Strategic sampling for large choice sets in estimation and application

Many discrete choice contexts in transportation deal with large choice sets, including destination, route, and vehicle choices. Model estimation with large numbers of alternatives remains computationally expensive. In the context of the multinomial logit (MNL) model, limiting the number of alternatives in estimation by simple random sampling (SRS) yields consistent parameter estimates, but estimator efficiency suffers. In the context of more general models, such as the mixed MNL, limiting the number of alternatives via SRS yields biased parameter estimates. In this paper, a new, strategic sampling scheme is introduced, which draws alternatives in proportion to updated choice-probability estimates. Since such probabilities are not known a priori, the first iteration uses SRS among all available alternatives. The sampling scheme is implemented here for a variety of simulated MNL and mixed-MNL data sets, with results suggesting that the new sampling scheme provides substantial efficiency benefits. Thanks to reductions in estimation error, parameter estimates are more accurate, on average. Moreover, in the mixed MNL case, where SRS produces biased estimates (due to violation of the independence of irrelevant alternatives property), the new sampling scheme appears to effectively eliminate such biases. Finally, it appears that only a single iteration of the new strategy (following the initialization step using SRS) is needed to deliver the strategy’s maximum efficiency gains.     

Freeway drivers’ willingness-to-pay for a distance-based toll rate

This paper applies the contingent valuation method to investigate and estimate the toll rate that freeway drivers are willing-to-pay (WTP) for each unit of distance they travel, after switching from per-entry based to distance-based tolling system. Due to a large portion of respondents who are unwilling to pay a toll at all, we adopt the spike model to avoid estimation errors. The estimation results show that average willingness to pay toll is TWD¹ 0.86/km, which can be refined further to TWD 0.81/km for short distance travelers, TWD 0.93/km for medium distance travelers, and TWD 0.97/km for long distance travelers. Additionally, the WTP toll rate of short distance travelers is significantly different on public holidays but not during peak hours. In contrast, the WTP toll rates of medium and long distance travelers significantly different during peak hours but not on public holidays.     

The Value of a Statistical Life in a Road Safety Context — A Review of the Current Literature

Abstract

This paper summarizes the state-of-the-art for assessing the value of a statistical life (VSL) as a component of the costs of road accidents. It focuses on the most popular approaches for assessing the VSL, with respect to its theoretical foundations, current state-of-research and empirical evidence. Our paper also provides a first (to our knowledge) compendium of results for the VSL based on Stated Choice (SC) methods. Among the analysed alternatives, the willingness-to-pay (WTP) appears to be the leading approach for assessing the VSL and the SC methods represent the current state-of-the-art for determining the WTP for non-market goods. We conclude that the SC approach overcomes some of the most important shortcomings of the alternative approaches and offers a significant flexibility that can be used to address its own limitations. We also identify a significant need for research, as a gap between the methods employed in research (SC methods) and the state-of-the-practice (other methods) has emerged.     

A note on the consistent aggregation of nested logit demand functions

The present paper derives a set of rules allowing for the consistent aggregation of nested logit travel demand functions across origin and destination zones. Presented aggregation rules are derived for the case when the mode choice is performed conditional on destination choice. The derivation is based on the principles of consistency between aggregate and disaggregate travel demand models introduced by Sweet as well as upon the sampling theory.     

Estimation of value of travel time reliability

In mode choice decision, travelers consider not only travel time but also reliability of its modes. In this paper, reliability was expressed in terms of standard deviation and maximum delay that were measured based on triangular distribution. In order to estimate value of time and value of reliability, the Multinomial and Nested Logit models were used. The analysis results revealed that reliability is an important factor affecting mode choice decisions. Elasticity is used to estimate the impacts of the different policies and system improvements for water transportation mode. Among these policies, decision maker can assess and select the best alternative by doing the benefit and cost analysis based on a new market share, the value of time, and the value of reliability. Finally, a set of promising policies and system improvement of the water transportation were proposed.     

