Comparative Analysis of Expert and Public Perceptions of Evaluation Criteria for Autonomous Demand-Responsive Transit Services
Autonomous Demand-Responsive Transit (Autonomous DRT) is a public transportation service that integrates autonomous driving technology with DRT. The success of Autonomous DRT depends on operational performance as well as public acceptance. Therefore, both expert and public perspectives need to be considered in service planning and evaluation. This study compares expert and public perceptions of the evaluation criteria for Autonomous DRT services using a common evaluation framework. Expert priorities were obtained from the analytic hierarchy process (AHP) results of a previous study involving 32 experts, whereas public priorities were analyzed using survey data from 300 residents of Namyang-eup, Hwaseong-si. Pairwise comparison questions were used as evaluation items to reduce the response burden on the public respondents, and ranking questions were used as evaluation indicators. The ranking data were converted into AHP-type importance values. Analyses using multiple weighting methods and nonparametric bootstrap procedures were conducted to examine the stability of the estimated priorities and their sensitivity to the weighting transformations. The results show that experts and the public evaluate Autonomous DRT services from different perspectives and assign different priorities to the evaluation criteria. The experts placed relatively greater importance on system-level performance factors, such as operational efficiency, service reliability, and demand responsiveness. In contrast, public respondents tended to prioritize factors directly related to the actual user experience, including access distance to boarding points, driving speed stability, and the number of vehicles in operation. These findings suggest that the planning and evaluation of Autonomous DRT services should consider system-level indicators of operational efficiency along with user-perceived accessibility, safety, and service availability. This study highlights the need to develop Autonomous DRT service designs and evaluation frameworks that balance system efficiency with user acceptance by incorporating both expert-oriented operational performance indicators and public-oriented perceived service quality indicators.