•This paper reviews stated preference/choice studies related to autonomous vehicles.•Classification based on components of opinions and attitudes, and study population.•Interrelation between ...components can explain how and the extent AVs can diffuse.•The benefits, barriers, and opportunities related to AV deployment are summarized.•Lessons learned and research gaps related to AV adoption/deployment are provided.
This paper provides a review of studies published in peer-reviewed journals, conference proceedings, and technical academic and private sector reports on surveys about autonomous vehicles (AVs) from 2012 onward. The studies and respective surveys are categorized in this paper based on the study objectives and methodology applied. More than half of the reviewed studies on AVs focus on capturing individuals’ behavioral characteristics and perceptions. The second most prevalent category includes studies about individuals’ willingness to pay to use AVs. The reviewed studies were also categorized according to the study population. The paper identifies and classifies attitudinal questions in each survey into different components that may affect behavioral intention to ride in AVs and provides information on specific hypotheses that were set in the studies. Moreover, a discussion of the benefits, barriers/concerns, and opportunities related to the deployment of AVs is presented. The paper concludes by summarizing the lessons learned and outlining the research gaps.
This paper proposes methodologies to estimate the electric energy and power consumption by light-duty plug-in electric vehicles (PEVs). Using the travel patterns of light-duty vehicles in the U.S. ...obtained from the 2009 National Household Travel Survey, the PEVs' energy and power consumption are estimated for two uncontrolled charging scenarios.
•A stated preference survey was distributed to truck fleet managers in the U.S.•Business model, product availability and charging time were the top cause barriers.•Grid resiliency and operational ...reliability were among the effect barriers.•Top barriers for electric truck adopters are charging time and product availability.•To attract non-adopters, focus should be on business model and governmental support.
Although the electrification of trucks can offer overall operation cost reduction and contribute to the decarbonization of transport, electric vehicles in the commercial sector are not widely adopted. Existing studies explore the barriers to truck electrification using qualitative or descriptive analysis. This study proposes that the barriers to electric truck (ET) adoption should be further studied as a system and examines their ranking and interrelationships to enhance policy decision making. Based on a literature review and feedback from experts, ten barrier groups were identified. Data was obtained from a stated preference survey that was distributed online to 74 truck fleet managers/owners in the United States (U.S.). A multicriteria decision-making approach was used that combines the decision-making trial and evaluation laboratory method (DEMATEL) with grey system theory. Additionally, a subgroup analysis was conducted to explore potential differences for ET adopters and non-ET adopters. Among other findings, the results indicate that the business model and partnerships, product availability, and charging time constitute the top cause factors. Addressing these barriers would also lead to or help address the most prominent barriers regarding operational reliability, grid resiliency, and customer acceptance and expectations. The subgroup analysis showed that ET adopters and non-adopters may not be viewed as one homogenous group, since differences were found in the ranking and interrelationships of barriers to ET adoption between these two groups. This study improves the theoretical rational for the barriers and can assist policymakers or other major stakeholders to frame and prioritize strategies for accelerating ET adoption.
•Investigated public perceptions of shared mobility benefits and barriers.•Conducted an extensive survey in Indianapolis, Indiana, gathering 424 responses.•Employed latent class analysis to ...reflecting varied perspectives.•LCA revealed three classes each for perceived benefits and barriers.•Policy recommendations are offered to target the untapped market potential.
The United States faces urban issues like congestion and pollution due to heavy car dependency, with over 91% owning cars and 87% driving to work. In response to these challenges, various shared mobility solutions have been integrated into transportation systems, encompassing bike-sharing, e-scooter sharing, and ride-hailing, but have not seen widespread adoption. To this end, this study investigates the perception of these services in the context of benefits and barriers. A survey was conducted in Indianapolis, Indiana and distributed online, gathering 424 responses. Latent class analysis (LCA) was used to determine groups of individuals with similar perceptions. The LCA identified three classes regarding perceptions of shared mobility benefits, and three others in relation to barriers. Regarding benefits, the classes include “Casual observers of benefits,” predominantly comprising older, less active females; “Benefits proponents,” featuring a majority of young, well-educated, higher-income males who prioritize health; and “Non-believers in benefits,” primarily consisting of older individuals, often identifying as black, with lower incomes and less active commuting. In terms of barriers, the classes are “Indifferent about barriers,” mainly comprising younger, lower-income individuals; “Shared mobility bystanders,” primarily characterized by older individuals with infrequent work commutes; and “Barrier conscious,” mostly including younger, well-educated, racially diverse individuals with complex commuting patterns. In both the benefits and barriers categories, the largest classes consist of individuals with neutral perspectives on shared mobility, signifying that a substantial portion of the population has not fully embraced these services. The study recommends policies to promote shared mobility to this significant population segment.
