Factors of electric vehicle adoption: A comparison of conventional and electric car users based on an extended theory of planned behavior

Increasing the share of battery electric vehicles (BEV) in the total car fleet is regarded as a promising way to reduce local car emissions. Based on online surveys in Denmark and Sweden, this study compares BEV users' (n = 673) and conventional vehicle (CV) users' (n = 1794) socio-demographic profiles, attitudinal profiles, and mobility patterns. In line with previous research, BEV users are typically male, highly educated, have high incomes, and often more than one car in their household. Additionally, BEV users perceive less functional barriers toward BEV use and have more positive attitudes and norms than CV users. The different profiles of these user groups suggest a separate analysis of potential factors of BEV adoption in both groups. In regression analyses, CV and BEV users' intention to use/purchase a BEV is modeled based on factors of the Theory of Planned Behavior extended by personal norm, perceived mobility necessities, and BEV experience. For CV users, symbolic attitudes related to BEVs are the most important factor of intention, while perceived functional barriers in terms of driving range are most relevant for BEV users' intention. How BEV users cope with trips of longer distance seems of particular relevance. In multiple car households, we found the percentage of actual BEV usage related to the type of other cars in the household, perceived functional barriers of BEVs as well as (successful) behavioral adaption to longer trips by BEVs. Based on the results, we discuss ways to increase BEV adoption for current users and non-users.     

Examining individuals preferences for hybrid electric and alternatively fuelled vehicles

This paper examines individuals motivations when purchasing vehicles, focusing upon what factors would encourage individuals to purchase hybrid electrical vehicle (HEV) or alternatively fuelled vehicle (AFV). AFVs in this paper refer to any cars run on alternatives to petrol and diesel. This research attempts to ascertain whether reductions in fuel costs, vehicle registration tax (VRT), or green house gas emissions would encourage individuals to purchase a HEV or an AFV instead of a conventional vehicle. VRT is an Irish tax that is levied on the purchase of new vehicles. One of the motivations to conduct this research was to examine a new car tax and VRT scheme introduced by the Irish government in 2008. This new policy rewards the purchase of environmentally friendly cars, with lower VRT and car tax rates. To understand individuals’ perceptions of these new taxes a survey was sent to recent customers of a car company in Ireland. The survey asked respondents about their recently purchased vehicle and how important they considered vehicle attributes such as environmental performance, fuel cost, and safety, before making their car purchase. The survey also contained a number of stated preference experiments that were designed to ascertain what factors influence individuals’ decisions when purchasing their new car. The results showed that respondents did not rate green house gas emissions or VRT as crucial attributes when purchasing a new vehicle. The vehicle attributes that respondents rated most highly were reliability, automobile safety, fuel costs, and the cost price. The majority of respondents agreed that HEVs and AFVs are better for the environment, cheaper to run than conventional vehicles and would be the vehicle of choice in ten years time.     

A fuel surcharge policy for reducing road traffic greenhouse gas emissions

This paper proposes a car pricing policy based on fuel surcharges in substitution of car ownership taxes for reducing greenhouse gas emissions by cars. The aim of the proposed policy is to change some (fixed) costs of car use that are not perceived at each trip into (variable) costs. The amount of fuel surcharges and the effects of their application on fuel consumption and on GHG emissions are estimated by a model that is able to relate gasoline and diesel consumption with fuel prices. The effects of the proposed policy on fuel consumption and on GHG emissions are estimated for Italy. The results show that car users prefer to shift towards more efficient fuel vehicles than to public transport, producing a significant, but less than expected, reduction of GHG emissions.     

Rural vehicles in China: appropriate policy for appropriate technology

Over 3 million Chinese Rural Vehicles (CRVs) were produced in China in 2002, three times that of conventional passenger cars. Yet these smaller, simpler, indigenous vehicles are virtually unknown outside China. The CRV industry is unusual in that it evolved largely outside the control of government regulation and policy, using local technology and resources. CRVs now consume one fourth of the diesel fuel in China and play an important role in rural development. This paper is the first comprehensive assessment (in English or Chinese) of these vehicles and this remarkable industry. This study documents and analyzes vehicle technology, government policy, environmental impacts, market demand, and industry dynamics. We find that increasing government regulation (mostly for emissions and safety) is having profound effects on the industry, with uncertain implications for the sales and globalization of rural vehicle technology.     

