The determinants of car ownership in England and Wales from anonymous 2001 census data

Within the transportation research literature, the attempt to understand and predict the level of car ownership is probably one of the most popular areas of study. The primary reason for this is understandable, having access to a vehicle increases an individual’s (or their household’s) travel options, leading to greater mobility. Secondary reasons for this scrutiny include the need to predict future transport investment in road infrastructure and the commercial demand for new vehicles. This paper attempts to predict the level of household car ownership as a function of the characteristics of the household and the individuals that make up the household. The primary data source for this study comes from the 2001 United Kingdom Census and the analysis methods used are from the discipline of data mining. The results of this study are in line with those from previous research but show a potential to predict the higher levels of household car ownership with greater accuracy than other similar studies.     

Use of hybrid vehicles in Japan: An analysis of used car market data

Despite the rapid market penetration of hybrid vehicles (HVs), their usage and contributions to environmental protection have not been examined by vehicle traveling data. In this paper, we analyzed Japan’s used car market data to understand how HVs are used on the street. We find GV drivers with high travel demand switched from GVs to HVs during the transition period. Despite HV owners driving much longer distances than conventional gasoline vehicle (GV) owners, they emit less carbon dioxide (CO₂) emissions, owing to better fuel economy. We also find that HV owners spend roughly the same amount of money annually as GV owners. However, the per-kilometer travel cost of HVs is much lower than that of GVs even if the depreciation cost of the vehicle and vehicle related taxes are included in the analysis.     

Electrification of the two-car household: PHEV or BEV?

In previous works, we have shown two-car households to be better suited than one-car households for leveraging the potential benefits of the battery electric vehicle (BEV), both when the BEV simply replaces the second car and when it is used optimally in combination with a conventional car to overcome the BEV’s range limitation and increase its utilization. Based on a set of GPS-measured car movement data from 64 two-car households in Sweden, we here assess the potential electric driving of a plug-in hybrid electric vehicle (PHEV) in a two-car household and compare the resulting economic viability and potential fuel substitution to that of a BEV.Using estimates of near-term mass production costs, our results suggest that, for Swedish two-car households, the PHEV in general should have a higher total cost of ownership than the BEV, provided the use of the BEV is optimized. However, the PHEV will increasingly be favored if, for example, drivers cannot or do not want to optimize usage. In addition, the PHEV and the BEV are not perfect substitutes. The PHEV may be favored if drivers require that the vehicle be able to satisfy all driving needs (i.e., if drivers don’t accept the range and charge-time restrictions of the BEV) or if drivers requires an even larger battery in the BEV to counter range anxiety.We find that, given a particular usage strategy, the electric drive fraction (EDF) of the vehicle fleet is less dependent on whether PHEVs or BEVs are used to replace one of the conventional cars in two-car households. Instead, the EDF depends more on the usage strategy, i.e., on whether the PHEV/BEV is used to replace the conventional car with the higher annual mileage (“the first car”), the less used car (“the second car”), or is used flexibly to substitute for either in order to optimize use. For example, from a fuel replacement perspective it is often better to replace the first car with a PHEV than to replace the second with a BEV.     

Substitution of bus for car travel in urban Britain: an economic evaluation of bus and car exhaust emission and other costs

Car exhaust emissions cause serious air pollution problems in many regions and, at a global level, contribute to climate change. Car use is also an important factor in other problems including traffic congestion, road accidents, noise pollution, community severance, and loss of countryside from road building. Forecasts of further increases in car ownership and use have prompted calls for policy-makers to encourage car users to switch to other forms of transport, particularly the bus. The effects of substituting bus for car travel in urban areas are simulated by specifying a spreadsheet model incorporating two types of car (petrol and diesel engine) and three types of bus (mini-, midi- and large bus). Six types of exhaust emission are considered for each vehicle type for the years 1992, 1995 and 1999: carbon monoxide, volatile organic compounds, nitrogen oxides, sulphur dioxide, (small) particulate matter and carbon dioxide. The paper provides a synthesis of monetary estimates of these exhaust emission and other costs. The other costs considered are traffic congestion, fuel consumption, noise pollution, road accidents and road damage. The exhaust emission monetary cost estimates, mainly from the United States and the United Kingdom, are discussed within the context of a sensitivity analysis which allows for changes in parameters such as load factors, emission factors and the individual exhaust emission cost estimates. The simulation results show that substitution of bus for car travel generally decreases the overall costs, particularly the costs of congestion, but increases exhaust emission costs if bus load factors are insufficiently high. In order to reduce exhaust emission costs from car to bus transfer at given load factors, the most effective policy option is to encourage the reduction of particulate emissions from bus engines. In terms of the overall costs, increasing bus load factors by relatively modest amounts can lead to substantial reductions in these overall costs. These results should be regarded as illustrative rather than definitive, given the uncertainties in a number of parameter estimates and the need for further research in areas not covered by the paper.     

