Error and optimism bias in toll road traffic forecasts

Traffic forecasts are employed in the toll road sector, inter alia, by private sector investors to gauge the bankability of candidate investment projects. Although much is written in the literature about the theory and practice of traffic forecasting, surprisingly little attention has been paid to the predictive accuracy of traffic forecasting models. This paper addresses that shortcoming by reporting the results from the largest study of toll road forecasting performance ever conducted. The author had access to commercial-in-confidence documentation released to project financiers and, over a 4-year period, compiled a database of predicted and actual traffic usage for over 100 international, privately financed toll road projects. The findings suggest that toll road traffic forecasts are characterised by large errors and considerable optimism bias. As a result, financial engineers need to ensure that transaction structuring remains flexible and retains liquidity such that material departures from traffic expectations can be accommodated.

The principles of calibrating traffic microsimulation models

Traffic microsimulation models normally include a large number of parameters that must be calibrated before the model can be used as a tool for prediction. A wave of methodologies for calibrating such models has been recently proposed in the literature, but there have been no attempts to identify general calibration principles based on their collective experience. The current paper attempts to guide traffic analysts through the basic requirements of the calibration of microsimulation models. Among the issues discussed here are underlying assumptions of the calibration process, the scope of the calibration problem, formulation and automation, measuring goodness-of-fit, and the need for repeated model runs.

Toll product preferences and implications for alternative payment options and going cashless

There has been a great deal of research on deriving estimates of the value of travel time savings (VTTS) as a way of converting travel time benefits of toll roads relative to free routes into monetary units, the major user benefit in the development of forecasts of traffic and hence revenue streams. By contrast there has been almost no consideration given to identifying the role that various tollroad products play in establishing preferences for toll routes over non-tolled routes. Increasingly tollroads give users the option to pay by cash at a toll booth, by electronic tolling or by a pre- or post-paid debit and credit account system involving vehicle identification. The efficiency gained by electronic tolling for both the users and the operator have resulted in moves in many jurisdictions to eliminate cash collection entirely (or not introduce it when introducing a new tolled road facility), and to introduce a range of pre- and post-payment options. This has been accompanied by a growing move to distance-based charging in some contexts which is more cumbersome to structure with a cash option. This paper investigates current and potential travellers’ preferences for a range of toll products and how much individual’s are willing to pay for very specific toll products. Data from a stated choice experiment is used in a mixed logit model to establish the role that toll products play in the context of offered times and costs of alternative routes, in choosing between alternative ways of paying for the use of tolled routes.

Second best toll and capacity optimisation in networks: solution algorithm and policy implications

This paper looks at the first and second best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (Netw. Spat. Econ., 4(2): 161–179, 2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network.

Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips

This paper analyzes transportation mode choice for short home-based trips using a 1999 activity survey from the Puget Sound region of Washington State, U.S.A. Short trips are defined as those within the 95th percentile walking distance in the data, here 1.40 miles (2.25 km). The mean walking distance was 0.4 miles (0.6 km). The mode distribution was automobile (75%), walk (23%), bicycle (1%), and bus (1%). Walk and bicycle are found less likely as the individual’s age increases. People are more likely to drive if they can or are accustomed to. People in multi-person families are less likely to walk or use bus, especially families with children. An environment that attracts people’s interest and provides activity opportunities encourages people to walk on short trips. Influencing people’s choice of transport mode on short trips should be an important part of efforts encouraging the use of non-automobile alternatives.

Transport models, philosophy and language

The aim of this paper is to encourage debate about the nature of transport modelling. It does so firstly by considering the underlying philosophies of science (apparently) adopted by transport modellers, over a period of more than 50 years, from the 1950s until the present day. The conclusion is that a new philosophy of science needs to be developed, which is more in tune with how transport modelling is actually carried out (as opposed to how early transport modellers thought it ought to be carried out). It is recommended that such a new philosophy perceives transport modelling as a linguistic activity within the overall context of transport planning, which is in turn considered as a communication process. The paper outlines three main approaches that could be taken in this respect, analysing transport models from metaphorical, narrative and aesthetic perspectives. Conclusions are drawn upon the possible future research directions that might follow from the analysis provided in the paper, emphasising the importance of bringing formal philosophical thinking into transport modelling research and practice.