Modeling green vehicle adoption: An integrated approach for policy evaluation

This article employs an integrated discrete-continuous car ownership model to jointly forecast households’ future preferences on vehicle type, quantity and use, and to estimate greenhouse gas (GHG) emissions. The model system is estimated on a dataset collected from a web-based stated preference survey conducted in Maryland in 2014. The data contain vehicle purchase decisions and sociodemographic information of 456 households who were requested to state their future preferences over a 9-year period (2014–2022). In each time period, a respondent is faced to four alternatives that include the current vehicle, a new gasoline vehicle, a new hybrid electric vehicle, and a new battery electric vehicle. Intertemporal choices between conventional and “green” vehicles such as hybrid and electric cars capture dynamics in vehicle purchase decisions. Short run and medium-long run situations were predicted and compared based on the first 4-year data and the entire 9-year data of the dynamic panel. Vehicle GHG emissions were calculated correspondingly. We find the introduction of “green” vehicles makes a positive impact on car ownership and use, especially in a medium-long run. Two “green” taxation policies, gasoline tax and ownership tax, were proposed and their impact on vehicle use and emission reductions was evaluated. Results indicate that: (a) gasoline tax is a more effective way to reduce vehicle miles traveled and GHG emissions and (b) gasoline tax makes a higher impact on car use and emission reductions in the medium-long run, while ownership tax makes a higher impact in the short run.     

A closer look at urban development under the emergence of autonomous vehicles: Traffic,land use and air quality impacts

Autonomous vehicles (AVs) hold great promise for increasing the capacity of existing roadways and intersections, providing more mobility to a wider range of people, and are likely to reduce vehicle crashes. However, AVs are also likely to increase travel demand which could diminish the potential for AVs to reduce congestion and cause emissions of greenhouse gases (GHG) and other air pollutants to increase. Therefore, understanding how AVs will affect travel demand is critical to understanding their potential benefits and impacts. We evaluate how adoption of AVs affects travel demand, congestion and vehicle emissions over several decades using an integrated travel demand, land-use and air quality modeling framework for the Albuquerque, New Mexico metropolitan area. We find that AVs are likely to increase demand and GHG emissions as development patterns shift to the region's periphery and trips become longer. Congestion declines along most roadways as expanded capacity from more efficient AV operation outpaces increasing demand. Most of the population can also expect a reduction in exposure to toxic vehicle emissions. Some locations will experience an increase in air pollution exposure and traffic congestion from changes in land-use and traffic patterns caused by the adoption of AVs.     

Automobile use,fuel economy and CO2 emissions in industrialized countries: Encouraging trends through 2008?

Car use and fuel economy are factors that determine oil demand and carbon dioxide (CO₂) emissions. Recent data on automobile utilization and fuel economy reveal surprising trends that point to changes in oil demand and CO₂ emissions. New vehicle and on-road fleet fuel economy have risen in Europe and Japan since the mid 1990s, and in the US since 2003. Combined with a plateau in per capita vehicle use in all countries analyzed, these trends indicate that per capita fuel use and resultant tail-pipe CO₂ emissions have stagnated or even declined.Fuel economy technology, while important, is not the only factor that explains changes in tested and on-road fuel economy, vehicle efficiency and transport emissions across countries. Vehicle size and performance choices by car producers and buyers, and driving distances have also played significant roles in total fuel consumption, and explain most of the differences among countries. Technology applied to new vehicles managed to drive down the fuel use per unit of horsepower or weight by 50%, yet most of the potential fuel savings were negated by overall increased power and weight, particularly in the US. Similarly, the promise of savings from dieselization of the fleet has revealed itself as a minor element of the overall improvement in new vehicle or on-road fuel economy. And the fact that diesels are driven so much more than gasoline cars, a difference that has increased since 1990, argues that those savings are minimal. This latter point is a reminder that car use, not just efficiency or fuel choice, is an important determinant of total fuel use and CO₂ emissions.We speculate that if the upward spiral of car weight and power slows or even reverses (as has been observed in Europe and Japan) and the now mandatory standards in many countries have the intended effect that fuel use will remain flat or only grow weakly for some time. If real fuel prices of 2008, which rivaled their peaks of the early 1980s, fell back somewhat but still remain well above their early 2000 values. If the prices remain high, this, combined with the strengthened fuel economy standards, may finally lead to new patterns of car ownership, use and fuel economy. However, if fuel prices continue their own stagnation or even decline after the peaks of 2008 and car use starts upward, fuel use will increase again, albeit more slowly.     

