基于CRITIC-TOPSIS的智能网联车辆城市道路感知与运行适配性评价

Evaluation of Urban Road Perception and Operational Adaptability for Intelligent Connected Vehicles Based on CRITIC-TOPSIS

摘要: 为评价城市道路对智能网联车辆感知与运行的适配程度，从道路基础与交通组织、道路感知环境和交通运行状态3个方面构建17项评价指标，采用CRITIC-TOPSIS模型对成都市锦江区20个典型路段进行评价。结果表明，交通标线清晰度、行人及非机动车影响和交通信号灯情况权重较高；样本综合贴近度为0.340~0.717，红星路一至二段跨线桥适配水平最高，净居寺路和龙舟路相对较低。敏感性分析表明，关键指标权重扰动±20%时道路排序总体稳定。研究可为城市道路环境优化及智能网联车辆运行条件改善提供参考。

Abstract: To evaluate the adaptability of urban roads to the perception and operation of intelligent connected vehicles (ICVs), 17 evaluation indicators are constructed from three dimensions: road infrastructure and traffic organization, road perception environment, and traffic operation status. The CRITIC-TOPSIS model is adopted to assess 20 typical road segments in Jinjiang District, Chengdu. The results show that the clarity of traffic markings, the impact of pedestrians and non-motor vehicles, and the condition of traffic signals have relatively high weights. The comprehensive closeness degrees of the samples range from 0.340 to 0.717; the overpass of Section 1~2 of Hongxing Road has the highest adaptation level, while Jingjusi Road and Longzhou Road have relatively low levels. The sensitivity analysis indicates that the ranking of road segments remains generally stable when the weights of key indicators are perturbed by ±20%. This study can provide a reference for optimizing the urban road environment and improving the operation conditions of intelligent connected vehicles.