Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment

The paper proposes a first-order macroscopic stochastic dynamic traffic model, namely the stochastic cell transmission model (SCTM), to model traffic flow density on freeway segments with stochastic demand and supply. The SCTM consists of five operational modes corresponding to different congestion levels of the freeway segment. Each mode is formulated as a discrete time bilinear stochastic system. A set of probabilistic conditions is proposed to characterize the probability of occurrence of each mode. The overall effect of the five modes is estimated by the joint traffic density which is derived from the theory of finite mixture distribution. The SCTM captures not only the mean and standard deviation (SD) of density of the traffic flow, but also the propagation of SD over time and space. The SCTM is tested with a hypothetical freeway corridor simulation and an empirical study. The simulation results are compared against the means and SDs of traffic densities obtained from the Monte Carlo Simulation (MCS) of the modified cell transmission model (MCTM). An approximately two-miles freeway segment of Interstate 210 West (I-210W) in Los Ageles, Southern California, is chosen for the empirical study. Traffic data is obtained from the Performance Measurement System (PeMS). The stochastic parameters of the SCTM are calibrated against the flow-density empirical data of I-210W. Both the SCTM and the MCS of the MCTM are tested. A discussion of the computational efficiency and the accuracy issues of the two methods is provided based on the empirical results. Both the numerical simulation results and the empirical results confirm that the SCTM is capable of accurately estimating the means and SDs of the freeway densities as compared to the MCS.     

A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models

This paper evaluates the ability of the maximum approximate composite marginal likelihood (MACML) estimation approach to recover parameters from finite samples in mixed cross-sectional and panel multinomial probit models. Comparisons with the maximum simulated likelihood (MSL) estimation approach are also undertaken. The results indicate that the MACML approach recovers parameters much more accurately than the MSL approach in all model structures and covariance specifications. The MACML inference approach also estimates the parameters efficiently, with the asymptotic standard errors being, in general, only a small proportion of the true values. As importantly, the MACML inference approach takes only a very small fraction of the time needed for MSL estimation. In particular, the results suggest that, for the case of five random coefficients, the MACML approach is about 50 times faster than the MSL for the cross-sectional random coefficients case, about 15 times faster than the MSL for the panel inter-individual random coefficients case, and about 350 times or more faster than the MSL for the panel intra- and inter-individual random coefficients case. As the number of alternatives in the unordered-response model increases, one can expect even higher computational efficiency factors for the MACML over the MSL approach. Further, as should be evident in the panel intra- and inter-individual random coefficients case, the MSL is all but practically infeasible when the mixing structure leads to an explosion in the dimensionality of integration in the likelihood function, but these situations are handled with ease in the MACML approach. It is hoped that the MACML procedure will spawn empirical research into rich model specifications within the context of unordered multinomial choice modeling, including autoregressive random coefficients, dynamics in coefficients, space-time effects, and spatial/social interactions.     

Meta-analysis of UK values of travel time: An update

Numerous travel demand studies have been carried out over the past five decades, many of which produce estimates of the value of travel time. This includes a rich body of largely unpublished evidence, which can provide valuable insights into the impact of variables such as GDP, travel distance, purpose and mode on this critical parameter for transport modelling and appraisal. The work reported in this paper updates and extends our previous meta-analyses of UK values of time ( [Wardman, 1998], [Wardman, 2001a] and [Wardman, 2004]) by adding recent studies and widening the range of explanatory variables included. Our current research covers 226 studies carried out between 1960 and 2008, yielding a total of 1749 valuations (a 50% increase relative to our previous work) and making this the largest data set of its kind to the best of our knowledge. This is also the most comprehensive study to date of parameters other than in-vehicle time and includes valuations of walk, wait, headway, congested, free flow, late, departure time shift and search time. Exploratory analysis of the data set provides interesting insights into methodological trends in travel demand modelling.For each valuation, over thirty quantitative and categorical variables were recorded and then included in a multivariate regression model to explain variations in the value of time. A large number of statistically significant effects were obtained from this meta-analysis, some of which are in marked contrast with, or not present in, our previous work. One finding that stands out is that the estimated elasticity of the value of time with respect to GDP per capita is 0.9 and highly significant, a much closer correspondence to the widely used convention of a unit income elasticity over time than we have previously obtained. The ratio between walk and wait time and in-vehicle time was found to be substantially lower than the commonly used value of two. We also found large and significant differences between the results from studies based on different types of Stated Preference survey presentation. Other important effects include variations by mode used, mode valued, travel purpose, attribute type and distance. It is envisaged that the results are of direct relevance in the British context, as inputs to appraisal or for benchmarking, whilst the methodological implications are of broader interest and the results, in terms of time equivalents and variations in values of time, can be transferred to other contexts.     

