Required traffic micro‐simulation runs for reliable multivariate performance estimates

Previous methods to calculate the minimum number of traffic micro‐simulation runs do not consider multiple measures of performance simultaneously at an overall confidence level, which can lead to unreliable simulation outputs. This paper describes new methodologies for calculating the minimum number of traffic micro‐simulation runs for multivariate estimates at an overall confidence level. Simultaneous confidence intervals obtained from multiple comparisons in statistical theory such as the Bonferroni inequality and simultaneous confidence interval method are used to estimate multiple measures of performance with allowable errors at an overall confidence level. Measures of performance can be means and standard deviations. Results of numerical analysis based on an example corridor suggest that the proposed methods provide improved means of assessing statistical accuracy of multiple measures of performance. Results also indicate that the minimum number of runs is influenced by not only the sample size issue but also the complexity of the traffic system. Copyright © 2015 John Wiley & Sons, Ltd.     

Introducing Willingness‐to‐pay for Noise Changes into Transport Appraisal: An Application of Benefit Transfer

Abstract

Numerous research studies have elicited willingness‐to‐pay values for transport‐related noise. However, in many industrialized countries including the UK, noise costs and benefits are still not incorporated into appraisals for most transport projects and policy changes. This paper describes the actions recently taken in the UK to address this issue, comprising: primary research based on the city of Birmingham; an international review of willingness‐to‐pay evidence; the development of values using benefit transfers over time and locations; and integration with appraisal methods. Amongst the main findings are: that the willingness‐to‐pay estimates derived for the UK are broadly comparable with those used in appraisal elsewhere in Europe; that there is a case for a lower threshold at 45 dB(A)Leq,18h rather than the more conventional 55 dB(A); and that values per dB(A) increase with the noise level above this threshold. There are significant issues over the valuation of rail versus road noise, the neglect of non‐residential noise and the valuation of high noise levels in different countries. Conclusions are drawn regarding the feasibility of noise valuation based on benefit transfers in the UK and elsewhere, and future research needs in this field are discussed.     

Exploring airline passengers’ willingness to pay for carbon offsets

This study examines airline passengers’ willingness to pay for carbon-offsets. Using the contingent valuation method of double-bounded dichotomous choice format and a survey of over 1000 Taiwanese passengers flying to countries in Asia, Europe, North America, and Oceania to gauge their willingness-to-pay for airline carbon-offsets. The results suggest that despite the trip characteristics and personal background, air travel passengers’ knowledge and perceptions of the carbon-offset scheme also greatly influence the stated willingness to pay.     

Drivers’ willingness-to-pay to reduce travel time: evidence from the San Diego I-15 congestion pricing project

The adoption of congestion pricing depends fundamentally upon drivers’ willingness to pay to reduce travel time during the congested morning peak period. Using revealed preference data from a congestion pricing demonstration project in San Diego, we estimate that willingness to pay to reduce congested travel time is higher than previous stated preference results. Our estimate of median willingness to pay to reduce commute time is roughly $30 per hour, although this may be biased upward by drivers’ perception that the toll facility provides safer driving conditions. Drivers also use the posted toll as an indicator of abnormal congestion and increase their usage of the toll facility when tolls are higher than normal.     

Passengers’ willingness to pay for airport ground access time savings

There are cases when passengers are willing to pay a premium to reduce the travel time, in particular when the trip has to be made. This paper aims to provide insight into factors that determine passengers’ willingness to pay to reduce travel time for their ground access to an airport. A methodology is developed that comprises two steps: the identification of the passengers with zero willingness to pay and from the rest the estimation of the additional price they are willing to pay to reduce their travel time. For the first step a Probit model was formulated and for the second a linear regression model. To this purpose, data has been collected employing stated preference from passengers at the Athens International Airport. It has been found that a high percentage of passengers have zero willingness to pay, and of the remaining ones those using public transport have a significant willingness to pay to reduce access travel time. The methodology and the models are structured in such a way that their transferability to any airport environment is possible, thus providing a useful tool for decisions relating to airport ground access measures.     

