A new method for real-time evaluation of urban traffic congestion: a case study in Xi'an, China.

Clarifying the spatiotemporal characteristics of urban traffic congestion can help to manage and alleviate such congestion more effectively. In this study, we used real-time traffic data provided by the Gaode LBS open platform to model and analyze urban traffic congestion in Xi'an, China, focusing on the spatiotemporal characteristics of single roads, different road grades, and the whole road network at different moments and time periods. Weekday real-time traffic data were collected from 23 April to 11 May, 2018, and the congestion index for different types of roads within Xi'an's Third Ring Road was calculated. The results allowed us to thoroughly analyze the spatiotemporal characteristics of traffic congestion in Xi'an and suggest methods for congestion control and improvement, including enhanced traffic control during special periods and more balanced urban development. Our results show the feasibility of this evaluation approach, which can provide timely decision-making support for urban traffic congestion management. [ABSTRACT FROM AUTHOR]