首页|基于有向图的城市交叉口场景相似性评价方法

基于有向图的城市交叉口场景相似性评价方法

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准确的场景相似性评估对于优化测试场景集极为重要。然而,现有的基于轨迹的评价方法未能充分捕捉城市交叉口中车辆间的复杂动态交互特征,从而影响评价结果的准确性。针对此问题,本研究提出了一种基于有向图的城市交叉口场景相似性评价方法,该方法通过比较两个场景中车辆的全局交互拓扑关系在时空上的匹配程度来量化场景之间的相似性。首先,使用有向图来表征各个交叉口中车辆间的交互拓扑结构。然后,通过比较不同交叉口场景的有向图结构匹配程度来估计它们之间的交互相似性。最后,采用动态时间扭曲算法在时间维度上对齐场景,实现两个不同长度测试场景序列的有效比较。3对典型评价案例的定性分析结果显示,该方法能够细粒度地区分不同相似度水平的场景。进一步地,为定量验证方法的有效性,开展了场景相似度与自动驾驶系统性能之间的方差分析实验。实验结果表明,在不同相似度水平场景簇的测试条件下,系统的安全性和效率均表现出显著的差异,从而证实了该方法的有效性。最终,该方法应用于Apollo的测试场景集的优化,结果表明方法能够有效指导测试场景集中同质化场景的剔除,从而提高测试效率。
Directed Graph-Based Method for Evaluating Similarity in Urban Intersection Scenarios
Accurate evaluation of scenario similarity is extremely important for optimizing test scenarios.However,existing trajectory-based evaluation methods fail to adequately capture the complex dynamic interaction characteristics between vehicles at intersections,which affects the accuracy of the evaluation results.To address this problem,in this study a directed graph-based similarity evaluation method for urban intersection scenes is pro-posed,which quantifies the similarity between scenes by comparing the degree of spatial and temporal matching of the global interaction topologies of vehicles in two scenarios.Firstly,a directed graph is used to characterize the in-teraction topology between vehicles at each urban intersection.Then,the interaction similarity between different in-tersection scenarios is estimated by comparing the degree of matching of their directed graph structures.Finally,a dynamic time warping algorithm is used to align the scenarios in the time dimension to effectively compare two test scenario sequences of different lengths.The results of the qualitative analysis of three pairs of typical evaluation cas-es demonstrate that the method is capable of distinguishing scenes with different similarity levels at a fine-grained level.Furthermore,to quantitatively validate the effectiveness of the method,an ANOVA experiment is conducted to compare scenario similarity with the performance of the autopilot system.The experimental results reveal that the safety and efficiency of the system exhibit significant differences under test conditions with different levels of scenar-io similarity,thus proving the method's effectiveness.Ultimately,this method is applied to optimize Apollo.Ulti-mately,this method rformance of the autopilot system.The experimental results reveal that the safety and efficiency of the system exhibit significantd

autonomous drivingurban intersection scenariossimilarity evaluationdirected graphdynamic time warping

李江坤、纵瑞雪、邓伟文、王莹、丁娟

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北京航空航天大学交通科学与工程学院,北京 100191

吉林大学计算机科学与工程学院,长春 130025

浙江天行健智能科技有限公司,嘉兴 314000

自动驾驶 城市交叉口场景 相似性评价 有向图 动态时间扭曲

2025

汽车工程
中国汽车工程学会

汽车工程

北大核心
影响因子:0.751
ISSN:1000-680X
年,卷(期):2025.47(1)