Vehicle Holdings Research Articles

Does license plate rule induce low-carbon choices in residents’ daily travels: Motivation and impacts

With increasing traffic and corresponding environmental problems, the measure of license plate rule has adopted on travel restriction in urban cities of China. This paper uses large-scale survey data to make an independent test and estimation model to analyse whether the vehicle policy of license plate rule has a significant impact on the low-carbon choice of residents' daily travel. The moderate effect for whether the increase in household vehicle holdings weakens the license plate rule policy was also explored in our paper. This study found that the license plate rule policy can induce low-carbon travel, but the impact is inefficient in comparison to the control of household vehicle holdings. The results also showed that household vehicle holdings moderate the impact of license plate rule on low carbon choices of residents’ daily travel. These findings can provide more support for the government when it seeks to make future decisions in low-carbon travel policies.

Impact of road traffic noise on functional connectivity of human brain networks

With the rapid economic development, the rapid increase in motor vehicle holdings, a sharp increase in urban road traffic, road traffic noise exposure is becoming increasingly serious. This paper focuses on the impact of traffic noise exposure on the human brain. We collected road traffic noise sounds of different sound pressure levels (SPLs), and recorded the electroencephalograph (EEG) when subjects exposed under different SPLs’ road noise. Using the graphic theoretical-based EEG method, the effects of road traffic noise with different SPLs on the functional connectivity of human brain networks were studied. Using time-frequency analysis, the beta2 bands was found to be most sensitive frequency band to different SPLs road noise. The brain network characteristic parameters of different SPLs noises were calculated. It is found that in these two frequency bands, the higher the noise SPL, the lower the clustering coefficient and the higher the characteristic path length. In summary, the paper points out the specific effects of road noise with different SPLs on the human brains. It is found that the higher the SPL of noise, the greater the damage to the functional connectivity of the human brain. That means, noise exposure can affect the rate at which the brain processes, analyses, and transmits information. The research results can provide a basis for road noise evaluation and prevention.

Household vehicle holding decisions in response to life cycle events

Abstract People choose a new mobility tool when their mobility needs of change or their current vehicle need replacement. Changes in mobility needs may be triggered by life events. A life event triggers households to reconsider their current vehicle holdings and leads them to change their vehicle holdings if the changing demand makes a changed desirable. Electric cars and car sharing provide new options, which deserve studying in the context of sustainable transport and energy consumption. In the context of re-assessing mobility needs, it is important to better understand the process that leads households to purchase an electric car as a replacement or supplement of their current vehicle, or to join car-sharing. To investigate this decision-making process, a stated choice experiment was designed. This paper reports the results of a mixed logit model, which was estimated to assess the degree of heterogeneity among households in their preferences for vehicle purchase and replacement decisions as a function of life events.

Age, autos, and the value of a statistical life

The value of a statistical life (VSL) is used to assign a dollar value to the benefits of health and safety regulations. Many of those regulations disproportionately benefit older people, but most estimates of the VSL come from hedonic wage regressions with few older workers and no retirees. Using automobile purchase decisions, I estimate a VSL for individuals from the age of 18 up to the age of 85. Combining information on vehicle holdings and use, household attributes, used vehicle prices, crash test results, and yearly fatal accidents for each make, model, and vintage automobile, I calculate a separate willingness to pay for reduced mortality for different age groups. I find a significant inverted-U shape to the age-VSL function that ranges from $1.5 to $19.2 million (in 2009 dollars). The shape and magnitude of the vehicle-based age-VSL relationship corroborate labor market estimates and extend the age range of revealed preference evidence on the relationship between age and the VSL.

Dynamic system optimum simultaneous route and departure time choice problems: Intersection-movement-based formulations and comparisons

In this paper, we propose intersection-movement-based models to formulate dynamic system optimum simultaneous route and departure time choice (DSO-SRDTC) problems over general networks and compare the models with the link-based and path-based counterparts. Each of these three types of models has four variants, which are formed by whether to consider first-in-first-out (FIFO) constraints and non-vehicle holding (NVH) constraints. In all three types of DSO-SRDTC models and their variants, the link transmission model (LTM) is incorporated as their traffic flow model. The DSO-SRDTC problems without FIFO constraints are formulated as linear programming (LP) problems, while the DSO-SRDTC problems with FIFO constraints are formulated as non-convex non-linear programming problems. We find that existing link-based NVH constraints cannot completely eliminate vehicle holding (VH) solutions, and propose both intersection-movement-based and path-based NVH constraints, which can completely eliminate VH solutions. We also prove that the link-based, intersection-movement-based, and path-based models of DSO-SRDTC problems without FIFO constraints are equivalent in terms of obtaining the same optimal total system travel cost (TSTC). However, the three types of models for DSO-SRDTC problems with FIFO constraints can obtain different optimal TSTCs. Based on the solution properties of the DSO-SRDTC problems with FIFO constraints, branch-and-bound algorithms are modified to solve the DSO-SRDTC problems with FIFO constraints for global optima. Numerical examples are set up to demonstrate the properties and performance of the proposed models. To the best of our knowledge, we are the pioneers to provide intersection-movement-based formulations for DSO-SRDTC problems and analyze their mathematical properties.

