Signal Timing Optimization for Urban Arterials Based on Entropy-Weighted TOPSIS Comprehensive Evaluation

Abstract

To address recurrent queues and delays caused by uneven traffic demand on urban arterials and the mismatch between fixed intersection signal timings and actual vehicle arrivals, this study proposes a signal timing optimization method based on entropy-weighted TOPSIS comprehensive evaluation. The continuous signalized corridor of Beixin East Road from Jianshe Road to Binhe Road in Tangshan is taken as the study area. Without introducing multi-source data fusion, a unified evaluation system is constructed directly from the road network, traffic demand, and SUMO simulation outputs. First, 59 OD demands are established according to road functional hierarchy, approach-lane capacity, turning structure, and node flow conservation, with a total external demand of 4470 veh/h. Average travel time, average waiting time, average time loss, and average queue length are then selected as the core performance indicators. Information entropy is used to determine objective weights, and TOPSIS relative closeness is employed to evaluate signal timing schemes. On this basis, an offline feedback optimization process of evaluation, diagnosis, adjustment, and re-evaluation is developed. While maintaining the original phase sequence and safety transition times, the coordinated cycle of the major intersections in the corridor is unified to 110 s, and effective green times are redistributed according to critical flow ratios. SUMO 1.27.1 simulations show that, compared with the original timing scheme, the optimized scheme reduces average travel time from 352.35 s to 334.12 s, average waiting time from 240.12 s to 220.31 s, and average time loss from 311.86 s to 294.04 s, corresponding to improvements of 5.18%, 8.25%, and 5.71%, respectively. The average queue length increases from 72.78 m to 79.47 m, indicating a local spatial redistribution of queues while temporal costs are reduced by the common-cycle and green-split reconstruction. In the entropy-weighted TOPSIS evaluation, the relative closeness increases from 0.4978 to 0.5022. The results demonstrate that the proposed method avoids judging signal timing performance using a single indicator and provides a reproducible technical route for multi-indicator optimization and simulation-based evaluation of urban arterial signal timing.