An ANFIS Based Derivations of Inference Rules for Users’ Adoptions of Autonomous Vehicles
| Autor: | Yu Sun, Ying-Ting Kuo, Yung-Cheng Lin, Jen-Chieh Cheng, Chi Yo Huang, Liang-Chieh Wang, Yu-Feng Lu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
050210 logistics & transportation
Data processing Adaptive neuro fuzzy inference system Computer science 05 social sciences Decision rule 010501 environmental sciences 01 natural sciences Intervention (law) Risk analysis (engineering) Conceptual framework Order (exchange) Control system 0502 economics and business Rule of inference 0105 earth and related environmental sciences |
| Zdroj: | iFUZZY |
| DOI: | 10.1109/ifuzzy50310.2020.9297811 |
| Popis: | Autonomous Vehicles (AVs) have great potential and can improve transportation efficiency and safety through minimal manual intervention and optimized traffic control systems. Advances in artificial intelligence and real-time data processing technology have promoted the development of practical AVs. AV manufacturers are trying to understand the potential factors that may affect consumers' acceptance of autonomous vehicles. However, there is very little research on autonomous vehicles and consumers. In order to understand these factors, this research will use UTAUT 2, as a research framework to predict consumer intentions and behaviors. This research will first review the literature, invite experts to define and evaluate appropriate criteria and dimensions, and use the ANFIS is used to derive the decision rules, and the weights of the corresponding rules are compared. The resulting analysis can be used as a basis for predicting consumer acceptance of AVs in the future. |
| Databáze: | OpenAIRE |
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