Demand for electric vehicles in hybrid households: an exploratory analysis

Previous studies of the potential market for battery electric vehicles (BEVs) from different research streams have failed to converge on a single, robust estimate. What these previous research streams share are untested or implausible assumptions about consumer response to new transportation technology. We frame the BEV purchase decision in terms of a household's entire stock of vehicles, car purchase behavior and travel behavior. Within this framework, households which own both electric vehicles and gasoline vehicles are called ‘hybrid households’. Because nearly all consumers are unfamiliar with the characteristics of BEVs, we designed an interactive interview based on week-long travel diaries, which we call Purchase Intentions and Range Estimation Games (PIREG) to explore hypothetical hybrid household vehicle use. Our primary finding is that consumers' perceived driving range needs are substantially lower than previous hypothetical stated preference studies conclude. We find evidence of a viable market for BEVs with 60 to 100 miles driving range.     

Integrated transportation and energy sector CO2 emission control strategies

This paper analyses the mutual benefits of integrating strategies for future energy and transport CO₂ emissions control. The paper illustrates and quantifies the mutual benefits of integrating the transport and the energy sector in the case of Denmark. Today this issue is very relevant in Denmark due to the high share of fluctuating renewable energy produced in the country. In the future, such issue will apply to other countries who plan to use a high share of renewable energy. In short, the energy sector can help the transport sector to replace oil by renewable energy and combined heat and power production (CHP), while the transport sector can assist the energy system in integrating a higher degree of intermittent energy and CHP. Two scenarios for partial conversion of the transport fleet have been considered. One is battery cars combined with hydrogen fuel cell cars, while the other is the use of biofuel (ethanol) and synthetic fuel (methanol) for internal combustion cars. An increase in the fraction of electricity delivered by fluctuating sources like wind power will lead to excess electricity production and the two aforementioned scenarios have a substantial effect on the decrease of the excess production.     

Modeling different penetration rates of eco-driving in urban areas: Impacts on traffic flow and emissions

Climate change and air quality are two main environmental challenges in metropolitan areas. As road transportation is one of the main contributors, public administrations are facing these problems with a number of complementary policy measures: shift to cleaner modes, new fuels and vehicle technologies, demand management, and the use of information and communication technologies (ICT) applied to transportation. Eco-driving is one of the measures that present large fuel savings at individual level. Although these savings are well documented in the literature, few studies focus on how eco-drivers driving patterns affect the surrounding vehicles and the traffic in general, and more particularly what would be the impact when the number of eco-drivers grows. Using a traffic microsimulation tool, four models in urban context have been built, corresponding to the different types of urban roads. Both the base-case and the parameters setting to simulate eco-driving have been calibrated with real data collected through floating vehicles performing the trips with normal and eco behaviors. In total, 72 scenarios were simulated, varying the type of road, traffic demand, and the percentage of eco-drivers. Then, the CO₂ and NO_x emissions have been estimated through a microscopic emission model. The results show that in scenarios with low or medium demand levels and increasing number of eco-drivers, the effects are positive in terms of emissions. On the other side, with high percentage of eco-drivers and high traffic demand, the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.     

Selecting sustainable electric bus powertrains using multipreference evolutionary algorithms

Constant improvement of vehicle technologies towards more efficient powertrains and reduced pollutant emissions, frequently leads to the increase of the vehicle or fuel costs, compromising its viability. Multi-objective optimization methods are commonly used to solve such problems, finding optimal trade-off solutions relatively conflicting objectives. Nevertheless, vehicle driving performance, is often disregarded from the optimization process or considered only as a fixed constraint. This may raise some issues, which are discussed in this paper: (a) vehicle dynamics are not improved, (b) trade-off optimal solutions are not distinguishable, (c) interesting solutions near constraints limits won´t be considered if constraints are not marginally relaxed.