발사체 지상고정장치 유압시스템 작동 시험 및 결과 분석

발사체 지상고정장치 유압시스템 작동 시험 및 결과 분석

A study of realistic dynamic traffic assignment with signal control, time-scale, and emission

ABSTRACTDynamic Traffic Assignment (DTA) is a mathematical framework that with a System Optimal (SO) objective is often used for long-term transport planning, design, and traffic management. However, the conventional SO-DTA formulation gives optimal solutions having an unrealistic vehicle Holding–Back (HB) property. Existing approaches in the literature aiming to resolve the HB problem are either computationally intractable or suffer from recursive parameter selection problem. In addition, most of the existing Signal Control (SC) models considered in the DTA formulation are mixed-integer or nonlinear in nature that are not scalable for large networks. With an exception, there exists a linear signal control model that can only set signal control cycle-length equal to DTA time-slot duration, and thus trades the accuracy of the SO-DTA solution for a more realistic cycle-length. In this article, we address the above issues by proposing a linear Non-Holding-Back SO-DTA with SC (NHB DTA-SC) formulation for single destination networks. The embedded signal control in the proposed framework enables us to set realistic cycle-length using any DTA time-slot (i.e., flexible time-scale). We find that the time-scale has a significant impact on traffic density which affects vehicle-discharged emissions. To this end, we develop a novel linear Emission-Based DTA with SC (EB DTA-SC) formulation that obtains NHB flows as well as lowest possible emission. Our results show that there is a 32% difference between emission estimated by 60-second and 5-second time-scales.

Addressing the joint occurrence of self-selection and simultaneity biases in the estimation of program effects based on cross-sectional observational surveys: case study of travel behavior effects in carsharing

We estimate the effect of carsharing on travel behavior (specifically, household vehicle holdings, frequency of transit usage, and frequency of biking and walking) using data from the 2011–2012 California Household Travel Survey (CHTS). The effect of carsharing on vehicle ownership is a dynamic process that plays out over a period of time—past ownership influences enrollment decisions, which in turn influence holdings in a later period. Representing this process using cross-sectional data conflates causal effects with simultaneity bias. Further, members and non-members differ in various observed and unobserved ways—demographics, built environment of residential and workplace location, and attitudes—raising the potential for self-selection bias in comparing travel behavior between the two groups given the observational nature of the data. Drawing on established methods for dealing with each bias individually, we develop a method to help control for this joint occurrence of self-selection and simultaneity biases. Restricting the analysis to employed respondents residing in the San Francisco Bay Area, we find that 80% of the observed difference of 0.9 units in average vehicle holdings between carsharing non-members and members may be explained by the biases listed above. The remaining difference of 0.17 units reflects the estimated effect of carsharing, which is the equivalent of shedding one vehicle by about one out of every six households whose member(s) are enrolled in carsharing. The effect on transit usage and walking and biking frequency is positive, albeit small and statistically non-significant. We identify factors that may affect the internal and external validity of our results. Our methods cannot completely replace randomized experiments or panel data. However, the methods used here provide a way to help control for the joint occurrence of self-selection and simultaneity biases, and provide a ballpark estimate of causal effects, for large-scale, general-purpose, cross-sectional datasets such as the CHTS.

발사체용 지상고정장치 구동유압실린더의 운동특성에 관한 해석적 연구

발사체용 지상고정장치 구동유압실린더의 운동특성에 관한 해석적 연구

Using a central Vehicle Holding Compound (VHC) in an open pipeline automotive order fulfilment system: A simulation study

Satisfying requests for specific vehicle variants in a timely manner may increase profit margins for the producer and dealers in the automotive sector and may reduce the need to incentivise customers financially to make a purchase. Open pipeline order fulfilment systems have emerged in this sector to allow dealers to fulfil a customer in a number of ways. Not only can a dealer search its own stock for a suitable match to a customer׳s requested vehicle specification, the dealer can also search for a suitable vehicle in the planning, assembly or distribution pipeline. If a suitable match cannot be found, the dealer can submit a specific Build-to-Order request to the producer. This study examines the impact of adding a central vehicle holding compound (VHC) in such a system. Any dealer can search for a suitable vehicle match in the VHC. A simulation study of a real automotive fulfilment system is conducted to examine the effects on order fulfilment performance of establishing a VHC in a specific market. The simulation model incorporates important features that affect the management and control of the fulfilment system. The study shows that establishing a VHC in an open pipeline system has a significant effect on the level of use of each fulfilment mechanism and on fulfilment performance. A VHC results in significant reductions in lead time but can increase the total stock level in the system if the VHC operating conditions are not determined carefully. The implications of the findings are discussed in detail. They are valuable in providing a base line to consider investment in a VHC and to decide the most appropriate operating policies.

