Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: results of a conjoint choice experiment

In this paper, we report the results of a stated choice experiment, which was conducted to examine truck drivers?? route choice behavior. Of particular interest are the questions (i) what is the relative importance of road accessibility considerations via-a-vis traditional factors influencing route choice behavior, (ii) what are the influences of particular personal and situational variables on the evaluation of route attributes, (iii) how sensitive are truck drivers for possible pricing policies, and (iv) is there a difference in impact if environmental concerns are framed as a bonus or as a pricing instrument. The main findings indicate that road accessibility characteristics have a substantial impact on route preferences which is of the same order of magnitude as variation in travel times. This suggests that provision of adequate travel information in itself can be an effective instrument to prevent negative externalities of good transport associated with shortest routes. Furthermore, the results indicate that truck drivers/route planners when choosing a route are relatively sensitive to road pricing schemes and rather insensitive to environmental bonuses.     

Distinguishing the land use effects of road pricing based on the urban form attributes

This paper studies the effects of road pricing on land use under different development scenarios (business as usual scenario and transit oriented development scenario) by a quantitative method, which combines the integrated land use and transport interaction model (TRANUS model) with the scenario-planning techniques. Moreover, in order to further analyze the differences of the land use effects of road pricing on traffic analysis zones (TAZs) with different urban form attributes, a quantitative classification method combining factor analysis and cluster analysis is then used to quantitatively classify TAZs. The results demonstrate that the effects of road pricing on the land use of a specific region depend on the urban form attributes of the region. The higher the densities of employments and population, and better street design (high densities of street and intersections) and public transportation condition, the less the region is negatively affected by road pricing, and vice versa. More importantly, rail transit can alleviate the negative impact of road pricing on commercial development and population concentration of the region. Therefore, before introducing a road pricing policy, it is necessary to develop public transport system, especially rail transit.     

Labour market effects in assessing the costs and benefits of road pricing

Traffic congestion and the policies used to combat it have been studied extensively. One area which has received less attention is the secondary impacts of such policies. This paper uses a micro-simulation framework to study the effect on labour markets of road pricing. The key benefit of our chosen methodology is that it allows a simultaneous consideration of both commuting and migration decisions. We show that while welfare gains can be achieved through optimal charging, this may come at the price of decreased integration. This may manifest through either greater centralisation tendencies in population, or through unemployment disparities between regions.     

A framework to analyze the vulnerability of European road networks due to Sea-Level Rise (SLR) and sea storm surges

This study proposes a framework to explore the concepts of exposure, vulnerability and connectivity in EU road network and to assess the potential transportation infrastructure sensitivities towards Sea-Level Rise (SLR) and storm surges. The magnitude and significance of impacts were determined and knowledge of network robustness was built up based on existing climate data and on future trends. Various spatial databases were integrated and a four-stage transport model was used to explore the likely impacts of network degradation. The pattern of the network was assessed via both node- and link-based measurements, where different road databases, namely TRANS-TOOLS and Tele Atlas/TomTom, were employed in order to analyze the impact of spatial resolution within network connectivity analyses. This general framework developed for European Union, was tested on a specific and articulated case study area; namely, the north-east coastal region of Spain. The research conducted, yielded useful methods for the analysis of network vulnerability, where impacts are more significant in regional accessibility patterns. Accessibility indicators at the regional level changed drastically, with some regions showing up to a 26% decrease. According to the results of network connectivity indicators, the changes in network topology have reduced the number of alternative routes and placed more pressure on the transport system. The implementation of this framework and quantitative assessment methodologies outlined in this paper could be employed to assist policy makers to recognize the opportunities that may arise or diminish the adverse effects.     

