요관리정책에 대한 의식분석과 교통행동관리(Mobility Management)에 관한 연구

교통수요관리정책에 대한 의식분석과 교통행동관리(Mobility Management)에 관한 연구

Best Option For Reducing On-Campus Private Car-Based CO2 Emissions: Reducing VKT Or Congestion?

Reducing carbon footprint, especially from private cars, is an inevitable goal of sustainable transportation programs. Middle East Technical University (METU) in Ankara, Turkey, has a fairly large campus, for which carbon emissions are estimated to guide development of sustainable campus transportation demand management (TDM) policies. Focus is on reducing private car usage and increasing non-motorized and shared ride modes in a network. On the other hand, vehicle emissions with today’s engine technology are mostly governed by two major factors: Vehicle-km-travelled (VKT) and congestion, which slows down traffic and forces inefficiency in the engine performance. From engineering perspective, in order to evaluate real emission reduction potential of TDM scenarios, it is important to quantify its impact on these two factors and how much, which is the main focus of this study. For numerical examples, METU campus private car travel demand was used to calculate the VKT and speed levels for campus links by performing a network assignment in PTV-VISUM. The daily assignment was carried in three parts, as a morning and an evening peak, and an off-peak assignment, for a base case and 8 different scenarios. Emission component due to congestion was determined separately, as a percentage. The results showed that METU campus emissions were primarily function of the VKT, thus, could not be reduced by congestion management alone. They could be reduced by 30% if commuters would shift to the metro service supported by a strong in-campus shuttle services.

Route Divert Behavior in Jakarta Electronic Road Pricing Policy Implementation

The effectiveness of transportation demand management policy depends on how commuters respond to it. This study attempts to comprehend commuter behavior in choosing routes based on electronic road pricing (ERP) policy implementation on the Sudirman and Kuningan corridors. The experiments were conducted using the data collections from a stated preference experiment in which each commuter makes a route choice with an alternative representing a hypothetical situation with a combination of tariffs and travel time in ERP policy implementation. Logit models found that the individual and household variables influence route divert behavior. A commuter with a higher income or more family members living together is more likely to have less flexibility in diverting route. In addition, the distance of the trips affected their route divert behavior and influenced an individual trip chain constrained in timespace prism.

Acceptability of increasing petrol price as a TDM pricing policy: A case study in Tehran

Many cities around the world suffer from air pollution but Tehran is among the worst. Tehran suffers severely from congestion and air pollution, which is caused primarily by private vehicles. To mitigate these problems, Transportation Demand Management (TDM) policies should be instituted across the city to reduce private car usage. However, the acceptability of these policies is a major concern for policymakers. The goal of this research was to gauge individual opinions with regards to the increasing petrol price policy, followed by a comparison of these opinions with other TDM pricing policies, including cordon pricing or parking pricing. To do this, we conducted a survey of 366 car commuters in Tehran. Throughout the analysis of collected data, it was observed that increasing petrol price was the least acceptable of the above policies. In order to identify the effects of trip-related and socio-economic characteristics of car commuters on their acceptance of increasing petrol price, we developed an ordered logit model and identified the most significant factors affecting commuters. Next, we suggested policies that could lead to better acceptance of the increasing petrol price policy. This examination of the acceptability of TDM pricing policies helps policymakers to understand how pricing policies will have a greater chance of successful implantation and acceptance by the general public, thus allowing them to make informed policy implementation decisions.