The valuation of commuter travel time savings for car drivers: evaluating alternative model specifications

The empirical valuation of travel time savings is a derivative of the ratio of parameter estimates in a discrete choice model. The most common formulation (multinomial logit) imposes strong restrictions on the profile of the unobserved influences on choice as represented by the random component of a preference function. As we progress our ability to relax these restrictions we open up opportunities to benchmark the values derived from simple (albeit relatively restrictive) models. In this paper we contrast the values of travel time savings derived from multinomial logit and alternative specifications of mixed (or random parameter) logit models. The empirical setting is urban car commuting in six locations in New Zealand. The evidence suggests that less restrictive choice model specifications tend to produce higher estimates of values of time savings compared to the multinomial logit model; however the degree of under-estimation of multinomial logit remains quite variable, depending on the context.     

The reliable hub-and-spoke design problem: Models and algorithms

Hub-and-spoke structure is widely adopted in industry, especially in transportation and telecommunications applications. Although hub-and-spoke paradigm demonstrates significant advantages in improving network connectivity with less number of routes and saving operating cost, the failure of hubs and reactive disruption management could lead to substantial recovery cost to the operators. Thus, we propose a set of reliable hub-and-spoke network design models, where the selection of backup hubs and alternative routes are taken into consideration to proactively handle hub disruptions. To solve these nonlinear mixed integer formulations for reliable network design problems, Lagrangian relaxation and Branch-and-Bound methods are developed to efficiently obtain optimal solutions. Numerical experiments are conducted with respect to real data to demonstrate algorithm performance and to show that the resulting hub-and-spoke networks are more resilient to hub unavailability.     

The effect of income on car ownership: evidence of asymmetry

This paper examines the effect of income on car ownership, and specifically the question of hysteresis or asymmetry. Although there is little doubt that rising income leads to higher car ownership, less is understood about the effect of falling income. Traditional demand modelling is based on the implicit assumption that demand responds symmetrically to rising and falling income. The object of this study is to test this assumption statistically. Using a dynamic econometric model relating household car ownership to income, the number of adults and children in the household, car prices and lagged car ownership, income decomposition techniques are employed to separately estimate elasticities with respect to rising and falling income. The equality of these elasticities – no hysteresis – is tested statistically against the inequality – hysteresis – hypothesis. Various functional specifications are tested in order to assure the robustness of the results to assumptions concerning functional form. The estimation is based on cohort data constructed from 1970 to 1995 UK Family Expenditure Surveys, and a pseudo-panel methodology is employed. The results indicate that car ownership responds more strongly to rising than to falling income – there is a ‘stickiness’ in the downward direction. In addition, there is evidence that the income elasticity is not constant, but instead declines with increasing car ownership.     

Some errors in macroscopic traffic models based on car following models

The macroscopic traffic flow models developed from the car following models of Gazis et al. (1961) are shown to have a flaw in that they do not meet certain of the boundary conditions that researchers have said that they do. This does not affect many existing models but, nevertheless, should be cleared up.     

The effects of motivational factors on car use: a multidisciplinary modelling approach

Current transport models usually do not take motivational factors into account, and if they do, it is only implicitly. This paper presents a modelling approach aimed at explicitly examining the effects of motivational factors on present and future car use in the Netherlands. A car-use forecasting model for the years 2010 and 2020 was constructed on the basis of (i) a multinominal regression analysis, which revealed the importance of a motivational variable (viz., problem awareness) in explaining current car-use behaviour separate from socio-demographic and socio-economic variables, and (ii) a population model constructed to forecast the size and composition of the Dutch population. The results show that car use could be better explained by taking motivational factors explicitly into account, and that the level of car use forecast might change significantly if changes in motivations are assumed. The question on how motivational factors could be incorporated into current (Dutch) national transport models was also addressed.     

The value of travel time savings in freight transport: a meta-analysis

Transportation - The value of freight travel time savings (VFTTS) is a monetary value that is considered an important input into cost–benefit analysis and traffic forecasting. The VFTTS is...     

Estimating heterogeneity of car travelers on mode shifting behavior based on discrete choice models

In order to understand the mode shift behavior of car travelers and relieve traffic congestion, a Stated Preference survey has been conducted in the city of Ji'nan in China to analyze bus choice behavior and the heterogeneity of car travelers. Several discrete choice models, including multinomial logit, mixed logit and latent class model (LCM) are developed based on these survey data. A comparative analysis indicates that the LCM has the highest precision and is more suitable to analyze the heterogeneity of car travelers. The LCM divides car travelers into three classes. Different classes have different sets of influencing factors in the model. Policy recommendations are also proposed for those classes to promote bus shift from car travelers based on the model results. Finally, sensitivity analysis on parking fees and fuel cost is carried out on the LCMs under different bus service levels. Car travelers have different sensitivities to the influencing factors. The conclusions indicate that the LCM can reflect the heterogeneity and preferences of car travelers and can be used to understand how to shift the behavior of car travelers and make more effective traffic policy.     

The influence of interview location on the value of travel time savings

The value of travel time savings (VTTS) is used as input in traffic forecasting models and cost-benefit analyses, and it is typically estimated in stated choice studies in which preferences are derived. However, preferences are affected by the recollection of prior experience, and evidence suggests that the recollection of an event is different than the actual experience. Although the choice of interview location is likely to affect how long it has been since the respondents travelled, evidence is somewhat limited on the influence of interview location on VTTS. This paper investigates the role that interview location plays in the VTTS of ferry travellers. We find that the mean value of headway time savings is significantly higher among respondents interviewed onboard ferries than among those interviewed at home. The mean value of onboard time savings is significantly lower among those interviewed onboard the ferries than among those interviewed at home. Failure to take into account the influence of interview location might lead to biased estimates. To the extent that such biased estimates are used in cost-benefit analyses, this bias will affect the calculated welfare effects of changes in frequency and speed on scheduled passenger transport, resulting in suboptimal allocation of public resources.     