Estimating the willingness to pay and value of risk reduction for car occupants in the road environment

In recent years there has been a re-focus on the valuation of a statistical life from the ex post or human capital method to an ex ante willingness to pay (WTP) approach. This is in part a recognition that we may have been undervaluing the cost of fatalities and injuries to society associated with crashes, but also a strong belief in the need to focus on establishing the amount, ex ante, that individuals are willing to pay to reduce the risk of exposure to circumstances that might lead to death or degree of injury on the road network. This study has developed a framework in which to identify the degree of preference heterogeneity in willingness to pay by individuals who are drivers or passengers in cars to avoid being killed or injured. A stated choice experiment approach is developed. The empirical setting is a choice of route for a particular trip that a sample of individuals periodically undertakes in Australia. The particular trip is described in enough detail to provide the respondent with a familiar market environment, providing all the relevant background information required for making a decision. Mixed logit models are estimated to obtain the marginal (dis)utilities associated with each influence on the choice amongst the attribute packages offered in the stated choice scenarios. These estimates are used to obtain the WTP distributions for fatality and injury avoidance, which are then aggregated to obtain estimates of the value of risk reduction (VRR), of which the fatality class is also known as the value of a statistical life (VSL).     

The university workers’ willingness to pay for commuting

Using a dynamic approach, employing data on job mobility, we demonstrate that university workers?? marginal willingness to pay for reducing commuting distance is about ?0.25 per kilometre travelled. This corresponds to a marginal willingness to pay for reducing commuting time of about 75?% of the net average hourly wage. For females, the willingness to pay is substantially higher than for males. It is also substantially higher for workers that work few hours per day, as predicted by theory.     

Intention and willingness to pay for green freight transportation: An empirical examination

The objective of this paper is to explore what motivates consumer intention and willingness to pay for green transportation. The model is based on the theory of planned behavior and explains the relationship between consumer attitude, perceived behavioral control and peer pressure on intention and willingness to pay for a t-shirt that was transported using energy efficient fuel. Data from a survey of U.S. consumers is analyzed. Results suggest consumer attitude and peer pressure are positively associated with intention which is positively associated with willingness to pay. High levels of consumer attitude, perceived behavioral control and intention suggest a positive outlook for organizations investing in green transportation initiatives. Results also suggest a need for organizations and government to market and educate consumers and citizens about the positive implications of green transportation and using energy efficient fuel.     

Electric vehicles and residential parking in an urban environment: Results from a stated preference experiment

This paper presents the results of a preference survey of 1545 respondents’ willingness to purchase electric vehicles (EVs) in Philadelphia. We pay particular attention to respondents’ willingness to pay for convenient charging systems and parking spaces. If the value of dedicated parking substantially outweighs the value of convenient charging systems, residential-based on-street charging systems are unlikely to ever be politically palatable. As expected, respondents are generally willing to pay for longer range, shorter charging times, lower operating costs, and shorter parking search times. For a typical respondent, a $100 per month parking charge decreases the odds of purchasing an EV by around 65%. Across mixed logit and latent class models, we find substantial variation in the willingness to pay for EV range, charge time, and ease of parking. Of note, we find two primary classes of respondents with substantially different EV preferences. The first class tends to live in multifamily housing units in central parts of the city and puts a high value on parking search time and the availability of on-street charging stations. The second class, whose members are likelier to be married, wealthy, conservative, and residing in single-family homes in more distant neighborhoods, are willing to pay more for EV range and charge time, but less for parking than the first group. They are also much likelier to consider purchasing EVs at all. We recommend that future research into EV adoption incorporate neighborhood-level features, like parking availability and average trip distances, which vary by neighborhood and almost certainly influence EV adoption.     

Statistical methods for estimating speed correction factors with confidence intervals for mobile source emissions models

Speed correction factors are an important component of mobile source emissions models. The current “ratio of means” methodology used by the California Air Resources Board (CARB) and the US EPA does not provide estimates of error or account for the dependence in the data. A repeated measures regression method that takes into account the dependence in the data and provides estimates of error is proposed and illustrated using recent emissions data from CARB. A method for calculating confidence intervals for the ratio of means is also derived and illustrated. Using the same dataset, we find that the method currently in use, which fits a polynomial curve to the ratio of mean emissions, slightly underestimates the correction factors when compared with the repeated measures method. However, both methods appear to overestimate values in the middle range of speeds when compared with a method that does not assume a polynomial curve.     

Analyzing loss aversion and diminishing sensitivity in a freight transport stated choice experiment

Choice behaviour might be determined by asymmetric preferences whether the consumers are faced with gains or losses. This paper investigates loss aversion and diminishing sensitivity, and analyzes their implications on willingness to pay and willingness to accept measures in a reference pivoted choice experiment in a freight transport framework. The results suggest a significant model fit improvement when preferences are treated as asymmetric, proving both loss aversion and diminishing sensitivity. The implications on willingness to pay and willingness to accept indicators are particular relevant showing a remarkable difference between symmetric and asymmetric model specifications. Not accounting for loss aversion and diminishing sensitivity, when present, produces misleading results and might affect significantly the policy decisions.     