The British colonial ‘divide and rule’ concept: its influence to transport access in inner city of George Town,Penang

George Town, Penang, is the oldest British colonial city in South East Asia. The colonial settlement layout in the inner city area is still intact today. The establishment of George Town as a trading centre had attracted immigrants from all over the world, especially from Asia (Chinese, Indians and Arabs). Recently, George Town has been enlisted under the UNESCO World Heritage Lists as an outstanding example of traditional multi-cultural settlement. The uniqueness of this inner city is that the formation of its urban pattern is the result of ‘divide and rule’ concept adopted by the British authority. Under the ‘divide and rule’ concept, these immigrants were located to settlement areas based on their ethnic background under one leader known as ‘kapitan’ (captain). The study finds that transport access in this inner city was influenced by the ‘divide and rule’ concept. Unlike formation of well-planned gridiron pattern in other British colonial cities such as in North America, Canada and Australia, the formation of the urban pattern in George Town has an irregular gridiron pattern. This type of urban pattern is typical under ‘divide and rule’ concept and this had indirectly influenced the setting and planning of the present street access and transport networks.

How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles

This study explores the relationships between adoption and consideration of three travel-related strategy bundles (travel maintaining/increasing, travel reducing, and major location/lifestyle change), linking them to a variety of explanatory variables. The data for this study are the responses to a fourteen-page survey returned by nearly 1,300 commuting workers living in three distinct San Francisco Bay area neighborhoods in May 1998. We first identified patterns of adoption and consideration among the bundles, using pairwise correlation tests. The test results indicate that those who have adopted coping strategies continue to seek for improvements across the spectrum of generalized cost, but perhaps most often repeating the consideration of a previously-adopted bundle. Furthermore, we developed a multivariate probit model for individuals’ simultaneous consideration of the three bundles. It is found that in addition to the previous adoption of the bundles, qualitative and quantitative Mobility-related variables, Travel Attitudes, Personality, Lifestyle, Travel Liking, and Sociodemographics significantly affect individual consideration of the strategy bundles. Overall, the results of this study give policy makers and planners insight into understanding the dynamic nature of individuals’ responses to travel-related strategies, as well as differences between the responses to congestion that are assumed by policy makers and those that are actually adopted by individuals.

Transportation and land-use preferences and residents’ neighborhood choices: the sufficiency of compact development in the Atlanta region

This paper analyzes the transportation and land-use preference and actual neighborhood choices of a sample of 1,455 residents of metro Atlanta. We develop a stated-preference scale on which desires for neighborhood type are gauged, from preferences for low-density, auto-oriented environments to desires for compact, walkable, and transit-oriented neighborhoods. This scale is then related to desires for change in one’s own neighborhood characteristics after a hypothetical move. If all neighborhood preferences were equally likely to be satisfied, then neighborhood preferences would not be correlated with a desire for change. By contrast, in the current study, stronger preferences for a more walkable environment are associated with greater desire for change in one’s neighborhood characteristics. This suggests an undersupply of compact, walkable, and transit-friendly neighborhood types relative to current demand.

