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Evaluating the Utility of Autonomous Vehicles Acceptance Theories and Providing a Model for Choosing the Type of Car Control Based on user Driving Experience

Taftian, Zohreh | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57905 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Nassiri, Habibollah
  7. Abstract:
  8. An autonomous vehicle, also known as a driverless car or robotic car, is a car that can recognize its environment and move with little or no human intervention. Self-driving cars bring many benefits, such as reducing traffic congestion, reducing greenhouse gas emissions, and improving transportation accessibility. The acceptance of AV’s has always been a debated issue for the manufacturers and importers of these cars, so it is necessary to examine the acceptance of these cars and the role of various psychological and social factors in it. The first objective of this study is to review three widely used theories in the literature of AV’s acceptance, namely the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) in the acceptance of the use of level 5 AV’s (SAE 5) in Iran and choosing the most favorable ones in explaining the behavioral intention of using these cars. The second aim of the study is to provide a model based on the experience and driving performance of the individual in choosing the type of car control (manual, semi-autonomous full-autonomous). The results of the first part showed that all three theories partially support the behavioral intention to accept self-driving cars, however, the UTAUT theory along with the moderator variables can predict up to 60.6% of the behavioral intention variance, which is the most favorable theory for the second part of the research. made way The results of the second part showed that the factors of the UTAUT theory and the variables of driving experience, legality of driving and driving accuracy are important and significant predictors of choosing the type of car control, and the variables of driving habits and driving performance are not significant predictors. Also, the structural model presented in this section was able to predict up to 75% of vehicle control type selection
  9. Keywords:
  10. Autonomous Vehicles (AVs) ; Planned Behavior Theory ; Technology Acceptance Model (TAM) ; Driving Experience ; Unified Theory of Acceptance and Use of Technology (UTAUT) ; Automatic Vehicle Driving

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