Comprehensive Evaluation on Traffic Safety of Mixed Traffic Flow in a Freeway Merging Area Based on a Cloud Model: From the Perspective of Traffic Conflict
Yaqin He, Jun Xia · Symmetry · 2025
As human-driven vehicles (HDVs) and autonomous vehicles (AVs) coexist on the road, the asymmetry between their driving behaviors, decision-making processes, and responses to traffic scenarios introduces new safety challenges, especially in complex merging areas where frequent interactions occur. The existing traffic safety analysis of mixed traffic is mainly to analyze each safety index separately, lacking comprehensive evaluation. To investigate the safety risk more broadly, this study proposes a comprehensive safety evaluation framework for mixed traffic flows in merging areas from the perspective of traffic conflicts, emphasizing the asymmetry between HDVs and AVs. Firstly, an indicator of Emergency Lane Change Risk Frequency is introduced, considering the interaction characteristics of the merging area. A safety evaluation index system is established from lateral, longitudinal, temporal, and spatial dimensions. Then, indicator weights are determined using a modified game theory approach that combines the entropy weight method with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, ensuring a balanced integration of objective data and expert judgment. Subsequently, a cloud model enhanced with the fuzzy mean value method is then developed to evaluate comprehensive safety. Finally, a simulation experiment is designed to simulate traffic operation of different traffic scenarios under various traffic flow rates, AV penetration rates, and ramp flow ratios, and the traffic safety of each scenario is estimated. Moreover, the evaluation results are compared against those derived from the fuzzy comprehensive evaluation (FCE) method to verify the reliability of the comprehensive evaluation model. The findings indicate that safety levels deteriorate with increasing total flow rates and ramp flow ratios. Notably, as AV penetration rises from 20% to 100%, safety conditions improve significantly, especially under high-flow scenarios. However, at AV penetration rates below 20%, an increase of the AV penetration rate may worsen safety. Overall, the proposed integrated approach provides a more robust and accurate assessment of safety risks than single-factor evaluations, providing deeper insights into the asymmetries in traffic interactions and offering valuable insights for traffic management and AV deployment strategies.