Use of a novel dataset to explore spatial and social variations in car type,size, usage and emissions

The ’MOT’ vehicle inspection test record dataset recently released by the UK Department for Transport (DfT) provides the ability to estimate annual mileage figures for every individual light duty vehicle greater than 3 years old within Great Britain. Vehicle age, engine size and fuel type are also provided in the dataset and these allow further estimates to be made of fuel consumption, energy use, and per vehicle emissions of both air pollutants and greenhouse gases. The use of this data permits the adoption of a new vehicle-centred approach to assessing emissions and energy use in comparison to previous road-flow and national fuel consumption based approaches. The dataset also allows a spatial attribution of each vehicle to a postcode area, through the reported location of relevant vehicle testing stations. Consequently, this new vehicle data can be linked with socio-demographic data in order to determine the potential characteristics of vehicle owners.This paper provides a broad overview of the types of analyses that are made possible by these data, with a particular focus on distance driven and pollutant emissions. The intention is to demonstrate the very broad potential for this data, and to highlight where more focused analysis could be useful. The findings from the work have important implications for understanding the distributional impacts of transport related policies and targeting messaging and interventions for the reduction of car use.     

A field evaluation case study of the environmental and energy impacts of traffic calming

This study quantifies the energy and environmental impact of a selection of traffic calming measures using a combination of second-by-second floating-car global positioning system data and microscopic energy and emission models. It finds that traffic calming may result in negative impacts on vehicle fuel consumption and emission rates if drivers exert aggressive acceleration levels to speed up to their journeys. Consequently by eliminating sharp acceleration maneuvers significant savings in vehicle fuel consumption and emission rates are achievable through driver education. The study also demonstrates that high emitting vehicles produce CO emissions that are up to 25 times higher than normal vehicle emission levels while low emitting vehicles produce emissions that are 15–35% of normal vehicles. The relative increases in vehicle fuel consumption and emission levels associated with the sample traffic calming measures are consistent and similar for normal, low, and high emitting vehicles.     

Recent advances in automotive technology and the cost-effectiveness of fuel economy improvement

The potential for improving the fuel economy of conventional, gasoline-powered automobiles through optimized application of recent technology advances is analyzed. Results are presented at three levels of technical certainty, ranging from technologies already in use to technologies facing technical constraints (such as emissions control problems) which might inhibit widespread use. A fleet-aggregate, engineering-economic analysis is used to estimate a range of U.S. new car fleet average fuel economy levels achievable given roughly 10 years of lead time. Technology cost estimates are compared to fuel savings in order to determine likely cost-effective levels of fuel economy, which are found to range from 39 miles per gallon to 51 miles per gallon depending on technology certainty level. The corresponding estimated increases in average new car price range from $540 to $790 (1993$). Estimated fuel savings payback times average less than 3 years and the cost of conserved energy averages $0.50 per gallon, indicating that these levels of fuel economy improvement are cost-effective over a vehicle lifetime. A vehicle stock turnover model is used to project the reductions in gasoline consumption and associated emissions that would follow if the estimated fuel economy levels are achieved. Potential trade-offs regarding vehicle performance, safety, and emissions are also discussed.     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

A model to design a national high-speed rail network for freight distribution

High-speed rail is often touted as a means to reduce congestion on the United States’ highways by removing passenger car traffic. But highway congestion can also be reduced by reducing the amount of freight traffic. So, given the advances in high-speed rail, the potential exists for developing a national high-speed network for freight distribution. To design such a network considering highway traffic and transit times, we present an uncapacitated network design model with a post-processing step for the capacity constraint. To illustrate how our modeling approach could be used by policy makers to evaluate the impacts of a high-speed rail network, we apply our models with preliminary data on high-speed rail operating parameters for freight applications and from current data on shipments from a major truckload carrier and the US Census Bureau.     