•A structural equation model was constructed based on a public opinion survey in Iowa.•Distracted driving culture was represented by four latent constructs.•Distracted driving attitudes, experiences, ...and behaviors were highly correlated.•Age and household income strongly influenced the culture around distracted driving.•Our findings can inform the design of culture-based interventions for distracted driving.
Traffic safety culture does not merely focus on risky behaviors and their consequences, but also on change in social norms, values, and beliefs. Past research has recommended establishing a comprehensive program to shape a safer traffic safety culture in the United States. In 2011, a cell phone and landline survey regarding traffic safety culture was disseminated across the state of Iowa. The survey gauged opinions from 1088 participants on driving experience, covering a wide range of traffic safety topics including law enforcement, driver education program, various driving behaviors, and attitudes toward traffic safety policies and programs.
A descriptive analysis of the responses revealed a need for an in-depth study of the current culture related to distracted driving in Iowa. A Structural Equation Model (SEM) was estimated to define the relationship among individual characteristics (participants’ socioeconomic and demographic characteristics), experience, and attitudes towards distracted driving (mainly cell phone use). Four latent variables: distractibility (DB), self-reported distracted driving behavior (SDDB), personal acceptability of distracted driving (PADD), and prediction of possible crashes (PPC) caused by distraction were constructed to represent the culture around distracted driving. The SEM estimation results suggested that participants’ distracted driving attitudes, experiences, and behaviors were highly correlated. In addition, it also suggested that participants’ characteristics (primarily age and household income) strongly influenced their experiences and behaviors related to distracted driving. The results of this paper can be useful for developing interventions designed for target groups of drivers (primarily younger and high-income drivers) in a bid to transform the culture around distracted driving.
Health problems such as obesity and related illnesses have been attributed to the lack of both spatial and economic access to healthy food. Even though access to healthy food in urban areas has been ...widely studied, access to healthy food in rural areas has not received much attention to date. Rural residents usually face similar accessibility challenges as urban populations but at a greater magnitude. The lack of access to reliable transportation in rural areas acts as a barrier to accessing healthy food, especially for individuals that might not have access to an automobile.
This paper uses a cost-based accessibility measure and estimates spatial econometric models to identify the differences between healthy food accessibility in rural and urban areas considering multiple transportation modes available in those areas. Furthermore, the paper explores the relationship between healthy food accessibility and the characteristics of the built environment that can be used to advise planning decisions and policy. Four study areas in Indiana were selected to demonstrate the study methodology.
Both the location of healthy food providers and infrastructure that allows access by different modes are spatially clustered. Urban area residents incur a lower average cost to reach healthy food, especially when driving and walking are considered, compared to rural areas. The spatial models' results suggested that built environment characteristics, especially land-use characteristics, influence the cost to reach healthy food providers in urban areas, regardless of the mode.
The solution to facilitate access to healthy food providers is not a one-size-fits-all approach. However, transportation innovations such as mobile markets, ridesharing, drone delivery, and autonomous delivery services can serve to bring closer healthy food to the population that cannot access it by their current means. This paper's methodology involves publicly available data that allow for easy replication by any planning agency.
•Disparities in urban and rural access to healthy food are factual.•Urban and rural areas differ in transportation modes and cost to access healthy food.•Built environment characteristics are important in studying healthy food access.•Urban areas incur a lower cost to access healthy food when driving and walking.•Transportation innovations should be promoted to enhance healthy food accessibility.
