The socio-cognitive links between road pricing acceptability and changes in travel-behavior

The objective of this study is to examine the effect of road pricing on people’s tendency to adapt their current travel behavior. To this end, the relationship between changes in activity-travel behavior on the one hand and public acceptability and its most important determinants on the other are investigated by means of a stated adaptation experiment. Using a two-stage hierarchical model, it was found that behavioral changes themselves are not dependent on the perceived acceptability of road pricing itself, and that only a small amount of the variability in the behavioral changes were explained by socio-cognitive factors. The lesson for policy makers is that road pricing charges must surpass a minimum threshold in order to entice changes in activity-travel behavior and that the benefits of road pricing should be clearly communicated, taking into account the needs and abilities of different types of travelers. Secondly, earlier findings concerning the acceptability of push measures were validated, supporting transferability of results. In line with other studies, effectiveness, fairness and personal norm all had a significant direct impact on perceived acceptability. Finally, the relevance of using latent factors rather than aggregate indicators was underlined.     

The impact of road pricing on housing prices: Preliminary evidence from Milan

Road pricing is increasingly used as an economic tool to decrease the burden of transport externalities. Following the examples of several cities worldwide, on 2nd January, 2008, the city of Milan introduced a charge for accessing the city centre with the aim of curbing air pollution and congestion. The aim of this paper is to evaluate empirically the effect of such a charge on the housing market. By applying a difference-in-differences methodology, I find empirical support for a decrease in housing prices in the coverage area.     

Air pollution dynamics and the need for temporally differentiated road pricing

In this paper we investigate the effects of the temporal variation of pollution dispersion, traffic flows and vehicular emissions on pollution concentration and illustrate the need for temporally differentiated road pricing through an application to the case of the congestion charge in Stockholm, Sweden. By accounting explicitly for the role of pollution dispersion on optimal road pricing, we allow for a more comprehensive view of the economy–ecology interactions at stake, showing that price differentiation is an optimal response to the physical environment. Most congestion charges in place incorporate price bands to mitigate congestion. Our analysis indicates that, to ensure compliance with air quality standards, such price variations should also be a response to limited pollution dispersion.     

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.     

Distributional effects of road pricing: Assessment of nine scenarios for Paris

The starting point of this paper is to consider that there is no general answer to the question of the equity of urban road pricing. We therefore simulate and compare the distributional effects on commuters of nine toll scenarios for Paris, assuming that utility is nonlinear in income. We show that the distributional pattern across income groups depends crucially on the level of traffic reduction induced by tolling. Stringent tolls are more favourable to low-income motorists. Equity effects also vary with toll design. Compared to a reference scenario which uniformly charges all motorists driving within Paris, an inbound cordon toll is detrimental to low-incomes. Conversely, granting a rebate to low CO₂ emission cars slightly improves their situation while an exemption for Paris residents is neutral. Surprisingly, it matters little for social equity whether toll revenues are allocated to all commuters or solely to public transport users.     

Capturing value of reliability through road pricing in congested traffic under uncertainty

Empirical studies showed that travel time reliability, usually measured by travel time variance, is strongly correlated with travel time itself. Travel time is highly volatile when the demand approaches or exceeds the capacity. Travel time variability is associated with the level of congestion, and could represent additional costs for travelers who prefer punctual arrivals. Although many studies propose to use road pricing as a tool to capture the value of travel time (VOT) savings and to induce better road usage patterns, the role of the value of reliability (VOR) in designing road pricing schemes has rarely been studied. By using road pricing as a tool to spread out the peak demand, traffic management agencies could improve the utility of travelers who prefer punctual arrivals under traffic congestion and stochastic network conditions. Therefore, we could capture the value of travel time reliability using road pricing, which is rarely discussed in the literature. To quantify the value of travel time reliability (or reliability improvement), we need to integrate trip scheduling, endogenous traffic congestion, travel time uncertainty, and pricing strategies in one modeling framework. This paper developed such a model to capture the impact of pricing on various costs components that affect travel choices, and the role of travel time reliability in shaping departure patterns, queuing process, and the choice of optimal pricing. The model also shows the benefits of improving travel time reliability in various ways. Findings from this paper could help to expand the scope of road pricing, and to develop more comprehensive travel demand management schemes.     

