Defining Psychometric Variables Related to Use of Autonomous Vehicles

2019 ◽  
Vol 2673 (12) ◽  
pp. 655-669
Author(s):  
Yanbo Ge ◽  
Andisheh Ranjbari ◽  
Elyse O’C. Lewis ◽  
Eric Barber ◽  
Don MacKenzie
Keyword(s):  
Factor Analysis ◽  
Travel Behavior ◽  
Latent Variables ◽  
Autonomous Vehicles ◽  
Ad Hoc ◽  
Autonomous Vehicle ◽  
Behavioral Studies ◽  
Perceptions And Attitudes ◽  
Transportation Modes ◽  
Use Behavior

With the goal of understanding autonomous vehicle (AV) adoption and use behavior, numerous behavioral studies and surveys have included variables intended to capture individuals’ perceptions of and attitudes toward AVs. However, the selection of questions to measure these psychometric variables appears to be ad hoc and, in many cases, arbitrary. In contrast, this study defines psychometric latent variables (LVs) that are related to the adoption and use of AVs and develops a set of questions to reliably measure them. By considering three psychological concepts (norms, perceptions, and attitudes) and nine qualitative utility constructs that influence individuals’ travel behavior, this study defines a comprehensive list of LVs and identifier questions to support their construction. A factor analysis of a nationwide n = 347 sample was used to obtain a minimum set of relevant LVs and questions to measure them. Ultimately, the factor analysis resulted in a final set of nine LVs specified by 44 questions (four or five questions for each LV). The final set of questions may be used by researchers or survey organizations interested in studying future trends of demand and adoption for AVs or other emerging transportation modes. The approach used in this study may also be employed in other contexts to define psychometric variables of interest and the questions needed to reliably measure them.

Pedestrians, Autonomous Vehicles, and Cities

2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Neighborhoods ◽  
Urban Traffic ◽  
Risk Averse ◽  
Strategic Interactions ◽  
Road Users ◽  
Self Driving Cars ◽  
Time Autonomous

Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.

Incorporating Attitudinal Factors to Examine Adoption of and Willingness to Pay for Autonomous Vehicles

2019 ◽  
Vol 2673 (8) ◽  
pp. 418-429 ◽  
Author(s):  
Hamidreza Asgari ◽  
Xia Jin
Keyword(s):  
Willingness To Pay ◽  
Stress Reduction ◽  
Latent Variables ◽  
Autonomous Vehicles ◽  
Mode Choice ◽  
Autonomous Vehicle ◽  
Cost Savings ◽  
Structural Equations ◽  
Driving Mode ◽  
Attitudinal Factors

Results from a recent consumer survey were thoroughly analyzed in relation to willingness to adopt and willingness to pay (WTP) for different autonomous vehicle (AV) features. Four different levels of automation were considered including basic vehicles, adding advanced features, partial automation, and full automation. A structural equations model with latent variables was employed, which simultaneously regressed adoption and WTP levels against a variety of available variables including socioeconomic and demographic attributes, private car usage habits, and attitudinal preferences/personal opinions. To address the endogeneity in personal attitudes, these variables were added to the model as latent factors. Accordingly, the analysis revealed four major latent attitudinal factors, respectively labeled as “joy of driving,”“mode choice reasoning,”“trust,” and “technology savviness.” Model results indicated that those who enjoy driving were the hardest to persuade towards AV adoption or to pay for automated features. On the other hand, technology savvy people showed higher tendency towards AV adoption. When it comes to factors affecting mode choice including travel time, travel cost, and functionality, people are willing to pay more for automated features when they believe that these features and services will provide them better utility, in relation to time and cost savings, convenience, stress reduction, and quality of life, and so forth. Interestingly, individuals with trust concerns showed higher WTP values, which may indicate that the market believes autonomous vehicles will bring more privacy and protection, at least compared with existing shared mobility or public transit options.