Formal scientific research of traffic collision data utilizing GIS

This paper explores the tenuous link between speeding behavior and accident causation, one that has not been well established in the international literature to date. Taking advantage of established engineering conventions and formulae, we were able to set up an a priori hypothesis suitable for testing. Utilizing this formal scientific method (which GIS researchers have been criticised for not using) we establish a statistical link for this relationship. Our methodology can be used to support all police intervention strategies, including the controversial photo radar systems. The results from our research have been entered into a GIS in order to create a map for spatial display. This map illustrates the relative probability or risk of collision occurrence resulting from speeding at all intersections and interchanges within the scope of the study. It is suggested that this methodology could easily be maintained with periodic updates of data, thus creating a dynamic model from which to monitor traffic safety within the city. Furthermore, this model can be utilized to study specific strategies, allowing for the scrutiny of before, during and after effects. The study area is the entire city of Calgary, Alberta, Canada, and includes all traffic collisions occurring during the year of 1994.     

An improved Dial's algorithm for logit-based traffic assignment within a directed acyclic network

Abstract

Dial's algorithm is one of the most effective and popular procedures for a logit-type stochastic traffic assignment, as it does not require path enumeration over a network. However, a fundamental problem associated with the algorithm is its simple definition of ‘efficient paths’, which sometimes produces unrealistic flow patterns. In this paper, an improved algorithm based on the route extension coefficient is proposed in order to circumvent this problem, in which ‘efficient paths’ simultaneously consider link travel cost and minimum travel cost. Path enumeration is still not required and a similar computing efficiency with the original algorithm is guaranteed. A limitation of the algorithm is that it can only be applied to a directed acyclic network because a topological sorting algorithm is used to decide the order of the sequential calculation. A numerical example based on the Beijing subway network illustrates the effectiveness of the proposed algorithm. It is found that it is able to exclude most unrealistic paths, but include all reasonable paths when compared with path enumeration and the original Dial's algorithm.     

Choice valuation of traffic restrictions: Noise, pollution, and congestion preferences. A note

This Note looks at the choice valuation restrictions on traffic entering the city of Lisbon, based on individual preferences in relation to noise, pollution and congestion. The analysis employs a questionnaire distributed in 2007 to ascertain the significant characteristics of traveling to Lisbon, with the aim of curbing the number of cars that are associated with the probability of individuals supporting a charge on motor vehicles entering the city. The model also takes into account the uncontrolled heterogeneity of the data.     

A study of rail demand in a two‐tier fares environment

A method based on logit analysis is suggested for predicting the effects on patronage and revenue of relative changes in peak and offpeak fares. The method also permits the ready estimation of consequent changes in service profitability. Data was collected specifically for this study from British Rail's Teesside corridor to achieve model calibration. Results show the extent to which demand in peak and offpeak fare‐periods is complementary when fare restrictions are applied only to the morning peak.     

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.     

The multinomial logit model revisited: A semi-parametric approach in discrete choice analysis

The multinomial logit model in discrete choice analysis is widely used in transport research. It has long been known that the Gumbel distribution forms the basis of the multinomial logit model. Although the Gumbel distribution is a good approximation in some applications such as route choice problems, it is chosen mainly for mathematical convenience. This can be restrictive in many other scenarios in practice. In this paper we show that the assumption of the Gumbel distribution can be substantially relaxed to include a large class of distributions that is stable with respect to the minimum operation. The distributions in the class allow heteroscedastic variances. We then seek a transformation that stabilizes the heteroscedastic variances. We show that this leads to a semi-parametric choice model which links the linear combination of travel-related attributes to the choice probabilities via an unknown sensitivity function. This sensitivity function reflects the degree of travelers’ sensitivity to the changes in the combined travel cost. The estimation of the semi-parametric choice model is also investigated and empirical studies are used to illustrate the developed method.