The effect of carsharing on vehicle holdings and travel behavior: A propensity score and causal mediation analysis of the San Francisco Bay Area

We examine the impacts of carsharing on travel behavior utilizing a San Francisco Area subsample of the 2010–2012 California Household Travel Survey. We control for self-selection bias due to differences in observed characteristics of the respondents using propensity-score based matching. We find that vehicle holdings of carsharing members are substantially and significantly lower than for non-members with similar characteristics in terms of individual and household demographics and built environment features of both residential and job location. These differences increase as the propensity to enroll in carsharing programs increases. A latent construct, which measures the propensity to own or utility from owning vehicles and rises with numbers of vehicles owned, is lower for members by 0.3–1.3 standard deviations relative to non-members. Members are also likely to walk, bike, and use transit more frequently than non-members. However, these differences are relatively minor and tend to be statistically non-significant. Future research should control for self-selection bias arising from differences in unobserved characteristics of respondents, as well as simultaneity bias whereby decisions concerning vehicle ownership both influence and are influenced by the decision to join carsharing programs.

Exploration of Short-Term Vehicle Utilization Choices in Households with Multiple Vehicle Types

With the growing concerns of energy sustainability, greenhouse gas emissions, and climate change, there is an increasing interest in understanding vehicle ownership and utilization decisions better so that effective policies can be implemented to reduce the negative impacts of private automobile usage. Although there is a rich body of literature on the long-term decisions of vehicle ownership and the composition of vehicles, the short-term choices of which vehicle to use from the household's vehicle holdings and what distance will be traveled to access opportunities, as well as the interrelationship between the two, are less understood. The purpose of this study was to contribute to the literature on short-term vehicle utilization decisions with the use of data collected in 2009 from the National Household Travel Survey. A latent class segmentation model was estimated with alternate interrelationship structures as the latent classes. Within each latent class, the choices were modeled consistently with the interrelationship structure through the introduction of the first choice as an explanatory variable in the model of the second choice. Additionally, scale was introduced to account for differences in the choices and interrelationships across regions. Most of the model estimation results were behaviorally plausible and consistent with expectations. A significant finding was that interrelationships in both latent classes were insignificant. It was also found that the latent model, even with the insignificant interrelationships, outperformed the alternate model formulations in terms of model fit. This finding shows that the latent segments may capture unobserved heterogeneity beyond the interrelationships.

Examining the Variation of Household Vehicles Holding Behavior in the Chukyo Region in Japan

Japan began initial stage of motorization in 1960s. The motorization made life of human highly dependent on private cars. As a result, vehicle holding behavior in the household might have a change during this process. This study examines the variation of the household vehicles owning behavior in the Chukyo region in Japan. The vehicle type is classified into the light motor car and the ordinary motor one. Meanwhile, the impact of the ownership of trucks is not taken into consideration. The person trip survey data in 1971 and 2001 are used as the sample. A bivariate ordered probit model is proposed for analyzing the ownership of two types of private cars. Since the maximal likelihood estimation method was found to be low efficient, the Gibbs sampler algorithm is implemented in this study. The conclusions of this study are listed as follows. Firstly, age of the householder, numbers of workers and number of members (>= 25 years old) were significant factors with same effects both in 1971 and 2001. Secondly, gender of the householder, district, population density and density of railway stations changed their effects from 1971 to 2001. The households with female householder were unwilling to own the light motor car only in 1971.The residents living in Nagoya would not like to own the ordinary motor car in 2001. Population density and density of railway stations affected ownership of the light motor car only in 2001. Lastly, there was a substitution effect on ownership between the light motor car and the ordinary motor one only in 2001.

Microsimulating Automobile Markets: Evolution of Vehicle Holdings and Vehicle Pricing Dynamics

Vehicle ownership decisions are central to estimates of emissions, gas tax revenues, energy security, pavement management, and other concerns. This work combines an auction-style microsimulation of vehicle prices and random-utility-maximizing choices, producing a market model for the evolution of new and used personal-vehicle fleets. All available vehicles compete directly, with demand, supply, and price signals endogenous to the model. The framework is described, analyzed, and implemented to show its capabilities in predicting outcomes of varying inputs. Application of the model system using Austin, Texas, survey data over a 20-year period highlight the model’s flexibility and reasonable response to multiple inputs, as well as potential implementation issues.

