Trip distribution for limited destinations: a case study for grocery shopping trips in the Netherlands

In this paper, we introduce a new trip distribution model for destinations that are not homogeneously distributed. The model is a gravity model in which the spatial configuration of destinations is incorporated in the modeling process. The performance was tested on a survey with reported grocery shopping trips in the Dutch city of Almelo. The results show that the new model outperforms the traditional gravity model. It is also superior to the intervening opportunities model, because the distribution can be described as a function of travel costs, without increasing the computational time. In this study, the distribution was described by a simple function of Euclidean distance, which provides a good fit to the survey data. The slope of the distribution is quite steep. This shows that most trips are made to nearby supermarkets. However, a significant fraction of trips, mainly made by car, still goes to supermarkets further away. We argue that modeling of these trips by the new method will improve traffic flow predictions.     

Parameter transfer of common-metric attributes in choice analysis: implications for willingness to pay

There is a growing literature that promotes the presence of a mix of compensatory and semi-compensatory processing strategies in the way that individuals evaluate packages of attributes in real or hypothetical markets, and make choices. This paper proposes a specification for the utility form in a choice model to test if, given a pair of attributes with a common-metric (e.g., components of travel time or cost), the attribute with the dominating level defines the marginal (dis)utility that is assigned to both attributes. We refer to this processing strategy as a parameter transfer rule. We use a stated choice data set, in the context of car driving individuals choosing between tolled and non-tolled routes, to estimate a mixed logit model which incorporates the presence of the parameter transfer rule and the conventional fully compensatory rule, both existing up to a probability. We find that if this parameter transfer heuristic is part of the mix, the WTP is more than 30% higher, on average, than when only a fully compensatory rule is imposed. We also contrast the parameter transfer rule with other semi-compensatory heuristics which have been investigated in other papers, and show that the finding adds further support to the accumulating evidence that a semi-compensatory attribute processing rules tend to result in higher mean WTP estimates compared to the fully compensatory attribute processing rule.     

Access control policies without inside queues: Their properties and public policy implications

An access control policy that eliminates all queues beyond the entry points to a network has obvious benefits, which include smooth travel and predictable travel times inside the network. Yet it has never been proven, to the best of our knowledge, whether excluding inside queues yields sub-optimal network performance or, in other words, allowing inside queues can actually further reduce the system travel cost. Moreover, it is not clear whether an optimal control policy derived from efficiency considerations can also be a fair policy to all road users. This paper provide answers to these questions in the context of a monocentric network. By analyzing the structure of the access control problem considering all feasible policies (with/without inside queues), we show that the minimal system cost realizable by access control can be obtained without directly solving a non-convex optimization program, and can indeed always be achieved by a control policy excluding all of the inside queues. These optimal policies are defined by a polyhedral set and a Finite Generation Algorithm can be applied to derive the analytical form of this set. The optimal policies are not unique in general, thus making it possible to achieve both minimal system cost and fairness simultaneously.     

Red-light cameras at intersections: Estimating preferences using a stated choice model

Red-light cameras placed at intersections have the potential to increase safety, but they are often viewed as an invasion of privacy. Preferences for these cameras were explored using a stated choice model that presents key attributes of camera placements. Stated choice models involve careful experimental design, akin to experimental control in laboratory settings. A variety of design approaches were used, settling on a composition of the choice sets people face in the survey. To illustrate the approach, an internet survey was used with a convenience sample containing a high percentage of college students. The results show that while not the case independently, as the number of cameras and fines for violators are simultaneously increased, the preferences for one particular red light cameras program are likely to improve.     

Contracting in highway maintenance and rehabilitation: Are spatial effects important?

Highway agencies around the world strive to improve practices for infrastructure maintenance and rehabilitation, using project delivery policies that range from total ‘in-house’ responsibility to complete privatization, with a number of flexible contracting policies such as performance-based contracting, variants of design-build-maintain, and lane rentals among others between these two extremes. In this paper, we present a methodology that duly accounts for underlying spatial effects and estimates the expected cost savings of innovative contracting policies for highway maintenance and rehabilitation relative to in-house execution of these activities. Spatial econometric modeling is used to analyze highway contract data from 49 countries. We also investigate the marginal effects of key explanatory variables on contract cost savings using spatial multipliers. Our findings show that there are significant relationships between cost savings and contract characteristics, and that there is an apparent direct relationship between the average cost savings of contracts in a country and contract average cost savings and contract sizes in neighboring countries.     