This paper proposes a method to optimize three electric-drive vehicle options for an urban bus, a battery electric (BEV), a fuel cell hybrid (FC-HEV) and a plug-in hybrid (FC-PHEV), aiming minimum carbon footprint, maximum financial indicator and simultaneously improved driving performance (speed, acceleration, and electric range). The carbon footprint is assessed by a life cycle (LC) approach, considering the impact of the fuel production and use, and vehicle embodied materials; while the financial assessment considers the vehicle and fuel costs. The spherical pruning multi-objective differential evolution algorithm (spMODE-II) is used in the optimization, considering different preference regions within the problem constraints and objectives. The vehicle solutions optimality and suitability are compared with other multi-objective algorithm, NSGA-II.

The FC-HEV achieved the lowest LC emissions (547 g/km), and the FC-PHEV the maximum financial gain (0.19 $/km), while the BEV achieved the best trade-off of solutions.     

Electric and hybrid car use in a free-floating carsharing system

A free-floating carsharing system is a flexible way to provide cars to members in a limited area. This paper discusses the user behavior and choice between electric and hybrid cars in a free-floating system. We use Auto-mobile's transactional and Global Positioning System (GPS) datasets to analyze car use. We develop a binomial logit model to find the probability of choosing an electric car when there is a choice. The analysis reveals that travel distance has a major influence on this probability: electric vehicles are less popular for distances of more than 24 km. Cold temperatures and being a female also decrease the probability, while higher energy level increases odds. The spatial analysis shows a difference in behavior between both car technologies. Trips made by electric cars are less dispersed spatially than those made by hybrid cars.     

New mobility service users' perceptions on electric vehicle adoption

The recent growth of new mobility services such as car-sharing (ZipCar, Car2Go) and ride-hailing (Uber, Lyft) has interesting implications for new vehicle technologies. We explore the users of the services and their relation to electric vehicles preferences by analyzing two large-scale mobility service surveys. A number of categories (car-share usage, ride-hail usage, commute mode, demographics, current vehicle attributes, environmental attitudes, technology attitudes, and life-stage information) are examined in order to determine the likelihood a respondent considers purchasing an electric vehicle in the future. Survey respondents explicitly expressed that exposure to ride-hailing did not increase their propensity for wanting to purchase an electric vehicle in the future. However, we run a full suite of cross-validation models and find that in addition to the typical factors used in modeling preferences, the use of new mobility services statistically increases the predictive power of our model to identify preferences for electric vehicles.     

Socially optimal replacement of conventional with electric vehicles for the US household fleet

In this study, a framework is proposed for minimizing the societal cost of replacing gas-powered household passenger cars with battery electric ones (BEVs). The societal cost consists of operational costs of heterogeneous driving patterns' cars, government investments for charging deployment, and monetized environmental externalities. The optimization framework determines the timeframe needed for conventional vehicles to be replaced with BEVs. It also determines the BEVs driving range during the planning timeframe, as well as the density of public chargers deployed on a linear transportation network over time. We leverage data sets that represent US household driving patterns, as well as the automobile and the energy markets, to apply the model. Results indicate that it takes 8 years for 80% of our conventional vehicle sample to be replaced with electric vehicles, under the base case scenario. The socially optimal all-electric driving range is 204 miles, with chargers placed every 172 miles on a linear corridor. All public chargers should be deployed at the beginning of the planning horizon to achieve greater savings over the years. Sensitivity analysis reveals that the timeframe for the socially optimal conversion of 80% of the sample varies from 6 to 12 years. The optimal decision variables are sensitive to battery pack and vehicle body cost, gasoline cost, the discount rate, and conventional vehicles' fuel economy. Faster conventional vehicle replacement is achieved when the gasoline cost increases, electricity cost decreases, and battery packs become cheaper over the years.     

Interplay between ethanol and electric vehicles as low carbon mobility options for passengers in the municipality of São Paulo