Inferences on trip matrices from observations on link volumes: A Bayesian statistical approach

Previous methods for estimating a trip matrix from traffic volume counts have used the principles of maximum entropy and minimum information. These techniques implicitly give as little weight to prior information on the trip matrix as possible. The new method proposed here is based on Bayesian statistical inference and has several advantages over these earlier approaches. It allows complete flexibility in the degree of belief placed on the prior estimate of the trip matrix and also allows for different degrees of belief in diffeent parts of the prior estimate. Furthermore under certain assumptions the method reduces to a simple updating scheme in which observations on the link flows successively modify the trip matrix. At the end of the scheme confidence intervals are available for the estimates of the trip matrix elements.     

Stated choice valuation of urban traffic air pollution and noise

In this study environmental problems related to urban traffic are valued by Stated Choice. Stated Choice is a Stated Preference method in which non-market goods are assessed relatively to each other and not in absolute amounts as with the more common Contingent Valuation Method. The use of Stated Choice to estimate people’s willingness to pay to reduce environmental problems caused by road traffic can be seen as an extension of the established use of Stated Choice in transport research. Despite the fact that the results from this study have been used by the Norwegian Public Roads Administration in their cost benefit analyses since 1995, this paper points to the fact that considerable uncertainty remains with regard to (1) the area of validity of the results, (2) the impact on the valuations of interaction effects and other general methodological problems with Stated Preference methods, and (3) problems related to the complex choice situation of Stated Choice.     

A comment on W. Wei and M. Hansen’s benefit estimation in “An aggregate demand model for air passenger traffic in the hub-and-spoke network”

This comment analyzes the demand model and method used by W. Wei and M. Hansen for computing the benefits of an airport capacity extension. The log-linear specification and coefficients of the demand function imply that the airport extension’s positive effect on demand decreases with the volume of traffic and associated congestion. If this unlikely result is accepted, the surplus method used by Wei and Hansen underestimates the users’ investment benefit. The note argues that the marginal willingness to pay for a capacity extension should rather increase with congestion. If this is the case, the method used by Wei and Hansen could actually overestimates the benefit.A better specification would rather allow for a function concave to the origin in order to account for capacity constraints, and also set a maximum finite price. Above all, a fair evaluation of the users’ benefit should be based on a function which explicitly includes a variable, or function of variables, that permits an estimation of the users’ cost of congestion.     

Highway drivers' willingness to pay for speeding violations in Taiwan

This study investigates the effects of various factors on highway drivers' speeding behaviour and estimates the amount of money that a highway driver is willing to pay for speeding violations in Taiwan. The contingent valuation method is applied to measure drivers' preference and to derive the value function of the amount of money. Logit and probit models are estimated to analyse the significant variables influencing speeding behaviour and to calculate the willingness to pay for speeding violations. The research results show that increasing speeding fines is an effective way to reduce illegal driving behaviour on highways. Significant variables affecting highway drivers' speeding behaviour include gender, engine capacity, past offenders in the previous year, and the risk‐seeking characteristics of drivers. Finally, the logit and probit models show that the amounts of money that highway drivers are willing to pay for speeding violations are $US119 and $US116, respectively. Copyright © 2012 John Wiley & Sons, Ltd.     

Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings

In recent years we have seen important extensions of logit models in behavioural research such as incorporation of preference and scale heterogeneity, attribute processing heuristics, and estimation of willingness to pay (WTP) in WTP space. With rare exception, however, a non-linear treatment of the parameter set to allow for behavioural reality, such as embedded risk attitude and perceptual conditioning of occurrence probabilities attached to specific attributes, is absent. This is especially relevant to the recent focus in travel behaviour research on identifying the willingness to pay for reduced travel time variability, which is the source of estimates of the value of trip reliability that has been shown to take on an increasingly important role in project appraisal. This paper incorporates, in a generalised non-linear (in parameters) logit model, alternative functional forms for perceptual conditioning (known as probability weighting) and risk attitude in the utility function to account for travel time variability, and then derives an empirical estimate of the willingness to pay for trip time variability-embedded travel time savings as an alternative to separate estimates of time savings and trip time reliability. We illustrate the richness of the approach using a stated choice data set for commuter choice between unlabelled attribute packages. Statistically significant risk attitude parameters and parameters underlying decision weights are estimated for multinomial logit and mixed multinomial logit models, along with values of expected travel time savings.     