Accessibility and transport infrastructure improvement assessment: The role of borders and multilateral resistance

The market potential indicator is a commonly used tool in transport planning for evaluating the potential economic effects derived from improvements in transport infrastructures. The general assumption is that exports from a given region will rise with increased accessibility, thus benefiting economic activities. However, the specification of the market potential model is typically very simple and ignores both the impact of competing rivals and the role of international borders, which leads to unrealistic results. Spatial interaction models on bilateral trade have already proved that international trade is affected by multilateral resistance, borders, adjacency, language or currency. Nevertheless, apart from some recent analyses that simply calibrate the distance decay parameter from trade datasets, these variables have hardly been integrated into research on market potential. This paper sets out to demonstrate that more realistic results are obtained by calibrating the distance-decay parameter and introducing the impact of competing rivals and border effects into the market potential formulation. The proposed model is then applied to the assessment of the accessibility impacts of new road transport infrastructure in the European Union between 2001 and 2012, which shows that the greatest improvements in accessibility were experienced by peripheral countries with high road infrastructure investment.     

Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion

The effect of the application of advanced transport information system (ATIS) and road pricing is studied in a transportation system under non-recurrent congestion. A stochastic network deterministic user equilibrium model (SNDUE) with elastic demand is formulated and used to evaluate the welfare and private impacts of different market penetrations of ATIS, together with road pricing for a simple network. Both marginal first-best road pricing and a second-best fixed road pricing are considered. The incentives of private users to use ATIS are analyzed and the characteristics of optimum tolls as a function of ATIS market penetration are shown. We conclude that ATIS is an efficient and necessary tool to reduce the effects of non-recurrent incidents in a transportation network, especially when non-recurrent congestion causes a significant deterioration of operational conditions of the network. If the impact of non-recurrent incidents on free flow costs is small or is reduced only to congestion effects, the use of road pricing would be more efficient. Social benefits obtained when jointly implementing ATIS and road pricing are practically the same whether first-best or second-best road pricing is used. Considering the private costs perceived by the network users, and the benefits experienced by equipped users, the maximum level of market penetration achieved could be limited because private benefits disappear after certain market penetration is obtained.     

Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?

Air traffic has an increasing influence on climate; therefore identifying mitigation options to reduce the climate impact of aviation becomes more and more important. Aviation influences climate through several climate agents, which show different dependencies on the magnitude and location of emission and the spatial and temporal impacts. Even counteracting effects can occur. Therefore, it is important to analyse all effects with high accuracy to identify mitigation potentials. However, the uncertainties in calculating the climate impact of aviation are partly large (up to a factor of about 2). In this study, we present a methodology, based on a Monte Carlo simulation of an updated non-linear climate-chemistry response model AirClim, to integrate above mentioned uncertainties in the climate assessment of mitigation options. Since mitigation options often represent small changes in emissions, we concentrate on a more generalised approach and use exemplarily different normalised global air traffic inventories to test the methodology. These inventories are identical in total emissions but differ in the spatial emission distribution. We show that using the Monte Carlo simulation and analysing relative differences between scenarios lead to a reliable assessment of mitigation potentials. In a use case we show that the presented methodology can be used to analyse even small differences between scenarios with mean flight altitude variations.     

Remoteness and accessibility in the vulnerability analysis of regional road networks

This paper considers the development of a method for network vulnerability analysis which considers the socio-economic impacts of network degradation and seeks to determine the most critical locations in the network. The method compares the levels of remoteness (or its inverse, accessibility) of localities within the study region, on the basis of the impacts of degradation of the road network on a recognised accessibility/remoteness index that can be applied to each and every location within the region. It thus extends the earlier work on accessibility-based vulnerability analysis which was limited to assessment of impacts on selected nodes in a network. The new method allows study of impacts on both specified locations (which do not have to be represented as network nodes) and the region as a whole. The accessibility/remoteness index is defined so that an accessibility surface can be calculated for the region, and the volume under this surface provides an overall measure of accessibility. Changes in the volume under different network states thus reflect the overall impacts. The method is applied to a rural region in south east Australia.     

