Evaluating Traffic Performance in City-Level Road Network via an Entropy Weighted TOPSIS Method

Objective and effective evaluation of the urban road network traffic performance is a vital important for traffic management. However, due to the limitations on data sources and coverage, previous studies mostly focused on the local urban road network and measure the traffic performance only by single-dimensional indicators. In this study, based on AutoNavi’s big data, we proposed a macro comprehensive evaluation method to measure the city-level traffic. First, 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. Results show that the proposed method can effectively evaluate the city-level traffic performance and exhibit promising potential in guiding traffic management.