# Median U-Turn Intersection Critical Parameter Research and Operational Performance Evaluation
## 8 Conclusions  
This paper proposes theories for determining the critical parameters of MUT intersections. It also presents a delay model of MUT intersections based on vehicle dynamic operations. Vehicle average delay is chosen as the evaluation index. We analyzed which possible factors can impact the performance of MUT intersections, such as the separation distance, the gap of the median U-turn, the proportion of left-turn vehicles, and green phase percentage, etc. Based on the results of the simulation experiments, the following conclusions can be drawn:  
1. The critical parameters of MUT intersections can be concluded as one of the important factors affecting vehicle average delay. 2. Compared to the VISSIM model, the proposed cellular automata model demonstrates relatively high accuracy, with the errors around 7%. 3. Compared to the current intersection, the modified intersection performs better in reducing vehicle average delays in various conditions. The established framework offers a systematic analytical method to better obtain a series of operational performance metrics for MUT intersections. Additionally, this framework also helps us understand the dynamic variation in vehicle average delay under different simulation parameters for further exploring MUT intersections. Additionally, we conduct a stakeholder analysis to enhance the practical application and value of this study's findings. The major stakeholders include traffic control operators, local authorities, and road safety authorities. For traffic control operators, the proposed delay model provides a valuable tool for optimizing signal timing at MUT intersections, improving traffic flow and reducing delays, which facilitates more efficient road use and congestion management. Local authorities and transportation planners can use the study's insights to inform the design and upgrading of MUT intersections, incorporating the model's critical parameters to address varying traffic volumes and operational needs, leading to more efficient transportation networks. Moreover, road safety authorities can apply the delay model to assess the safety and efficiency of MUT intersections, contributing to improved road safety and reducing accidents. Based on these considerations, it is recommended that these stakeholders integrate the delay model and its parameters into intersection design and modification processes to optimize traffic performance, promote safety, and improve the overall transportation system. However, it is worth noting that the proposed cellular automata model still has some limitations. For instance, we do not take into account the impact of the width of the median U-turn on the performance of MUT intersections. Moreover, under a uniform vehicle arrival rate at each entrance, the proposed cellular automata model may still perform well enough in different simulation environments. Future research should explore several areas as follows. First, the impact of the median U-turn width on intersection performance should be explored because this factor can enhance predictive accuracy, especially for intersections with varying U-turn designs. Additionally, the model's assumption of uniform vehicle arrival rates should be revised to account for non-uniform traffic flow, which would improve its robustness and applicability. Finally, extending the model to other intersection types, such as signalized intersections and roundabouts, would help evaluate the broader applicability of the proposed framework. These improvements would enhance the model's versatility and accuracy, making it a more effective instrument for traffic management in diverse environments. We will consider more relevant factors to further improve the accuracy and applicability of the proposed cellular automata model. Conceptualization, X.L. and W.Z. ; methodology, C.Z. and X.L. ; writing--original draft preparation, C.Z. and T.W. ; investigation, C.Z. and T.W. ; writing--review and editing, X.L. and W.Z. All authors have read and agreed to the published version of the manuscript.