Impact of ITS measures on public transport: A Case study

Intelligent Transport Systems (ITS) have a wide range of applications. They range from the more traditional signal coordination system to concepts such as smart cars and smart roads. This paper describes transit‐based ITS measures in Singapore. The island‐state has plans to double the current 90 km rail network over the next ten years and has also implemented or committed to implement many ITS initiatives that impact upon the public transport systems. The aim of these investments is to achieve a high transit modal share using a comprehensive transit network. ITS measures that can promote this aim include: automatic vehicle location systems for buses and taxis, integrated transit fare systems using contactless smart cards, rail information systems, multi‐modal travel guides on Internet and electronic road pricing. The potential impacts of these measures are delay reduction, more comfort, productivity gain and better network accessibility. ITS measures do not necessarily add physical capacity to a public transport system but are excellent supporting measures to encourage the modal shift to transit, particularly if a quality transit system is already in place.     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.     

Walking accessibility and property prices

Walking is an imperative travel mode, especially for short trips. Walking accessibility, which is defined as the ease of reaching essential destinations in the walk-in catchment area, may affect property prices because residents are more likely to be willing to pay for this attribute. In addition, different categories of public services may have varied influencing directions and magnitude. These two hypotheses are tested in this study. Taking Xiamen, China as a case study, we estimate the cumulative opportunities of public services on foot and develop a set of hedonic pricing models (more specifically, two pre-specified ordinary least squares models, four Box-Cox transformed models, and two spatial econometric models) to estimate, whether and to what extent, walking accessibility contributes to price premiums (or discounts). Using a database of 22,586 second-hand residential properties in 358 multi- or high-storey residential complexes, we find that (1) walking accessibility to public services contributes to the variations in housing prices and plays a role in determining housing prices; (2) different categories of services have vastly divergent, even opposite, influencing impacts; and (3) walking accessibility to primary schools, commercial centers, and sports and cultural centers have positive effects on house prices whereas walking accessibility to comprehensive hospitals adversely affects housing prices. Methodologically, we confirm that spatial econometric methods improve estimation accuracy and have more explanatory power relative to the standard non-spatial models. Robustness check analysis further guarantees the plausibility of this study.     

Accessibility matters: Exploring the determinants of public transport mode share across income groups in Canadian cities

Planning for accessibility is increasingly considered in the development of equitable plans by transport agencies and it has also been shown to exert a positive influence on public transport use. However, this influence has not been examined across income groups and in different geographic regions of varying sizes. The present study measures the relationship between accessibility and mode choice for low- and higher-income groups in eleven Canadian metropolitan regions. Our results show that the impact of accessibility on public transport mode share is stronger and non-linear for the low-income group especially in the largest metropolitan areas, where increasing accessibility past a certain optimal value will lead to a decrease in public transport mode share. However, this point occurs at the 80th percentile of existing accessibility, so improvements in mode share are nonetheless expected with improved accessibility in most areas within these regions. Moreover, in regions where an optimal value is not readily observed, improved accessibility throughout the region would lead to increased uptake of public transport for both the higher- and to a greater extent, the low-income group. Findings from this paper can be of value to transport professionals working towards meeting ridership goals around the world as comparisons between groups and across regions highlight the variation in the impacts of accessibility on mode share.     

Road pricing — an outsider's view of American experiences

Abstract

Substantial changes in urban transport policy have taken place over the past decade. The concern with expanding infrastructure and the preoccupation with providing sufficient road capacity to meet the increasing demand of unrestricted car use, which characterized transport policy in the 1950s and 1960s, has gradually given way to the idea that there is a need to restrain motor traffic if urban society is to function efficiently. A variety of restrictive physical traffic management, land use planning and economic policies have, in consequence, been pursued. One option which has attracted considerable attention in the academic literature, but which has been received more cooly by policy‐makers, is the possibility of optimizing urban traffic congestion through the imposition of road pricing. The introduction and relative success of the area licensing scheme in Singapore has added fuel to the arguments of the advocates of such a policy. This review is not directly concerned with either the experiment with road pricing in Singapore nor the theoretical debates which have taken place concerning the potential merits and defects of such policies but rather looks at the applied work in the United States which has looked into the practical implications of road pricing for its cities. Further, it seeks to explore, again drawing on American experiences, just why there has been so much opposition to the employment of economic pricing principles in the urban road transport market. The author presents the results of an SSRC sponsored study into the practical problems of introducing road pricing to cities in the United States.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