Effect of mass on multimodal fuel consumption in moving people and freight in the U.S.

The United States transportation sector consumes 5 billion barrels of petroleum annually to move people and freight around the country by car, truck, train, ship and aircraft, emitting significant greenhouse gases in the process. Making the transportation system more sustainable by reducing these emissions and increasing the efficiency of this multimodal system can be achieved through several vehicle-centric strategies. We focus here on one of these strategies – reducing vehicle mass – and on collecting and developing a set of physics-based expressions to describe the effect of vehicle mass reduction on fuel consumption across transportation modes in the U.S. These expressions allow analysts to estimate fuel savings resulting from vehicle mass reductions (termed fuel reduction value, FRV), across modes, without resorting to specialized software or extensive modeling efforts, and to evaluate greenhouse gas emission and cost implications of these fuel savings. We describe how FRV differs from fuel intensity (FI) and how to properly use both of these metrics, and we provide a method to adjust FI based on mass changes and FRV. Based on this work, we estimate that a 10% vehicle mass reduction (assuming constant payload mass) results in a 2% improvement in fuel consumption for trains and light, medium, and heavy trucks, 4% for buses, and 7% for aircraft. When a 10% vehicle mass reduction is offset by an increase in an equivalent mass of payload, fuel intensity (fuel used per unit mass of payload) increases from 6% to 23%, with the largest increase being for aircraft.     

Well-to-wheel costs,primary energy demand,and greenhouse gas emissions for the production and operation of conventional and alternative vehicles

This study provides a comprehensive comparison of well-to-wheel (WTW) energy demand, WTW GHG emissions, and costs for conventional ICE and alternative passenger car powertrains, including full electric, hybrid, and fuel cell powertrains. Vehicle production, operation, maintenance, and disposal are considered, along with a range of hydrogen production processes, electricity mixes, ICE fuels, and battery types. Results are determined based on a reference vehicle, powertrain efficiencies, life cycle inventory data, and cost estimations. Powertrain performance is measured against a gasoline ICE vehicle. Energy carrier and battery production are found to be the largest contributors to WTW energy demand, GHG emissions, and costs; however, electric powertrain performance is highly sensitive to battery specific energy. ICE and full hybrid vehicles using alternative fuels to gasoline, and fuel cell vehicles using natural gas hydrogen production pathways, are the only powertrains which demonstrate reductions in all three evaluation categories simultaneously (i.e., WTW energy demand, emissions, and costs). Overall, however, WTW emission reductions depend more on the energy carrier production pathway than on the powertrain; hence, alternative energy carriers to gasoline for an ICE-based fleet (including hybrids) should be emphasized from a policy perspective in the short-term. This will ease the transition towards a low-emission fleet in Switzerland.     

Commuters' concern for the environment and knowledge of the effects of vehicle emissions

Attitudes towards the environment and knowledge of the polluting effects of vehicle emissions were surveyed in 566 train and bus commuters, private motor vehicle commuters and smoky vehicle commuters. Environmental concern was found to significantly correlate with level of contribution to an environmental organisation but not with levels of environmental attitudes or emissions knowledge. Smoky vehicle drivers did not have lower levels of knowledge of emissions or lower levels of environmental concern compared to other private motor vehicle commuters. Train commuters showed no greater concern for the environment than car commuters.     

