# Optimal Lane Allocation Strategy in Toll Stations for Mixed Human-Driven and Autonomous Vehicles
## 4 Numerical Experiments
### Discussion
#### 4.3.3. Dynamically Adjusting Lane Allocation Exhibits Significant Potential  
Under the same vehicle arrival rates at both the entry and exit points, adjusting the toll booth lane allocation based on our optimization model consistently outperforms the current system, with increasingly pronounced improvements as traffic volume rises. Moreover, the number of curves in Figure 6(a) exceeds that in Figure 6(b), and the maximum value on the x-axis of Figure 6(a) is greater than that of Figure 6(b). These findings indicate the effectiveness of our model, showing that lane allocation adjustments based on our optimization approach enable toll booths to better manage high traffic volumes. Additionally, dynamically adjusting lane allocation in response to changes in vehicle arrival rates proves to be a more effective supply strategy than maintaining a static allocation.  
Certainly, we must recognize that dynamic lane allocation adjustment faces multiple challenges in practical implementation. First, it relies heavily on the acquisition and processing of real-time data, requiring toll stations to possess efficient data collection and analysis capabilities. However, under high traffic volumes or complex traffic conditions, data delays and technological limitations may affect the timeliness of adjustments. Secondly, accurately predicting changes in traffic flow is inherently difficult, as traffic volumes are influenced by numerous factors such as weather, accidents, and holidays, thereby increasing the complexity of making timely adjustments. Furthermore, existing tolling infrastructure and hardware (e.g., tidal lanes and variable toll rate signs) may not be capable of quickly or flexibly adapting, as these adjustments often involve high costs and operational difficulties. Operators also need to make rapid decisions, which necessitates specialized training and efficient coordination, particularly during peak periods, where slow response times could become a bottleneck. Another challenge is the compatibility issue between different systems--such as traffic management, tolling, and monitoring systems--whose technological disparities could complicate implementation. While dynamic adjustments can improve efficiency, they also require significant financial investment in facility upgrades, technological inputs, and ongoing maintenance, which could be a substantial burden for toll stations with limited resources. Additionally, regional differences play a significant role, as toll stations in various areas may differ in traffic flow, infrastructure, and available resources. In regions with low traffic or minimal demand, static lane allocation may already suffice, making dynamic adjustment unnecessary or infeasible. In conclusion, while dynamic lane allocation adjustment has the potential to significantly enhance efficiency in highway toll stations, its complexity, costs, and implementation challenges make it difficult to achieve in many cases. However, with the advancement of smart tolling systems, we believe the application potential of this approach is immense.