Rationing and pricing strategies for congestion mitigation: Behavioral theory,econometric model,and application in Beijing

Some travel demand management policies such as road pricing have been widely studied in literature. Rationing policies, including vehicle ownership quota and vehicle usage restrictions, have been implemented in several megaregions to address congestion and other negative transportation externalities, but not well explored in literature. Other strategies such as Vehicle Mileage Fee have not been well accepted by policy makers, but attract growing research interest. As policy makers face an increasing number of policy tools, a theoretical framework is needed to analyze these policies and provide a direct comparison of their welfare implications such as efficiency and equity. However, such a comprehensive framework does not exist in literature. To bridge this gap, this study develops an analytical framework for analyzing and comparing travel demand management policies, which consists of a mathematical model of joint household vehicle ownership and usage decisions and welfare analysis methods based on compensating variation and consumer surplus. Under the assumptions of homogenous users and single time period, this study finds that vehicle usage rationing performs better when relatively small percentages of users (i.e. low rationing ratio) are rationed off the roads and when induced demand elasticity resulting from congestion mitigation is low. When the amount of induced demand exceeds a certain level, it is shown analytically that vehicle usage restrictions will always cause welfare losses. When the policy goal is to reduce vehicle travel by a fixed portion, road pricing provides a larger welfare gain. The performance of different policies is influenced by network congestion and congestibility. This paper further generalizes the model to consider heterogenous users and demonstrates how it can be applied for policy analysis on a real network after careful calibration.     

Accelerating the transformation to a low carbon passenger transport system: The role of car purchase taxes,feebates, road taxes and scrappage incentives in the UK

The transition to a low carbon transport world requires a host of demand and supply policies to be developed and deployed. Pricing and taxation of vehicle ownership plays a major role, as it affects purchasing behavior, overall ownership and use of vehicles. There is a lack in robust assessments of the life cycle energy and environmental effects of a number of key car pricing and taxation instruments, including graded purchase taxes, vehicle excise duties and vehicle scrappage incentives. This paper aims to fill this gap by exploring which type of vehicle taxation accelerates fuel, technology and purchasing behavioral transitions the fastest with (i) most tailpipe and life cycle greenhouse gas emissions savings, (ii) potential revenue neutrality for the Treasury and (iii) no adverse effects on car ownership and use.The UK Transport Carbon Model was developed further and used to assess long term scenarios of low carbon fiscal policies and their effects on transport demand, vehicle stock evolution, life cycle greenhouse gas emissions in the UK. The modeling results suggest that policy choice, design and timing can play crucial roles in meeting multiple policy goals. Both CO₂ grading and tightening of CO₂ limits over time are crucial in achieving the transition to low carbon mobility. Of the policy scenarios investigated here the more ambitious and complex car purchase tax and feebate policies are most effective in accelerating low carbon technology uptake, reducing life cycle greenhouse gas emissions and, if designed carefully, can avoid overburdening consumers with ever more taxation whilst ensuring revenue neutrality. Highly graduated road taxes (or VED) can also be successful in reducing emissions; but while they can provide handy revenue streams to governments that could be recycled in accompanying low carbon measures they are likely to face opposition by the driving population and car lobby groups. Scrappage schemes are found to save little carbon and may even increase emissions on a life cycle basis.The main policy implication of this work is that in order to reduce both direct and indirect greenhouse gas emissions from transport governments should focus on designing incentive schemes with strong up-front price signals that reward ‘low carbon’ and penalize ‘high carbon’. Policy instruments should also be subject to early scrutiny of the longer term impacts on government revenue and pay attention to the need for flanking policies to boost these revenues and maintain the marginal cost of driving.     

