Objective and effective evaluation of the urban road network traffic performance is of vital importance for traffic management. However, due to the limitation of data sources and coverage, previous studies mostly focus on the local urban road network and measure the traffic performance only by single-dimensional indicators e.g., speed. In this study, based on AutoNavi’s big data, we proposed a macro comprehensive evaluation method to measure the city-level traffic performance. Firstly, a multidimensional index system is established as the evaluation criteria from different perspectives of time, space and efficiency. Then the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) combined with entropy weight is employed on this index system to give an overall evaluation of the traffic performance. Finally, a case study of 50 cities in China is conducted to demonstrate the feasibility and effectiveness of the evaluation method. Results show that the proposed method can effectively evaluate the city-level traffic performance and exhibit promising potential in guiding traffic management.

CICTP