Prospects for plug-in hybrid electric vehicles in the United States and Japan: A general equilibrium analysis

The plug-in hybrid electric vehicle (PHEV) may offer a potential near term, low-carbon alternative to today’s gasoline- and diesel-powered vehicles. A representative vehicle technology that runs on electricity in addition to conventional fuels was introduced into the MIT Emissions Prediction and Policy Analysis (EPPA) model as a perfect substitute for internal combustion engine (ICE-only) vehicles in two likely early-adopting markets, the United States and Japan. We investigate the effect of relative vehicle cost and all-electric range on the timing of PHEV market entry in the presence and absence of an advanced cellulosic biofuels technology and a strong (450 ppm) economy-wide carbon constraint. Vehicle cost could be a significant barrier to PHEV entry unless fairly aggressive goals for reducing battery costs are met. If a low-cost PHEV is available we find that its adoption has the potential to reduce CO₂ emissions, refined oil demand, and under a carbon policy the required CO₂ price in both the United States and Japan. The emissions reduction potential of PHEV adoption depends on the carbon intensity of electric power generation. Thus, the technology is much more effective in reducing CO₂ emissions if adoption occurs under an economy-wide cap and trade system that also encourages low-carbon electricity generation.     

Effect of nozzle orifice diameter on diesel spray tip penetration according to various spray models for CFD simulation with widely varying back pressure

CFD simulations of spray tip penetration with the standard KIVA3V, ‘original gas jet’ and ‘Normal gas jet profile with breakup length formula’ (NGJBL) spray models were performed to investigate the effects of nozzle orifice size and ambient gas density combinations on the spray penetration. The accuracy of the CFD simulation results was estimated by comparing them with available experimental data. The ambient gas density was varied in 12 kg/m³ intervals from 12 to 69 kg/m³ for each nozzle orifice diameter. The nozzle orifice diameters used were 119, 140, 183 and 206 mm. A total of 20 cases in the CFD simulations were considered with combinations of the 4 nozzle orifice diameters and 5 ambient gas densities. CFD simulations with the NGJBL spray model were more accurate than those with either the standard KIVA3V or gas jet spray models as the nozzle orifice diameter and ambient gas density was increased. The NGJBL and original gas jet model is more effective in predicting the spray tip penetration near the nozzle tip region.     

An examination of the determinants of day-to-day variability in individuals' urban travel behavior

Day-to-day variability in individuals' travel behavior (intrapersonal variability) has been recognized in conceptual discussions, yet the analysis and modeling of urban travel are typically based on a single day record of each individual's travel. This paper develops and examines hypotheses regarding the determinants of intrapersonal variability in urban travel behavior.Two general hypotheses are formulated to describe the effects of motivations for travel and related behavior and of travel and related constraints on intrapersonal variability in weekday urban travel behavior. Specific hypotheses concerning the effect of various sociodernographic characteristics on intrapersonal variability are derived from these general hypotheses. These specific hypotheses are tested empirically in the context of daily trip frequency using a five-day record of travel in Reading, England.The empirical results support the two general hypotheses. First, individuals who have fewer economic and role-related constraints have higher levels of intrapersonal variability in their daily trip frequency. Second, individuals who fulfil personal and household needs that do not require daily participation in out-of-home activities have higher levels of intrapersonal variability in their daily trip frequency.     

Urban travel demand: The impact of Box-Cox transformations with nonspherical residual errors

We develop an algorithm for solving regression models with Box-Cox transformations on both the dependent and independent variables, while simultaneously taking into account corrections for serial correlation of several orders and for heteroscedasticity. The latter correction is of a general form which contains as special cases most specifications of heteroscedasticity found in practice. We apply the procedure to three urban travel demand functions, two of which are currently used in their linear form by the Montreal Transit Authority, and analyze more than 100 specifications. Our results show that taking into account nonsphericalness of the residuals has a major impact on model parameter estimates, notably on those which determine the functional form of the model, and that, conversely, modifications of the functional form have strong implications for both the structure of autocorrelation and the importance of heteroscedasticity; moreover, we find interactions between autocorrelation and heteroscedasticity structures. We introduce a special measure of elasticity for variables which contain zero observations, particularly dummy variables. Moreover, we find that elasticities of demand and implicit values of time depend to a large extent on the stochastic specification of the model.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.