The Brazilian cities as well as many of the large urban centers in the world continue to expand, increasing the demand for mobility and transport, while, at the same time, the same cities are investing in greenhouse gas (GHG) mitigation to avoid climate change. Brazil's urbanization rate increased from 26% in 1940 to almost 70% in 1980. During this period, the Brazilian population tripled and the urban population multiplied by seven. In 2010, the transport sector in São Paulo accounted for 71% of the total emissions released by the energy sector. Ethanol has been considered a fuel with less greenhouse gas emissions, when compared with fossil fuels. However, ethanol production would have to double to meet the expected demand. Electric vehicles (EVs) market is expanding around the world, and is also an option to reduce the transport emissions, if powered by clean electricity. To assess whether the adoption of EVs might bring more benefits than the current ethanol, we develop prospective scenarios supported by the Long-range Energy Alternatives Planning (LEAP) simulation tool, taking a bottom-up tank-to-wheel approach to consider the CO₂ emissions of car in São Paulo. The scenario considering a substitution of 25% of gasoline-powered cars by EV in 2030 showed a reduction in energy consumption and CO₂ emissions, around 15% and 26% respectively in that year in comparison with 2015. We discuss the interplay between ethanol and EV, also considering emission coefficients from life cycle analysis conducted in Brazil, and concluded EV will have higher positive impact on climate change mitigation than ethanol.     

Evaluating alternative concepts of bus-based park and ride

Whilst it has been used since the 1960s, the UK government have promoted bus-based Park and Ride (P&R) particularly heavily over the last 20 years as a tool to deal with traffic congestion and air pollution. There has long since been a view however that P&R in its current guise may actually be exacerbating the problems of traffic congestion, fuel use and emissions instead of mitigating them. This paper aims to reconsider this proposition whilst also testing a range of alternative forms of car–bus interchange in the context of traffic reduction, drawing on evidence from a large survey of P&R users in Cambridge, UK. Overall the results suggest that while current P&R significantly increases the vehicle miles travelled by its users, some of the alternative models presented potentially offer considerable improvements.     

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.     

Employment centers and travel behavior: exploring the work commute of Mumbai’s rapidly motorizing middle class

In the Greater Mumbai Region (GMR), jobs and housing are agglomerating in nodes in the periphery of Mumbai City. However, current transportation investments focus on strengthening connections within Mumbai City, while these outlying nodes have received less attention. As housing and jobs move out, given limited travel choices, the need for mobility nudges many middle class Indian households into owning private vehicles. Using household travel survey data from the GMR, this paper develops an understanding of how worker’s trips are different for those who commute to the city versus the exurbs. Socio-economic and transportation indicators for middle class workers going to the city versus the exurbs show that these populations are quite similar demographically. However, those traveling to the exurbs, on average, tend to be at a socio-economic disadvantage with respect to income, education and out-of-pocket travel burdens. Those traveling to exurban work locations have shorter travel times and trip distances, and make much higher use of walking, biking, rickshaws, and motorized two-wheelers compared to commuters to Mumbai City. Across the GMR, car users travel longer and farther compared to motorized two-wheeler users. On average, traveling by a private vehicle is faster than bus or rickshaw travel revealing advantages of private vehicle use. These mode choices in the middle class have resulted in rapid motorization and negative externalities such as traffic congestion and emissions. Evidence of large increases in motorized two-wheelers and cars in India suggests that these modes will likely keep growing, unless competing efficient travel options are supplied.     

PM,NOx and CO2 emission reductions from speed management policies in Europe

Speed reduction measures rank among the most common schemes to improve traffic safety. Recently many urban streets or entire districts were converted into 30 kph zones and in many European countries the maximum permissible speed of trucks on motorways is under discussion. However, besides contributing to traffic safety, reducing the maximum speed is also seen as beneficial to the environment due to the associated reduced fuel consumption and lower emissions. These claims however are often unsubstantiated.To gain greater insight into the impact of speed management policies on emissions, this paper examines the impact on different traffic types (urban versus highway traffic) with different modelling approaches (microscopic versus macroscopic). Emissions were calculated for specific types of vehicles with the microscopic VeTESS-tool using real-world driving cycles and compared with the results obtained using generalized Copert-like macroscopic methodologies. We analyzed the relative change in pollutants emitted before and after the implementation of a speed reduction measure for passenger cars on local roads (50–30 kph) and trucks on motorways (90–80 kph). Results indicate that emissions of most classic pollutants for the research undertaken do not rise or fall dramatically. For the passenger cars both methods indicate only minor changes to the emissions of NO_x and CO₂. For PM, the macroscopic approach predicts a moderate increase in emissions whereas microscopic results indicate a significant decrease. The effects of specific speed reduction schemes on PM emissions from trucks are ambiguous but lower maximums speed for trucks consistently result in lower emissions of CO₂ and lower fuel consumption. These results illustrate the scientific uncertainties that policy makers face when considering the implementation of speed management policies.