A forecast air pollution model applied to a hypothetical urban road pricing scheme: An empirical study in Madrid

Reducing the air pollution from increases in traffic congestion in large cities and their surroundings is an important problem that requires changes in travel behavior. Road pricing is an effective tool for reducing air pollution, as reflected currently urban road pricing outcomes (Singapore, London, Stockholm and Milan). A survey was conducted based on establishing a hypothetical urban road pricing system in Madrid (a random sample size n = 1298). We developed a forecast air pollution model with time series analysis to evaluate the consequences of possible air pollution decreases in Madrid. Results reveal that the hypothetical road pricing for Madrid could have highly significant effects on decreasing air pollution outside of the city and in the inner city during the peak operating time periods of maximum congestion (morning peak hours from 7:00 to 10:00 and evening peak hours from 18:00 to 20:00). Furthermore, this system could have significant positive effects on a shift toward using public transport and non-motorized modes inside the hypothetical toll zone. This reveals that the system has a high capacity to motivate a decrease in air pollution and impose more sustainable behavior for public transport users.     

Spatial impacts of road pricing: Accessibility, regional spillovers and territorial cohesion

Road pricing policies are gaining prominence in EU countries. These policies have positive impacts leading to mobility patterns which are socially and environmentally more desirable, but they also have negative impacts. One negative impact is to be found in regional accessibility, due to the increase in generalized transport costs. This study presents a methodology based on accessibility indicators and GIS to assess the accessibility impacts of a road pricing policy. The methodology was tested for the Spain’s road network considering two road pricing scenarios. It enables not only the more penalized regions to be identified but also negative road pricing spillover effects between regions. These effects are measured in terms of accessibility changes occurring in one region produced by charges implemented in another region. Finally, the study of accessibility disparities (by calculating inequality indexes for each of the scenarios considered), provides policymakers with useful information regarding the impact of road pricing policies from the point of view of territorial cohesion.     

Modelling the effects of road pricing on traffic using ERP traffic data

Singapore’s Electronic Road Pricing (ERP) system involves time-variable charges which are intended to spread the morning traffic peak. The charges are revised every three months and thus induce regular motorists to re-think their travel decisions. ERP traffic data, captured by the system, provides a valuable source of information for studying motorists’ travel behaviour. This paper proposes a new modelling methodology for using these data to forecast short-term impacts of rate adjustment on peak period traffic volumes. Separate models are developed for different categories of vehicles which are segmented according to their demand elasticity with respect to road pricing. A method is proposed for estimating the maximum likelihood value of preferred arrival time (PAT) for each vehicle’s arrivals at a particular ERP gantry under different charging conditions. Iterative procedures are used in both model calibration and application. The proposed approach was tested using traffic datasets recorded in 2003 at a gantry located on Singapore’s Central Expressway (CTE). The model calibration and validation show satisfactory results.     

The impact of transport pricing policy on individual energy consumption: a modeling case study in Kumamoto

To investigate the impact of traffic pricing policies on energy consumption, this study shows a microeconomic quantitative analysis scheme to simulate individual consumption behaviors from a microeconomic viewpoint. Energy consumption is estimated based on individual demand of non‐mobility goods and mobility goods under nine policy scenarios based on strategies of gasoline tax adding and mass transit fare reduction independently or combined. Results show that gasoline tax adding has strong effects on consumption behaviors. Energy consumption reduces mostly because of less consumption of non‐mobility goods and car trips. However, policy of mass transit fare reduction has limited impact on energy saving because consumption of non‐mobility goods and mass transit trips increases, but the number of car trips decline by only a small percentage. Comparing with single‐type policy, policies that combined gasoline tax adding and mass transit fare reduction show less energy consumption. Findings suggest that policies that increase cost of car trips, such as gasoline tax adding, are very helpful to reduce the consumption of non‐mobility goods and car trips, which contribute to less energy consumption. However, reducing cost of mass transit trips suggests limited effect on energy saving. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Distributional impacts of road pricing: The truth behind the myth