Impacts of built environment and emerging green technologies on daily transportation greenhouse gas emissions in Quebec cities: a disaggregate modeling approach

This paper aims to investigate the impact of the built environment (BE) and emerging transit and car technologies on household transport-related greenhouse gas emissions (GHGs) across three urban regions. Trip-level GHG emissions are first estimated by combining different data sources such as origin–destination (OD) surveys, vehicle fleet fuel consumption rates, and transit ridership data. BE indicators for the different urban regions are generated for each household and the impact of neighborhood typologies is derived based on these indicators. A traditional ordinary least square (OLS) regression approach is then used to investigate the direct association between the BE indicators, socio-demographics, and household GHGs. The effect of neighborhood typologies on GHGs is explored using both OLS and a simultaneous equation modeling approach. Once the best models are determined for each urban region, the potential impact of BE is determined through elasticities and compared with the impact of technological improvements. For this, various fuel efficiency scenarios are formulated and the reductions on household GHGs are determined. Once the potential impact of green transit and car technologies is determined, the results are compared to those related to BE initiatives. Among other results, it is found that BE attributes have a statistically significant effect on GHGs. However, the elasticities are very small, as reported in several previous studies. For instance, a 10 % increase in population density will result in 3.5, 1.5 and 1.4 % reduction in Montreal, Quebec and Sherbrooke, respectively. It is also important to highlight the significant variation of household GHGs among neighborhoods in the same city, variation which is much greater than among cities. In the short term, improvements on the private passenger vehicle fleet are expected to be much more significant than BE and green transit technologies. However, the combined effect of BE strategies and private-motor vehicle technological improvement would result in more significant GHGs reductions in the long term.     

Exhaust emissions and fuel consumption of a triple-fuel spark-ignition engine powered passenger car

This paper examines the influence of compressed natural gas, liquefied petroleum gas and gasoline fuel on the exhaust emissions and the fuel consumption of a spark-ignition engine powered passenger car. The vehicle was driven according to the urban driving cycle and extra urban driving cycle speed profiles with the warmed-up engine. Cause and effect based analysis reveals potential for using different fuels to reduce vehicle emission and deficiencies associated with particular fuels. The highest tank to wheel efficiency and the lowest CO₂ emission are observed with the natural gas fuelled vehicle, that also featured the highest total hydrocarbon emissions and high NO_x emissions because of fast three way catalytic converter aging due the use of the compressed natural gas. Retrofitted liquefied petroleum gas fuel supply systems feature the greatest air-fuel ratio variations that result in the lowest TtW efficiency and in the highest NO_x emissions of the liquefied gas fuelled vehicle.     

The impact of depot location,fleet composition and routing on emissions in city logistics

This paper investigates the combined impact of depot location, fleet composition and routing decisions on vehicle emissions in city logistics. We consider a city in which goods need to be delivered from a depot to customers located in nested zones characterized by different speed limits. The objective is to minimize the total depot, vehicle and routing cost, where the latter can be defined with respect to the cost of fuel consumption and CO₂ emissions. A new powerful adaptive large neighborhood search metaheuristic is developed and successfully applied to a large pool of new benchmark instances. Extensive analyses are performed to empirically assess the effect of various problem parameters, such as depot cost and location, customer distribution and heterogeneous vehicles on key performance indicators, including fuel consumption, emissions and operational costs. Several managerial insights are presented.     

Influence of vehicle driving parameters on the noise caused by passenger cars in urban traffic

In this work, a sample of vehicles has been instrumented to measure of variables that influence vehicle noise emissions in Madrid. A circuit reproducing a normal travel pattern in large city is traveled by a fleet of vehicle models representing the fleets of cars in a European city. A sample of drivers covers the test track under different traffic conditions. Driving parameters and noise emitted have been recorded in each test and average values have been extracted. These data have been analyzed to define the noise emissions produced by a vehicle in real driving conditions and to identify the noisiest driving behaviors.     