Neural based contingent valuation of road traffic noise

In this paper, we present a new approach to value the willingness to pay to reduce road noise annoyance using an artificial neural network ensemble. The model predicts, with precision and accuracy, a range for willingness to pay from subjective assessments of noise, a modelled noise exposure level, and both demographic and socio-economic conditions. The results were compared to an ordered probit econometric model in terms of the performance mean relative error and obtained 85.7% better accuracy. The results of this study show that the applied methodology allows the model to reach an adequate generalisation level, and can be applicable as a tool for determining the cost of transportation noise in order to obtain financial resources for action plans.     

How flexible is flexible? Accounting for the effect of rescheduling possibilities in choice of departure time for work trips

In departure time studies it is crucial to ascertain whether or not individuals are flexible in their choices. Previous studies have found that individuals with flexible work times have a lower value of time for late arrivals. Flexibility is usually measured in terms of flexible work start time or in terms of constraints in arrival time at work. Although used for the same purpose, these two questions can convey different types of information. Moreover, constraints in departure time are often related not only to the main work activity, but to all daily activities. The objective of this paper is to investigate the effect of constraints in work and in other daily trips/activities on the willingness to shift departure time and the willingness to pay for reducing travel time and travel delay. We set up a survey to collect detailed data on the full 24-hour out-of-home activities and on the constraints for each of these activities. We then built a stated preference experiment to infer preferences on departure time choice, and estimated a mixed logit model, based on the scheduling model, to account for the effects of daily activity schedules and their constraints. Our results show that measuring flexibility in terms of work start time or constraints at work does not provide exactly the same information. Since one-third of the workers with flexible working hours in the survey indicated that they have restrictions on late work-arrival times, their willingness to pay will be overestimated (almost doubled) if flexibility information is asked only in terms of fixed/flexible working hours. This clearly leads to different conclusion in terms of demand sensitivity to reschedule to a later departure time. We also found that having other activities and constraints during the day increases the individuals’ willingness to pay to avoid being late at work, where the presence of constraints on daily activities other than work is particularly relevant for individuals with no constraints at work. The important impact of these findings is that if we neglect the presence of constraints, as is common practise in transport models, it will generally lead to biased value-of-time estimates. Results clearly show that the shift in the departure time, especially towards a late departure time, is strongly overestimated (the predicted shift is more than double) when the effect of non-work activities and their constraints is not accounted for.     

Confidence intervals of willingness-to-pay for random coefficient logit models

Random coefficient logit (RCL) models containing random parameters are increasingly used for modelling travel choices. Willingness-to-pay (WTP) measures, such as the value of travel time savings (VTTS) are, in the case of RCL models estimated in preference space, ratios of random parameters. In this paper we apply the Delta method to compute the confidence intervals of such WTP measures, taking into account the variance–covariance matrix of the estimates of the distributional parameters. The same Delta method can be applied when the model is estimated in WTP space. Compared to simulation methods such as proposed by Krinsky and Robb, the Delta method is able to avoid most of the simulations by deriving partly analytical expressions for the standard errors. Examples of such computations are shown for different combinations of random distributions.     

Users’ perceptions and willingness to pay in interurban toll roads: identifying differences across regions from a nationwide survey in Spain

Users’ acceptability is considered one of the key drivers for the successful implementation of transport policy measures. This is especially crucial in the case of toll roads since they are financed through drivers’ contributions. Previous literature in this field has mainly focused on measuring users’ attitudes towards urban congestion pricing strategies. However limited research has been developed concerning interurban toll roads. Previous research shows that socioeconomic variables are not conclusive to explain users’ perceptions towards tolls. By contrast, other drivers such as regional differences seem to play a more important role, especially when charging conditions within the same nation greatly vary across regions. This paper analyzes regional differences in users’ attitudes within an asymmetrical distribution of the toll road network across regions. Based on a nationwide survey conducted to road users in interurban toll roads in Spain, we develop both a binomial logit and a censored regression (tobit) model to explore drivers’ perceptions and willingness to pay. The research concludes that users from regions with a more extensive tolled network generally show a more negative attitude towards charges, but not necessarily a lower willingness to pay. The paper also points out that an asymmetrical distribution of toll roads across regions may result in negative perceptions among those users perceiving to be unfairly treated when compared to citizens in other regions.