Joint Vehicle Holdings, by Type and Vintage, and Primary Driver Assignment Model with Application for California

In this paper an estimation is made of a joint household-level model of the number of vehicles owned by a household, the vehicle type choice of each vehicle, the annual mileage on each vehicle, and the individual assigned as the primary driver for each vehicle. A version of the proposed model system currently serves as the engine for a household vehicle composition and evolution simulator, which itself has been embedded in the larger Simulator of Activities, Greenhouse Emissions, Energy, Networks, and Travel (SimAGENT), an activity-based travel and emissions forecasting system for the Southern California Association of Governments planning region.

Selling Mobility instead of Cars: New Business Strategies of Automakers and the Impact on Private Vehicle Holding

ABSTRACTThis article considers the business strategy of an automaker entering the car‐sharing market. Given the high growth of the car‐sharing industry, this could become a new business segment and simultaneously have effects on branding. The considered case is a car‐sharing system called car2go, which was launched by Daimler in 2009. An empirical analysis based on primary data (N = 1881) indicates that private vehicles are reduced as a consumer reaction. This constitutes a potential for environmental gains, as shared and consecutively used cars require less of production resources compared to a higher number of private cars being bought, driven and parked individually. Implications for public policy are that the allocation of public space to car‐sharing systems could result in a net gain of space in cities. Policy makers should also consider the dependency of car‐sharing schemes on municipal support regarding parking spaces and they should anticipate the upcoming electrification. This is the first study on a large‐scale car‐sharing system operated by an automaker using retrospective primary data. It contributes to the assessment of the current trend of car manufacturers launching car‐sharing schemes. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.

Abatement cost functions for incentive-based policies in the automobile market

This paper compares the outcomes of policies that target vehicle holdings with those that target vehicle usage using data from the US Consumer Expenditure Survey. Results show that a higher price of gasoline shifts vehicle holdings towards more fuel efficient vehicles and reduces the annual demand for miles, whereas imposing a fee on vehicles or a feebate program only shifts vehicle holdings towards more fuel efficient vehicles and has little to no impact on the demand for miles. While it is relatively expensive to reduce CO 2 emission through incentive-based policies, achieving any abatement level is more expensive through imposing fees on vehicles than gasoline taxes. In addition, the maximum amount of abatement attainable by a feebate program is relatively small and the same amount could be achieved by imposing a $0.73 gasoline tax per gallon.

Joint Modeling of Vehicle Holding Duration and Traveling Distance with a Copula-based Multivariate Survival Model

Joint Modeling of Vehicle Holding Duration and Traveling Distance with a Copula-based Multivariate Survival Model

Estimation of sample selection models with two selection mechanisms

This paper focuses on estimating sample selection models with two incidentally truncated outcomes and two corresponding selection mechanisms. The method of estimation is an extension of the Markov chain Monte Carlo (MCMC) sampling algorithm from Chib (2007) and Chib et al. (2009). Contrary to conventional data augmentation strategies when dealing with missing data, the proposed algorithm augments the posterior with only a small subset of the total missing data caused by sample selection. This results in improved convergence of the MCMC chain and decreased storage costs, while maintaining tractability in the sampling densities. The methods are applied to estimate the effects of residential density on vehicle miles traveled and vehicle holdings in California.

Impact of Carsharing on Household Vehicle Holdings

Carsharing has grown considerably in North America during the past decade and has flourished in metropolitan regions across the United States and Canada. The new transportation landscape offers urban residents an alternative to automobility, one without car ownership. As car-sharing has expanded, there has been a growing demand to understand its environmental effects. This paper presents the results of a North American carsharing member survey (N = 6,281). A before-and-after analytical design is established with a focus on carsharing's effects on household vehicle holdings and the aggregate vehicle population. The results show that carsharing members reduce their vehicle holdings to a degree that is statistically significant. The average number of vehicles per household of the sample drops from 0.47 to 0.24. Most of this shift constitutes one-car households becoming carless. The average fuel economy of carsharing vehicles used most often by respondents is 10 mi/gal more efficient than the average vehicle shed by respondents. The median age of vehicles shed by carsharing households is 11 years, but the distribution covers a considerable range. An aggregate analysis suggests that carsharing has taken between 90,000 and 130,000 vehicles off the road. This equates to 9 to 13 vehicles (including shed autos and postponed auto purchases) taken off the road for each carsharing vehicle.