Consumer preferences for alternative fuel vehicles: A discrete choice analysis

This paper analyzes the potential demand for privately used alternative fuel vehicles using German stated preference discrete choice data. By applying a mixed logit model, we find that the most sensitive group for the adoption of alternative fuel vehicles embraces younger, well-educated, and environmentally aware car buyers, who have the possibility to plug-in their car at home, and undertake numerous urban trips. Moreover, many households are willing to pay considerable amounts for greater fuel economy and emission reduction, improved driving range and charging infrastructure, as well as for enjoying vehicle tax exemptions and free parking or bus lane access. The scenario results suggest that conventional vehicles will maintain their dominance in the market. Finally, an increase in the battery electric vehicles’ range to a level comparable with all other vehicles has the same impact as a multiple measures policy intervention package.     

How experience of use influences mass-market drivers’ willingness to consider a battery electric vehicle: A randomised controlled trial

Uptake of electric vehicles (EVs) by consumers could reduce CO₂ emissions from light duty road transport, but little is known about how mass-market consumer drivers will respond to them. Self-Congruity theory proposes that products are preferred whose symbolic meanings are congruent with personal identity. Further, Construal Level theory suggests that only those who are psychologically close to a new product category through direct experience with it can make concrete construals related to their lifestyles; most drivers lack this for EVs. For instance, potential performance benefits of EVs might offset range limitations for consumers who have such direct experience. The effect of direct experience was tested in a randomised controlled trial with 393 mass-market consumer drivers. An experimental group were given direct experience of a modern battery electric vehicle (BEV), and a control group an equivalent conventional car. Despite rating the performance of the BEV more highly than that of the conventional car, willingness to consider a BEV declined after experience, particularly if the range of the BEV considered was short. The participants willing to consider a short-range BEV were those high in self-congruity, for whom the BEV could act as a strong symbol of personal identity.     

Reducing emissions at land border crossings through queue reduction and expedited security processing

Vehicle border crossings between Mexico and the United States generate significant amounts of air pollution, which can pose health threats to personnel at the ports of entry (POEs) as well as drivers, pedestrians, and local inhabitants. Although these health risks could be substantial, there is little previous work quantifying detailed emission profiles at POEs. Using the Mariposa POE in Nogales, Arizona as a case study, light-duty and heavy-duty vehicle emissions were analyzed with the objective of identifying effective emission reduction strategies such as inspection streamlining, physical infrastructure improvements, and fuel switching. Historical traffic information as well as field data were used to establish a simulation model of vehicle movement in VISSIM. Four simulation scenarios with varied congestion levels were considered to represent real-world seasonal changes in traffic volume. Four additional simulations captured varying levels of expedited processing procedures. The VISSIM output was analyzed using the EPA’s MOVES emission simulation software for conventional air pollutants. For the highest congestion scenario, which includes a 200% increase in vehicle volume, total emissions increase by around 460% for PM_2.5 and NO_x, and 540% for CO, SO₂, GHGs, and NMHC over uncongested conditions for a two-hour period. Expedited processing and queue reduction can reduce emissions in this highest congestion scenario by as much as 16% for PM_2.5, 18% for NO_x, 20% for NMHC, 7% for SO₂ and 15% for GHGs and CO. Other potential mitigation strategies examined include fleet upgrades, fuel switching, and fuel upgrades. Adoption of some or all of these changes would not only reduce emissions at the Mariposa POE, but would have air-quality benefits for nearby populations in both the US and Mexico. Fleet-level changes could have far-reaching improvements in air quality on both sides of the border.     

Economic costs and environmental impacts of alternative fuel vehicle fleets in local government: An interim assessment of a voluntary ten-year fleet conversion plan

Vehicle fleets are widely viewed by policy makers as attractive first markets for introduction of alternative fuel technologies. Although, it is essential to understand the environmental benefits and economic challenges involved in fleet conversion, the literature provides little understanding of the implementation issues associated with alternative fuel vehicles. This paper examines the cost effectiveness and environmental impact of the conversion of a 180 plus vehicle fleet to alternative fuel vehicle technologies by a public organization at the mid-point of the project implementation. Using multi-year micro data on fuel usage, operational and capital expenditures, mileage and emissions, the paper examines conversion costs and infrastructure investments required, extent of user adoption, and emissions reductions achieved. Results are discussed in terms of their implications for managerial practice in local government fleet agencies and for future research.