This paper shows that road pricing can be regressive, progressive or neutral, and refutes the generalised idea that road pricing is always regressive. The potential distributional impacts of a road pricing scheme are assessed in three English towns. It is found that impacts are town specific and depend on where people live, where people work and what mode of transport they use to go to work. Initial impacts may be progressive even before any compensation scheme for losers is taken into account. When the situation before the scheme is implemented is such that majority of drivers entering the area where the scheme would operate come from households with incomes above the average, it can be expected that, once the scheme is implemented, these drivers coming from rich households will continue to cross the cordon and will be prepared to pay the charge. In such a case the overall effect will be that on average, rich people will pay the toll and poor people will not.     

Why experience changes attitudes to congestion pricing: The case of Gothenburg

Many cities have seen public support for congestion charges increase substantially after charges have been introduced. Several alternative explanations of this phenomenon have been suggested, but so far little evidence has been available to assess the relative importance of these explanations. We study attitudes to congestion pricing in Gothenburg before and after congestion charges were introduced in January 2013. Attitudes to the charges did indeed become more positive after the introduction, just as in previous cities. Using a two-wave postal survey, we separate contributions to the attitude change from a number of sources: benefits and costs being different than anticipated, use of hypothecated revenues, reframing processes, and changes in related attitudes such as attitudes to environment, equity, taxation and pricing measures in general. We conclude that the dominant reason for the attitude change is status quo bias, rather than any substantial changes in beliefs or related attitudes, although some of these factors also contribute. Contrary to a common belief, nothing of the attitude change is due to benefits being larger than anticipated.     

Benchmarking road safety performance by grouping local territories: A study in the Netherlands

The method of benchmarking provides an opportunity to learn from better performing territories to improve the effectiveness and efficiency of activities in a particular field of interest. Such a field of interest could be road safety. Road safety benchmarking can include several indicators, ranging from performance indicated by crash statistics, to indicators that also account for consequences in costs or the underlying state of the road safety system and relevant organisation and processes at actor level. The structure and culture of a territory is identified as a basic context of road safety performance. This is regarded as important information to use in grouping of territories to get more homogenous or equal and comparable conditions to learn from ‘the best in class’.The main aim of this study is to assess the usability of different groupings using the physical structure for benchmarking road safety performance at local territorial level. A traditional grouping of municipalities in the Netherlands was compared with a simple grouping of these municipalities based on their level of urbanisation and an advanced grouping in which more indicators such as differences in demography, growth and road structure were taken into account. As in other studies, urbanisation showed to be the most predominant structural factor for grouping local territories and related to differences in road safety performance. However, if information would be needed for specific target groups, other factors like age and gender distribution or the distribution of the road network can provide valuable additional insight and better homogenous starting points for benchmarking. Especially benchmarking of rural territories may profit from such extra distinctive characteristics.     

Estimating commuter mode choice: A discrete choice analysis of the impact of road pricing and parking charges

Automobile use leads to external costs associated with emissions, congestion, noise and other impacts. One option for minimizing these costs is to introduce road pricing and parking charges to reduce demand for single occupant vehicle (SOV) use, while providing improvements to alternatives to encourage mode switching. However, the impact of these policies on urban mode choice is uncertain, and results reported from regions where charging has been introduced may not be transferable. In particular, revealed preference data associated with cost recovery tolls on single facilities may not provide a clear picture of driver response to tolls for demand management. To estimate commuter mode choice behaviour in response to such policies, 548 commuters from a Greater Vancouver suburb who presently drive alone to work completed an individually customized discrete choice experiment (DCE) in which they chose between driving alone, carpooling or taking a hypothetical express bus service when choices varied in terms of time and cost attributes. Attribute coefficients identified with the DCE were used in a predictive model to estimate commuter response to various policy oriented combinations of charges and incentives. Model results suggest that increases in drive alone costs will bring about greater reductions in SOV demand than increases in SOV travel time or improvements in the times and costs of alternatives beyond a base level of service. The methods described here provide an effective and efficient way for policy makers to develop an initial assessment of driver reactions to the introduction of pricing policies in their particular regions.     