Examining the Equity Impacts of Autonomous Vehicles: A Travel Demand Model Approach

2019 ◽  
Vol 2673 (5) ◽  
pp. 23-35 ◽  
Author(s):  
Jesse Cohn ◽  
Richard Ezike ◽  
Jeremy Martin ◽  
Kwasi Donkor ◽  
Matthew Ridgway ◽  
...  
Keyword(s):  
Performance Measures ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Demand Model ◽  
The Status ◽  
Mode Share ◽  
Transit Agencies ◽  
Travel Demand Model

As investments in autonomous vehicle (AV) technology continue to grow, agencies are beginning to consider how AVs will affect travel behavior within their jurisdictions and how to respond to this new mobility technology. Different autonomous futures could reduce, perpetuate, or exacerbate existing transportation inequities. This paper presents a regional travel demand model used to quantify how transportation outcomes may differ for disadvantaged populations in the Washington, D.C. area under a variety of future scenarios. Transportation performance measures examined included job accessibility, trip duration, trip distance, mode share, and vehicle miles traveled. The model evaluated changes in these indicators for disadvantaged and non-disadvantaged communities under scenarios when AVs were primarily single-occupancy or high-occupancy, and according to whether transit agencies responded to AVs by maintaining the status quo, removing low-performing routes, or applying AV technology to transit vehicles. Across the performance measures, the high-occupancy AV and enhanced transit scenarios provided an equity benefit, either mitigating an existing gap in outcomes between demographic groups or reducing the extent to which that gap was expanded.

scholarly journals Common Driving Notification Protocol Based on Classified Driving Behavior for Cooperation Intelligent Autonomous Vehicle Using Vehicular Ad-Hoc Network Technology

2015 ◽  
Vol 5 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Che-Hung Lin ◽  
Fang-Yan Dong ◽  
Kaoru Hirota
Keyword(s):  
Autonomous Vehicles ◽  
Ad Hoc ◽  
Autonomous Vehicle ◽  
Driving Behavior ◽  
Packet Transmission ◽  
Wireless Data ◽  
Standard Format ◽  
Simulation Tools ◽  
Identification Time ◽  
Basic Protocol

Abstract A protocol, called common driving notification protocol (CDNP), is proposed based on the classified driving behavior for intelligent autonomous vehicles, and it defines a standard with common messages and format for vehicles. The common standard format and definitions of CDNP packet make the autonomous vehicles have a common language to exchange more detail driving decision information of various driving situations, decrease the identification time for one vehicle to identify the driving decisions of other vehicles before or after those driving decisions are performed. The simulation tools, including NS- 3 and SUMO, are used to simulate the wireless data packet transmission and the vehicle mobility; the experiment results present that the proposed protocol, CDNP, can increase the reaction preparing time with maximum value 250 seconds, decrease the identification time and the average travel time. Prospectively, it is decided to implement the CDNP as a protocol stack in the Linux kernel to provide the basic protocol capability for real world transmission testing.

scholarly journals Vehicle Electrification Impacts on Energy Consumption for Different Connected-Autonomous Vehicle Scenario Runs

2019 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Ehsan Sabri Islam ◽  
Ayman Moawad ◽  
Namdoo Kim ◽  
Aymeric Rousseau
Keyword(s):  
Energy Consumption ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Transportation System ◽  
Regional Energy ◽  
Energy Impact ◽  
Potential Factors ◽  
The Impact ◽  
The City

Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.

scholarly journals Spanish adaptation of the Alcohol Expectancy-Adolescent Questionnaire, Brief

2015 ◽  
Vol 5 (3) ◽  
pp. 357-369
Author(s):  
José J. Gázquez ◽  
Mª del Carmen Pérez-Fuentes ◽  
Mª del Mar Molero ◽  
África Martos ◽  
Fernando Cardila ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Ad Hoc ◽  
Demographic Data ◽  
Alcohol Expectancies ◽  
Reliability And Validity ◽  
Spanish Version ◽  
Alcohol Expectancy ◽  
Two Factors ◽  
Relevant Role ◽  
Use Behavior

Alcohol is a substance commonly used by adolescents. Due to the relevant role alcohol expectancies have for understanding adolescent use behavior, valid and reliable instruments need to be designed to evaluate these beliefs. The purpose of this study was to validate the Spanish version of the Alcohol Expectancy Questionnaire-Adolescent, Brief (AEQ-AB). The sample was comprised of 315 adolescents aged 14 to 18 years who filled in an ad hoc questionnaire on demographic data the Spanish version of the EQ and the (AEQ-AB). Factor analysis showed that the original seven-item model clustered in two factors (positive and negative), fit the Spanish sample correctly. The reliability and validity analysis showed adequate translation and adaptation of the AEQ-AB questionnaire in Spanish adolescents.

