Abstract

Nowadays, public transport is considered as an alternative to private vehicles to reduce environmental and social problems in developing countries. Hence, assuring a high passenger satisfaction level in the public transport system is an important task for municipalities and governments. However, passenger satisfaction evaluation of public transport is difficult as the opinions of passengers are vague and uncertain, and the number of involved passengers is large. In this article, we present a new method based on double hierarchy hesitant linguistic term sets (DHHLTSs) and alternative queuing method (AQM) for the passenger satisfaction evaluation of rail transit network under large group environment. First, the DHHLTSs are utilized to depict the uncertain satisfaction evaluation information given by passengers. Next, the k-means++ algorithm is modified to cluster the large group of passengers for satisfaction evaluation information aggregation. Then, the AQM is extended and used to acquire the passenger satisfaction ranking of rail transit lines. The practicability and rationality of the proposed passenger satisfaction evaluation method are illustrated via an application to the Shanghai rail transit network in China. The result shows that the new method provides more reliable and realistic results and introduces directions for further service quality improvement of public transport.