Optimization of tunnel tolls in land use and transport planning

The task of transport planning is to determine cost-effective methods of providing and improving mobility, which can include minimizing traffic congestion. A cost-effective solution to transport problems should consist of a land use pattern, a transport system an a set of road pricing policies that together bring demand and supply into balance in an efficient and equitable way. The conventional approach aimed to produce comprehensive, long-term plans for land use and transport in considerable detail, but tended to ignore the role of road pricing policy, thus ending up with solutions that might not be efficient or economical. This feature of sub-optimal road pricing policy is accentuated by the overall growth in car use, which has generated problems with the efficient use of road space. This paper presents a computer analysis system (or model) which will enable the analysis of coordinated tunnel toll pricing policies by optimising an “objective function” while satisfying the associated and other constraints. The possibility of integrating the optimal road pricing policies in the land use and transport planning are discussed. A case study based on Hong Kong data demonstrates the efficiency of optimizing tolls on two of the three harbour crossing tunnels in Hong Kong.     

A Pareto‐improving hybrid policy for transportation networks

This paper investigates an innovative Pareto‐improving hybrid policy that combines two policy instruments, that is, congestion pricing and road space rationing, and takes advantage of the synergistic effects between these instruments. Mathematical formulations for developing Pareto‐improving pure road space rationing schemes and hybrid policies are presented. Numerical examples demonstrate that the proposed hybrid policy offers greater flexibility and is more prominent in leading to Pareto improvement than both pure congestion pricing and road space rationing schemes. Copyright © 2013 John Wiley & Sons, Ltd.     

The spatial productivity of transportation infrastructure

Transportation infrastructure services may cause an impact on the economy of the region in which they are located and, additionally, they are likely to have an impact on other regions. This effect has been labeled the spillover effect. In this study, the existence of direct and spillover effects of road, railway, airport and seaport infrastructure projects is tested by estimating a production function. Together with this primary objective, two common concerns in the literature are addressed: the lack of theoretical foundations for spatial econometrics models and the likely endogenous relationship between transport infrastructure and economic development. The estimated production function takes the form of a Spatial Durbin Model and is estimated using panel data from the 47 peninsular Spanish provinces by alternatively applying a Maximum Likelihood estimator and Instrumental Variables/Generalized Method of Moments estimators. According to the estimates, road transport infrastructure positively affects the output of the region in which the infrastructure is located and its neighboring provinces, while the remaining modes of transportation projects cause no significant impacts on average.     

Envisioning an emission diet: application of travel demand mechanisms to facilitate policy decision making

Emission reduction strategies are gaining attention as planning agencies work towards adherence to air quality conformity standards. Policymakers struggling to reduce greenhouse gases (GHG) must grapple with a growing number of travel demand policies. To consider any of these emerging demand mechanisms as a viable option to meet emission targets, planners and policymakers need tools to better understand the implications of such policies on travel behavior. In this paper we present an integrated multimodal travel demand and emission model of four policy strategies; presenting GHG and air pollutant reduction results at a very detailed level. Multiple policy outcomes are compared within a single modeling framework and study area. The results reveal that while no one demand mechanism is likely to reduce emissions to a level that meets policy-maker’s goals; a first-best pricing strategy that incorporates marginal social costs is the most effective emission reduction mechanism. Implementing such a mechanism may offer total emission reductions of up to 24 %. However, the efficacy of this strategy must be weighed against difficulties of establishing efficient pricing, a costly implementation, and substantial negative impacts to non-highway facilities. Decision makers must select a mixture of pricing and land use strategies to achieve emission goals on all road facilities.