Generalized Stable User Matching for Autonomous Vehicle Co-Ownership Programs

2020 ◽  
Vol 12 (2-3) ◽  
pp. 61-79 ◽  
Author(s):  
Anpeng Zhang ◽  
Jee Eun Kang ◽  
Changhyun Kwon
Keyword(s):  
Autonomous Vehicles ◽  
Ad Hoc ◽  
Autonomous Vehicle ◽  
Stable Matching ◽  
Computational Time ◽  
Combinatorial Properties ◽  
Fractional Ownership ◽  
Shared Mobility ◽  
New Form

We investigate a new form of car-sharing system that can be introduced in the market for autonomous vehicles called fractional ownership or co-ownership. Although dynamic ride sharing provides ad hoc shared mobility services without any long-term commitment, we consider co-ownership programs with which users can still “own” a car with committed usage and ownership. We assume that an autonomous vehicle is shared by a group of users, which is only accessible by the group. We use stable matching to help users find an appropriate group with which to share an autonomous vehicle and present a generalized stable matching model that allows flexible sizes of groups as well as various alternative objectives. We also present a heuristic algorithm to improve computational time owing to the combinatorial properties of the problem.

scholarly journals Spanish adaptation of the Alcohol Expectancy-Adolescent Questionnaire, Brief

2015 ◽  
Vol 5 (3) ◽  
pp. 357-369
Author(s):  
José J. Gázquez ◽  
Mª del Carmen Pérez-Fuentes ◽  
Mª del Mar Molero ◽  
África Martos ◽  
Fernando Cardila ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Ad Hoc ◽  
Demographic Data ◽  
Alcohol Expectancies ◽  
Reliability And Validity ◽  
Spanish Version ◽  
Alcohol Expectancy ◽  
Two Factors ◽  
Relevant Role ◽  
Use Behavior

Alcohol is a substance commonly used by adolescents. Due to the relevant role alcohol expectancies have for understanding adolescent use behavior, valid and reliable instruments need to be designed to evaluate these beliefs. The purpose of this study was to validate the Spanish version of the Alcohol Expectancy Questionnaire-Adolescent, Brief (AEQ-AB). The sample was comprised of 315 adolescents aged 14 to 18 years who filled in an ad hoc questionnaire on demographic data the Spanish version of the EQ and the (AEQ-AB). Factor analysis showed that the original seven-item model clustered in two factors (positive and negative), fit the Spanish sample correctly. The reliability and validity analysis showed adequate translation and adaptation of the AEQ-AB questionnaire in Spanish adolescents.

Modeling Individual Preferences for Ownership and Sharing of Autonomous Vehicle Technologies

2017 ◽  
Vol 2665 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Patrícia S. Lavieri ◽  
Venu M. Garikapati ◽  
Chandra R. Bhat ◽  
Ram M. Pendyala ◽  
Sebastian Astroza ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Network Performance ◽  
Transportation Network ◽  
Autonomous Vehicle ◽  
Puget Sound ◽  
Heterogeneous Data ◽  
Model System ◽  
Vehicle Technologies ◽  
The One

Considerable interest exists in modeling and forecasting the effects of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle (AV) future, individuals may privately own such vehicles, use mobility-on-demand services provided by transportation network companies that operate shared AV fleets, or adopt a combination of those two options. This paper presents a comprehensive model system of AV adoption and use. A generalized, heterogeneous data model system was estimated with data collected as part of the Puget Sound, Washington, Regional Travel Study. The results showed that lifestyle factors play an important role in shaping AV usage. Younger, urban residents who are more educated and technologically savvy are more likely to be early adopters of AV technologies than are older, suburban and rural individuals, a fact that favors a sharing-based service model over private ownership. Models such as the one presented in this paper can be used to predict the adoption of AV technologies, and such predictions will, in turn, help forecast the effects of AVs under alternative future scenarios.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

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