A meta-model of vehicle ownership choice parameters

This paper builds a meta-model of vehicle ownership choice parameters to predict how their values might vary across extended periods as a function of macroeconomic variables. Multinomial logit models of vehicle ownership are estimated from repeated cross-sectional data between 1971 and 1996 for large urban centers in Ontario. Three specifications are tested: a varying constants (VC) model where the alternative specific constants are allowed to vary each year; a varying scales (VS) model where the scale parameter varies instead; and a varying scales and constants model. The estimated parameters are then regressed on macroeconomic variables (e.g., employment rate, gas prices, etc.). The regressions yield good fit and statistically significant results, suggesting that changes in the macroeconomic environment influence household decision making over time, and that macroeconomic information could potentially help predict how model parameters evolve. This implies that the common assumption of holding parameters constant across forecast horizons could potentially be relaxed. Furthermore, using a separate validation dataset, the predictive power of the VC and VS models outperform conventional approaches providing further evidence that pooling data from multiple periods could also produce more robust models.     

The relationship between transportation vulnerability,school attendance,and free transportation to an afterschool program for youth

Transportation - Transportation vulnerability, defined as lack of access to transportation resulting in financial, social, or health consequences, reduces quality of life. While research has...     

Efficiency of urban public transit: A meta analysis

The aim of this paper is twofold. First, to provide a statistical overview of the literature on public transit efficiency performance. Second, to statistically explain the variation in efficiency findings reported in the literature. To this end, first some key concepts of efficiency analysis will be introduced, while next the different frontier methodologies that are used in the literature will be discussed. The empirical part of this paper consists of a statistical summary of the literature as well as meta-regression analyses for different samples of the literature in order to identify key determinants of technical efficiency (TE) of public transit operators. For a broad sample of observations, we found significant and consistent effects of the type of database, region and output measurement method. For the sample of non-parametric studies we found that the type of frontier assumptions also have an impact on the efficiency ratio. Further results show that there is no statistical difference in TE ratios between parametric and non-parametric studies. Finally, we found a positive univariate relationship between the number of inputs in the estimated specification and the efficiency ratio.     

An automatic segmentation procedure for studying variations in mode choice behaviour

Urban areas are very complex and heterogeneous in terms of their population composition and activity systems. The transport system, modal choices and service levels available to the population also varies considerably across space and time. These similarities and differences in choices and levels of explanatory variables facing individual tripmakers have to be explicitly considered in any study of transport behvior. The common practice has been to include user attributes, in addition to the system characteristics, in the modal utility functions to help capture differences in choice behavior across individuals. However, it could well be that the mode-choice behavior of a segment of the population is fundamentally different from other segments of the population. In view of this, some studies have applied segmentation schemes to help identify the subgroups of presumably different travel responses. Typically, such schemes have been based on stratification of the population by a single variable, chosen either based on a priori notions or one-way cross tabulations. These have their shortcomings. Thus, this paper develops an analytical procedure that simultaneously deals with level of service, socioeconomic and spatial factors to determine the relative role each plays in determining travel behavior. The procedure is applied to data from the Toronto region to illustrate its use.     

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<正>加装说明:本文和大家分享一下奔驰新款CLA200加装倒车影像后视摄像头(如图1所示)的方法和步骤。此加装适用奔驰新款CLA200,型号117.3。加装步骤:此步骤总体来说分为两大类即拆卸和安装,那么我们先来说拆卸部分。1.将前排乘客座椅向后移动。2.关闭点火开关,取下遥控钥匙。3.断开蓄电池接地线。4.拆下前车门和右后车门槛装饰条。     

Advances in population synthesis: fitting many attributes per agent and fitting to household and person margins simultaneously

Agent-based microsimulation models of transportation, land use or other socioeconomic processes require an initial synthetic population derived from census data, conventionally created using the iterative proportional fitting (IPF) procedure. This paper introduces a novel computational method that allows the synthesis of many more attributes and finer attribute categories than previous approaches, both of which are long-standing limitations discussed in the literature. Additionally, a new approach is used to fit household and person zonal attribute distributions simultaneously. This technique was first adopted to address limitations specific to Canadian census data, but could also be useful in U.S. and other applications. The results of each new method are evaluated empirically in terms of goodness-of-fit.     

Expert versus lay perception of the risks of motor vehicle-generated air pollution

We explore whether experts’ perceptions of risk differ systematically from those of the public. To do so, we examine whether experts and non-experts make different location decisions in response to ground-level ozone pollution, one of the byproducts of motorized transportation. Physicians are experts in the field of health, and thus may differ from their lay neighbors in their knowledge of and attitude toward pollution and its health risks. If so, it is possible that they value locations with cleaner air differently than their neighbors do. Here we use hedonic price models based on willingness to bear housing and commute burdens to examine the differential valuation of clean air by doctors and laypeople in the Los Angeles region between 1980 and 2000. We find no evidence that doctors are more or less more willing than comparable lay residents to trade off time or money to live in cleaner-air neighborhoods.     

Revisiting the relationship between traffic congestion and the economy: a longitudinal examination of U.S. metropolitan areas

Conventional transportation practices typically focus on alleviating traffic congestion affecting motorists during peak travel periods. One of the underlying assumptions is that traffic congestion, particularly during these peak periods, is harmful to a region’s economy. This paper seeks to answer a seemingly straightforward question: is the fear of the negative economic effects of traffic congestion justified, or is congestion merely a nuisance with little economic impact? This research analyzed 30 years of data for 89 US metropolitan statistical areas (MSAs) to evaluate the economic impacts of traffic congestion at the regional level. Employing a two-stage, least squares panel regression model, we controlled for endogeneity using instrumental variables and assessed the association between traffic congestion and per capita gross domestic product (GDP) as well as between traffic congestion and job growth for an 11-year time period. We then investigated the relationship between traffic congestion and per capita income for those same 11 years as well as for the thirty-year time period (1982–2011) when traffic congestion data were available. Controlling for the key variables found to be significant in the existing literature, our results suggest that the potential negative impact of traffic congestion on the economy does not deserve the attention it receives. Economic productivity is not significantly negatively impacted by high levels of traffic congestion. In fact, the results suggest a positive association between traffic congestion and per capita GDP as well as between traffic congestion and job growth at the MSA level. There was a statistically insignificant effect on per capita income. There may be valid reasons to continue the fight against congestion, but the idea that congestion will stifle the economy does not appear to be one of them.

     

Effects of land-use transport scenarios on travel patterns: a multi-state supernetwork application

Understanding travellers’ response is essential to address policy questions arising from spatial and transport planning sectors. This paper demonstrates the usefulness of the multi-state supernetwork approach to investigate the effects of land-use transport scenarios on individuals’ travel patterns. In particular, it illustrates that multi-state supernetworks are capable of representing activity-travel patterns at a high level of detail, including the choice of mode, route, parking and activity location. Multi-faceted activity-travel preferences can be accommodated in supernetworks. Using a micro-simulation approach, the adaptation of individuals’ travel patterns to policies can be readily captured. The illustration concerns hypothetical land-use and transport scenarios for the city of Rotterdam (The Netherlands), focusing on accessibility changes, modal substitution and shift in the use of transport and location facilities.     

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.