Pedestrians are some of the most vulnerable road users as they are not protected by safety devices, and must also share the road with vehicles traveling at dangerous speeds, particularly during road ...crossings. In 2011, the state of Oregon changed their traffic laws to be more accommodating to pedestrians by giving right of way to pedestrians using a crosswalk, regardless if whether the crosswalk is marked or unmarked. This paper estimates a panel logit model to evaluate the efficacy of the law in preventing pedestrian fatalities. Pedestrian fatalities are shown to decrease over time, with smaller likelihood of a fatality outcome in the years following the change in pedestrian crossing laws. To the authors’ knowledge, it is the first time panel logit models have been used in evaluating pedestrian safety. Results indicate that panel logit models are an alternative to using Box-Tiao intervention models to analyze the long term effects of policy changes, as they allow for the consideration of crash exposure factors as well as temporal effects.
•Truck fleet managers’ stated preferences on electrification are explored.•There is heterogeneity in truck fleet managers’ perspectives across trucking firms and fleets.•Truck fleet managers also ...value sustainability besides total cost of ownership.•Awareness of emerging charging solutions can drive adoption of electric trucks.•Charging infrastructure availability and cost are hindering adoption of electric trucks.
Electrifying trucks can lead to large societal and private benefits for truck fleet managers. However, the electric truck market is still in its infancy compared to passenger electric vehicles. This study examines the intention of truck fleet managers/owners to electrify their fleets. A stated preference survey was designed and distributed online to truck fleet managers in the U.S., gathering 200 responses. This paper presents a descriptive analysis of the survey data, including information on the current and future market penetration of battery electric trucks. Additionally, using an ordered probit model with random parameters, this study identifies the factors affecting purchase intentions. The results showed that the purchase intentions of truck fleet managers are affected by three main groups of factors: trucking firm and truck fleet characteristics (such as trucking firm revenue and fleet size), opinions regarding electric trucks (such as cost to charge, perceived availability of charging infrastructure), and awareness of innovative charging technologies. Three factors related to the trucking segment, truck fleet composition, and truck annual mileage had mixed effects on truck fleet managers’ purchase intentions, that attests to the heterogeneity in truck fleet managers’ perspectives. This study contributes to the literature by providing significant insights regarding the perspectives of truck fleet managers in the U.S. and offering updated information on the electric truck market. Additionally, the study findings can be used by policymakers and other major stakeholders of the electric vehicle ecosystem to frame certain strategies to accelerate electric truck adoption.
Promotional strategies for electric vehicle (EV) adoption need to be tailored to the public's perception of these vehicles. However, there is a notable gap in understanding how public perception of ...EVs differs between adoption pioneers and those slower to adopt (“adoption laggards”) in terms of the percentage of registered EVs. This understanding is vital for the development of effective promotional strategies, especially for adoption laggards. To address this research gap, this study compares various public perception of EVs among adoption pioneers and laggards in U.S. states by analyzing historical Twitter discussions using Natural Language Processing (NLP) techniques, including topic and sentiment analysis. The findings reveal distinct patterns in online EV discussions between the two groups, with adoption laggards being concerned more about affordability and gas prices, and adoption pioneers consistently discussing various topics covering EV and battery manufacturing, charging infrastructure, government EV initiatives, and the EV market. Adoption pioneers exhibit stable, positive attitudes, while adoption laggards display frequent attitude fluctuations, including more negative ones recently. These differences emphasize the importance of EV affordability for adoption laggards and indicate a possible widening gap in EV adoption due to ongoing debates among adoption laggards surrounding the value of transportation electrification. By addressing adoption laggards' concerns and promoting the benefits of EVs, policymakers and stakeholders can enhance perceptions toward EVs, bridging the gap between adoption pioneers and laggards, and promoting widespread adoption of cleaner transportation options.
•Examines EV perception via social media among adoption pioneers and laggards.•Merges social media data with geography to show spatial differences.•Highlights diverse EV discussion topics by adoption pioneers and laggards.•Notes distinct time-based attitudes of adoption pioneers and laggards towards EVs.
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