Disentangling the influence of neighborhood type and self-selection on driving behavior: an application of sample selection model

The causality issue has become one of the key questions in the debate over the relationships between the built environment and travel behavior. Although previous studies have tested statistical and/or practical significance of the built environment on travel behavior, few have quantified the relative roles of the built environment and residential self-selection in influencing travel behavior. Using 1,479 residents living in four traditional and four suburban neighborhoods in Northern California, this study explores the causal effect of neighborhood type on driving behavior and its relative contribution to the total influence of neighborhood type. Specifically, this study applied Heckman’s sample selection model to separate the effect of the built environment itself and the effect of self-selection. The results showed that, on average, the effect of neighborhood type itself on driving distance was 25.8 miles per week, which accounted for more than three quarters of the total influence of neighborhood type and 16% of individuals’ overall vehicle miles driven. These results suggest that the effect of the built environment on driving behavior outweighs that of self-selection. This paper also discussed the advantages and weaknesses of applying the Heckman’s model to address the self-selection issue.

Nature or nurture: why do railroads carry greater freight share in the United States than in Europe?

During the 1950s, the share of freight carried by railroads was similar and declining in both the United States and Europe. By 2000, the railroads’ share of freight (measured in ton–kilometers) had reached 38% in the United States while falling to 8% in Europe. This paper examines the reasons for the difference in rail’s share of freight in Europe and the United States. We find that almost 83% of the gap in 2000 is probably due to natural or inherent differences, principally geography, shipment distance, and commodity mix. However, 17% of the gap cannot be explained by these inherent differences and is presumably due to public policies including priority of passenger service, lack of interoperability at borders, service quality and rates, and incentives of the rail operators. We estimate that if that policy gap were closed, railroads’ share of freight in Europe would increase from 8% to 13%.

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

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

Communicating something confidential while travelling by train: the use of a telephone conversation versus silent modes

Wireless ICTs are often used in public transport. Using survey data collected amongst 98 train travellers this article aims to gain insight into important factors that affect train travellers’ intentions to communicate with distant others while travelling. More specifically, the focus is on the decision-making process that leads to the intention to choose for a confidential conversation either via ‘audible’ mobile phone or via ‘silent’ SMS/e-mail. An approach that is related to the Extended Model of Goal-directed Behaviour (EMGB) is applied. Structural equation modelling results indicate that in particular past SMS behaviour, the desire to communicate (goal desire), the perceived efficacy and controllability influence the intention to conduct a confidential phone conversation in the train. The influence of the social environment (e.g. eavesdropping) seems to be less important. Several EMGB constructs are strongly influenced by age. It seems that older respondents have more negative attitudes towards telephoning while travelling by train, and find it more difficult to call other people in such a situation. Finally, they have a lower intention than younger respondents to conduct a confidential conversation over the phone while travelling.

Children’s mode choice for the school trip: the role of distance and school location in walking to school

Rising levels of childhood obesity in the United States and a 75% decline in the proportion of children walking to school in the past 30 years have focused attention on school travel. This paper uses data from the US Department of Transportation’s 2001 National Household Travel Survey to analyze the factors affecting mode choice for elementary and middle school children. The analysis shows that walk travel time is the most policy-relevant factor affecting the decision to walk to school with an estimated direct elasticity of −0.75. If policymakers want to increase walking rates, these findings suggest that current policies, such as Safe Routes to School, which do not affect the spatial distribution of schools and residences will not be enough to change travel behavior. The final part of the paper uses the mode choice model to test how a land use strategy—community schools—might affect walking to school. The results show that community schools have the potential to increase walking rates but would require large changes from current land use, school, and transportation planning practices.

The potential demand for a urban freight consolidation centre

This paper reports the results of a stated-preference study aimed at investigating how transport decisions are made by receivers or by transport operators about the potential use of an urban freight consolidation centre in the city of Fano, Italy. Because there are no revealed preference data, a stated-choice methodology is used. The stated-choice experiments present two alternatives—one using a private vehicle subject to various traffic regulations and one using the urban freight consolidation centre with varying cost and efficiency levels. Conventional discrete choice data modelling shows that the potential demand is influenced mainly by the distance of the parking bay from the shop, by access permit cost, by the service cost of the urban freight consolidation centre, and by the delay in delivery time. Simulations are then performed to assess how the potential demand is affected by various incentives and regulations affecting urban goods distribution.