谭庆琏:私家车已到该限时候

交通拥堵有没有快速解决之道?谭庆琏的回答是:现阶段,完全解决城市交通拥堵很难,只能是缓解.优先发展城市公共交通是缓解拥堵的战略举措,政府要从战略的高度予以引导.     

Modal split models based on car availability: the application of such models in studies of medium sized towns

This paper discusses the need for a new approach to urban transportation modelling in recognition that at least in medium sized towns the choice of model is largely dominated by car availability.     

Carsharing: the impact of system characteristics on its potential to replace private car trips and reduce car ownership

Transportation - This paper aims to explore the potential of carsharing in replacing private car trips and reducing car ownership and how this is affected by its attributes. To that affect, a...     

The influence of habit formation on modal choice —a Heuristic model

Most modal split models have been based on the assumption of rational behaviour in an individual's choice evaluation of the generalised costs of modal alternatives. This paper integrates conceptual and empirical information from a wide range of sources and points towards an alternative way of looking at modal choice. The main conclusion is that the car is usually perceived as the superior mode for vehicular travel and that the potential user is committed to its use largely through the act of purchasing it. The conceptual structure of a sequential modal split model is outlined as one that is based on a four-stage decision-making framework which considers the role of learning and habit-formation. In the conclusion, the implications of this approach are considered in terms of the conventional modal split and trip generation submodels, and certain policy measures are assessed.     

Breaking car use habits: The effectiveness of a free one-month travelcard

Based on calls for innovative ways of reducing car traffic and research indicating that car driving is often the result of habitual decision-making and choice processes, this paper reports on a field experiment designed to test a tool aimed to entice drivers to skip the habitual choice of the car and consider using—or at least trying—public transport instead. About 1,000 car drivers participated in the experiment either as experimental subjects, receiving a free one-month travelcard, or as control subjects. As predicted, the intervention had a significant impact on drivers’ use of public transport and it also neutralized the impact of car driving habits on mode choice. However, in the longer run (i.e., four months after the experiment) experimental subjects did not use public transport more than control subjects. Hence, it seems that although many car drivers choose travel mode habitually, their final choice is consistent with their informed preferences, given the current price–quality relationships of the various options.     

The corridor problem: Preliminary results on the no-toll equilibrium

Consider a traffic corridor that connects a continuum of residential locations to a point central business district, and that is subject to flow congestion. The population density function along the corridor is exogenous, and except for location vehicles are identical. All vehicles travel along the corridor from home to work in the morning rush hour, and have the same work start-time but may arrive early. The two components of costs are travel time costs and schedule delay (time early) costs. Determining equilibrium and optimum traffic flow patterns for this continuous model, and possible extensions, is termed “The Corridor Problem”. Equilibria must satisfy the trip-timing condition, that at each location no vehicle can experience a lower trip price by departing at a different time. This paper investigates the no-toll equilibrium of the basic Corridor Problem.     

Measuring the potential for automobile fuel savings in the US: The impact of obesity

High rates of oil consumption and obesity in the US have become important socioeconomic concerns. While these concerns may seem unrelated at first, growing obesity rates in the US increase fuel consumption by adding passenger weight to vehicles. This paper estimates the additional amount of fuel (i.e., gasoline) consumed annually by noncommercial passenger highway vehicles in the US due to passenger overweight and obesity. The mathematical model presented in this paper estimates that as many as one billion additional gallons of gasoline are consumed each year due to overweight and obesity in the US, accounting for up to 0.8% of the fuel consumed by these vehicles annually. This additional fuel consumption causes carbon dioxide emissions of up to 20 billion pounds or more, accounting for up to 0.5% of the annual carbon dioxide emissions in the transportation sector.     

The effect of prices and income on car travel in the UK

The objective of this paper is to analyse the factors determining household car travel, and specifically the effects of household income and the prices of cars and motor fuels, and to explore the intertemporal pattern of adjustment. The question of asymmetry in the response to rising and falling income is also addressed. Such asymmetry may be caused by habit or resistance to change or the tendency to acquire habits to consume more easily than to abandon them. The impact of prices, the speed of adjustment and the resistance to change will be important in determining the possibility of influencing travel behaviour and specifically car use. The study utilises repeated cross-section data from the annual UK Family Expenditure Surveys and employs a pseudo-panel methodology. The results are compared with those for car ownership estimated on the basis of similar models.     

Solving a Dynamic User Equilibrium model based on splitting rates with Gradient Projection algorithms

This article shows how Gradient Projection (GP) algorithms are capable of solving with high precision a Dynamic User Equilibrium (UE) model based on Splitting Rates, i.e. turning movements fractions by destination.Dynamic Traffic Assignment (DTA) is formulated as a Variational Inequality problem defined on temporal profiles of arc conditional probabilities that express a sequence of deterministic route choices taken at nodes by road users directed toward each destination.Congestion is represented through a macroscopic traffic model capable to reproduce a range of phenomena having increasing complexity, from links with bottleneck to intersections with spillback. Different time discretizations, from few seconds to few minutes, are also possible, which allows a range of applications from planning to operation.This assignment model, which is fully link based, is proved to be equivalent to a path based formulation. It also allows for the computation of a handy gap function for analyzing convergence to equilibrium.Numerical experiments on test networks are presented, showing that the proposed GP algorithms converge to dynamic equilibrium in a reasonable number of iterations, outperforming the Method of Successive Averages (MSA).