Optimal design and benefits of a short turning strategy for a bus corridor

We develop a short turning model using demand information from station to station within a single bus line-single period setting, aimed at increasing the service frequency on the more loaded sections to deal with spatial concentration of demand considering both operators’ and users’ costs. We find analytical expressions for optimal values of the design variables, namely frequencies (inside and outside the short cycle), capacity of vehicles and the position of the short turn limit stations. These expressions are used to analyze the influence of different parameters in the final solution. The design variables and the corresponding cost components for operators and users (waiting and in-vehicle times) are compared against an optimized normal operation scheme (single frequency). Applications on actual transit corridors exhibiting different demand profiles are conducted, calculating the optimal values for the design variables and the resulting benefits for each case. Results show the typical demand configurations that are better served using a short turn strategy.     

A conceptual and methodological framework of leisure activity loyalty accommodating the travel context

As leisure travel continues to grow, it has become a critical subject for planners and decision-makers since it significantly impacts regional economic and social development as well as contributes to emission levels and congestion. Despite being a significant percentage of our travel, however, leisure travel behavior is still not very well understood. The goal of this article is to contribute to our understanding of leisure activity participation by considering leisure activity loyalty within the travel context. In particular, this study focuses on one specific dimension of travel context: travel extent (i.e., whether an individual participates in a leisure activity on a daily versus a long-distance basis). As such, this article first introduces a unified conceptual framework for measuring leisure activity loyalties within a travel context, based on two distinct dynamics of leisure loyalty behavior—destination attachment and activity involvement. Additionally, this article uses a unique 2001 NHTS dataset comprised of households’ daily and long-distance leisure activities to undertake a unique empirical analysis of five distinct leisure activities using the conceptual framework and a copula-based model methodology. The findings confirmed that households demonstrate significant loyalties to travel contexts across all leisure activities, especially resting and sightseeing.     

A retrospective and prospective survey of time-use research

The central basis of the activity-based approach to travel demand modeling is that individuals' activity-travel patterns are a result of their time-use decisions within a continuous time domain. This paper reviews earlier theoretical and empirical research in the time-use area, emphasizing the need to examine activities in the context or setting in which they occur. The review indicates the substantial progress made in the past five years and identifies some possible reasons for this sudden spurt and rejuvenation in the field. The paper concludes that the field of time-use and its relevance to activity-travel modeling has gone substantially past the "tip of the iceberg", though it certainly still has a good part of the "iceberg" to uncover. Important future areas of research are identified and discussed.     

The experience of express coach deregulation in Great Britain

This paper reviews the effect of express coach deregulation in Britain following the Transport Act 1980. The authors have monitored the range of services offered before and after the Act, using operators' literature, roadside surveys, on-vehicle passenger interviews and interviews with operators as sources of information. These are used to present an overall picture of express deregulation, with particular reference to changes in real fare levels, and also the relative importance of competition within the coach industry compared with that of inter-modal competition (that between coach and rail). The latter has emerged as more significant.The greater part of the paper is devoted to analysis of the long-distance market but the development of commuter coach services into central London is also examined, together with the reasons why independent operators have secured a larger share of this market.     

Goodness-of-fit measures for probabilistic travel demand models

This paper is concerned with the assessment of the goodness-of-fit of nonlinear models of the type currently being used in the development of the disaggregate, behavioral travel demand approach. These models are emerging as a potential new technique for many transportation planning problems, although much research is yet needed before they are sufficiently developed for operational use. In order to pursue the necessary research, and also for the later assessment of operational models, it is necessary to have adequate measures of the goodness-of-fit.The paper examines the adequacy of standard measures of goodness-of-fit as applied to any nonlinear estimating equation and they are found to be inappropriate and inadequate. A little-known statistic, called the correlation ratio, is then defined and derived, and is explored as a substitute for the standard measures. In both theoretical and empirical tests, the correlation ratio is found to be a significantly more useful and appropriate measure of goodness-of-fit.Some further properties of the correlation ratio are examined, and the ratio is found to possess some degree of arbitrariness when applied to typical travel demand models. This arbitrariness, however, only impairs the usefulness of the correlation ratio in the absolute assessment of a model, but not for the comparative assessment of two or more models. Finally, a number of research tasks, relating to the correlation ratio, are identified.