Railway reforms: do they influence operating efficiency?

This paper considers railway operations in 23 European countries during 1995–2001, where a series of reform initiatives were launched by the European Commission, and analyses whether these reform initiatives improved the efficiency of the railway systems. Efficiency is measured using Multi-directional Efficiency Analysis, which enables investigation of how railway reforms affect the inefficiencies of specific cost drivers. The main findings are that the reform initiatives generally improve technical efficiency but potentially differently for different cost drivers. Specifically, the paper provides empirical evidence that accounting separation is important for improving the efficiency in the use of both material and staff costs, whereas other reforms only influenced one of these factors.

Weekly rhythms in task and time allocation of households

Analysis of household activity scheduling has to date been limited to one-day periods. This paper extends the study of household task allocation to a one-week period. Using a one-week time use survey held under couples in The Netherlands in 2003, the paper proposes indicators for measuring task allocation on a daily and weekly scale and investigates to what extent role expectations, work status and indicators of time pressure influence task allocation patterns. The outcomes suggest that egalitarian role expectations and higher female work status lead to a more balanced allocation of work and households tasks between spouses. More traditional role views and increased time pressure lead to more specialisation and inequality between spouses. Interestingly, households under time pressure apply day-to-day specialisation to arrive at balanced weekly allocation totals.

An analysis of the social context of children’s weekend discretionary activity participation

This paper examines the discretionary time-use of children, including the social context of children’s participations. Specifically, the paper examines participation and time investment in in-home leisure as well as five different types of out-of-home discretionary activities: (1) shopping, (2) social, (3) meals, (4) passive recreation (i.e., physically inactive recreation, such as going to the movies or a concert), and (5) active recreation (i.e., physically active recreation, such as playing tennis or running). The social context of children’s activity participation is also examined by focusing on the accompanying individuals in children’s activity engagement. The accompanying arrangement is classified into one of six categories: (1) alone, (2) with mother and no one else, (3) with father and no one else, (4) with both mother and father, and no one else, (5) with other individuals, but no parents, and (6) with other individuals and one or both parents. The utility-theoretic Multiple Discrete-Continuous Extreme Value (MDCEV) is employed to model time-use in one or more activity purpose–company type combinations. The data used in the analysis is drawn from the 2002 Child Development Supplement (CDS) to the U.S. Panel Study Income Dynamics (PSID). The results from the model can be used to examine the time-use choices of children, as well as to assess the potential impacts of urban and societal policies on children’s activity participation and time-use decisions. Our findings also emphasize the need to collect, in future travel surveys, more extensive and higher quality data capturing the intra- and inter-household interactions between individuals (including children). To our knowledge, the research in this paper is the first transportation-related study to rigorously and comprehensively analyze the social dimension of children’s activity participation.

A hybrid model of fuzzy and AHP for handling public assessments on transportation projects

Having an effective public participation in transportation planning and project development processes has been a major concern for developed countries. In the United States, for instance, all state Departments of Transportation are subject to the Transportation Equity Act (TEA-21) that formally requires public involvement in transportation planning. Since transportation planning involves public resources and values, judgments by the public should play a key role in determining final decisions. Therefore, all these agencies are required not only to disseminate information to the public, but also to solicit and consider public opinion in forming transportation policy. This work presents a decision support model, with public involvement and public oversight, to help policy makers select appropriate transportation projects for implementation. Since focus groups will face multiple objectives and inexact information in the process, a hybrid model of fuzzy logic and analytical hierarchy process (AHP) is proposed. A set of ‘if–then’ rules based on Weber’s psycho-physical law of 1834 is presented to reason from fuzzy numbers to capture essential subjective preferences, pairwise, among the alternatives. The AHP is then incorporated to estimate preference allotments among alternatives. An example application of the suggested method is provided seeking public approval of an appropriate public bus transportation system choosing between one run by municipal authorities and one run by private agencies to show how this procedure works.

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.