Just pricing: the distributional effects of congestion pricing and sales taxes

Those who oppose tolls and other forms of road pricing argue that low-income, urban residents will suffer if they must pay to use congested freeways. This contention, however, fails to consider (1) how much low-income residents already pay for transportation in taxes and fees, or (2) how much residents would pay for highway infrastructure under an alternative revenue-generating scheme, such as a sales tax. This paper compares the cost burden of a value-priced road, State Route 91 (SR91) in Orange County, California with the cost burden under Orange County’s local option transportation sales tax, Measure M. We find that although the sales tax spreads the costs of transportation facilities across a large number of people inside and outside Orange County, it redistributes about $3 million (USD) in revenues from less affluent residents to those with higher incomes. The entire Measure M program redistributes an estimated $26 million from low-income residents to the more affluent. Low-income drivers as individuals save substantially if they do not have to pay tolls, but as a group low-income residents, on average, pay more out-of-pocket with sales taxes.

Optimization of transport investment and pricing policies: the role of transport pricing in network design

This paper investigates the role of transport pricing in network design and describes two facts about flow pattern in a transportation system. The first, illustrated by an example of Braess paradox, is that adding a new link to the network does not necessarily minimize the total travel time. The second is that introducing of appropriate toll pricing may reduce not only the total network time but also the travel time for each individual traveller. It follows with the investigations of different system objectives and different pricing policies (only toll pricing and distance‐based pricing are considered), and shows how they affect the system performance and flow pattern. Lastly, a systematic optimization process is proposed for integrated planning of transport network and pricing policies.     

Evaluating the benefits of a combined route guidance and road pricing system in a traffic network with recurrent congestion

When drivers do not have complete information on road travel time and thus choose their routes in a stochastic manner or based on their previous experience, separate implementations of either route guidance or road pricing cannot drive a stochastic network flow pattern towards a system optimum in a Wardropian sense. It is thus of interest to consider a combined route guidance and road pricing system. A road guidance system could reduce drivers' uncertainty of travel time through provision of traffic information. A driver who is equipped with a guidance system could be assumed to receive complete information, and hence be able to find the minimum travel time routes in a user-optimal manner, while marginal-cost road pricing could drive a user-optimal flow pattern toward a system optimum. Therefore, a joint implementation of route guidance and road pricing in a network with recurrent congestion could drive a stochastic network flow pattern towards a system optimum, and thus achieve a higher reduction in system travel time. In this paper the interaction between route guidance and road pricing is modeled and the potential benefit of their joint implementation is evaluated based on a mixed equilibrium traffic assignment model. The private and system benefits under marginal-cost pricing and varied levels of market penetration of the information systems are investigated with a small and a large example. It is concluded that the two technologies complement each other and that their joint implementation can reduce travel time more efficiently in a network with recurrent congestion.     

The interaction between road traffic safety and the condition of sewers laid under roads

The main objective of this paper is to show how the service condition of the underground pipeline infrastructure, especially sewage systems, may contribute to road surface failures such as subsidence, bulging and particularly collapse. The analysis was based on CCTV surveys conducted in Poland to investigate the causes of more than a hundred road surface collapse incidents.The method proposed in this paper enables us to determine the risk of road surface collapse as the product of the category of probability of road collapse caused by damaged sewer pipelines and the weighted arithmetic mean category of their consequences.The key conclusions highlight the causes of road collapse incidents, the scale of the hazards, and the benefits resulting from the application of the proposed method to prioritize roads according to the road collapse risk.     

Exploring the impacts of road surface texture on tyre/road noise - A case study in Hong Kong

The impacts of road surface texture on tyre/road noise are explored by analysing field data applying fast Fourier transform technique to tyre/road noise spectrum analysis. The results indicate that the tyre/road noise can be higher at lower frequency bands but lower at higher bands. Cluster analysis on surface texture in terms of wavelength identified three cluster groups that centred at 1.32 mm, 3.65 mm, and 5.11 mm have different impacts on noise. The shorter wavelength group suppressed tyre/road noise, medium group aggravated it and the high wavelength group were outliers.