ASSESSING PUBLIC ACCEPTANCE OF AUTONOMOUS VEHICLES USING A NOVEL IRN PIPRECIA - IRN AROMAN MODEL
Autonomous vehicles (AVs) have become a tangible presence on roads, indicating the emergence of a promising transportation technology for the future, possibly arriving sooner than anticipated. Nevertheless, the extensive integration of this technology is contingent on various factors, with the foremost being the level of public acceptance and adjustment to this advanced technology. Several factors, including safety, privacy, and cost, play crucial roles in fostering acceptance. Consequently, this research delves into the key determinants shaping individuals' willingness to embrace AVs. In this paper, a novel model, which consists of two methods: PIPRECIA and AROMAN with Interval Rough Numbers (IRNs) has been developed. The IRN PIPRECIA serves to define criterion weights, while the most significant contribution of the paper is the extension of the AROMAN method with IRNs for evaluating the public acceptance of autonomous vehicles and adapting all the necessary conditions for their use. The results show that a rapid implementation with extensive testing strategy represents the best solution.