# A Hybrid Control Path Planning Architecture Based on Traffic Equilibrium Assignment for Emergency
## 6 Conclusions and Future Work  
The hybrid control path planning perceives the background traffic and evolution volume of the system to make individual path decisions. This paper first predicts the dynamic traffic load in large-scale networks using multidimensional features to provide a more accurate dynamic road network state for system-compatible emergencies. Then, its models macro and micro information using the adaptive multi-feature fusion technique, mapping the offline SO flow assignment method to generate equilibrium distribution graphs considering dynamic traffic states. Finally, the potential travel demand is assigned in a data-driven manner online in real time. Hybrid control path-planning techniques increase the diversity of path choices for evacuating travelers by sensing both macro and micro information, which is conducive to improving the capability of the transportation system to rapidly return to normality in emergencies. As this paper adopts the way of training the prediction and assignment model in advance, the network-wide dynamic traffic flow can be obtained in real time in the actual path-planning decision-making. Through the mapping of the assignment process without iteration, the algorithm can give the traffic assignment plan in real time, which is well adapted to the needs of rapid planning decisions in emergencies. The current method applies to daily traffic and roads with temporary emergencies. It cannot be adapted to major disasters scenarios where the structure of the road network changes (e.g., earthquakes). This is because the forecasting method used involves the impact of the network's structural characteristics. Since ST-ETA cannot learn the maximum carrying capacity of the roadway, it allows roadway flows to be diverted when they exceed the average optimal distribution. While this alleviates the load on critical roads, it will result in a slight increase in the total evacuation time. In future work, a limit on the maximum load of the network can be added to the spatio-temporal network training to bring it closer to the SO optimal flow distribution. Otherwise, given the current state of emergency data and subject routes data collection, the model in this paper has some limitations at the data and validation level. The future work intends to collect and simulate more representative data of normal and non-normal scenarios, so as to further verify and compare the model performance under different scenarios in detail, and make more scenario-specific improvements to the model. Figure 11: Comparison of hybrid control planning path and shortest path. **Author Contributions:** Conceptualization, Z.Z. and M.C. ; Methodology, Z.Z., Z.C., and M.C. ; Software, Z.Z. ; Writing--original draft, Z.Z. ; Validation, Z.Z., Z.C. and M.C. ; formal analysis, Z.C. and M.C. ; investigation, Z.Z. ; resources, Z.D. ; data curation, M.C. and Z.D. ; funding acquisition, Z.D. and Z.C. All authors have read and agreed to the published version of the manuscript. **Funding:** This work is supported by the National Key R & D Program of China under Grant 2022 YFF0503900, the Key R & D Program of Shandong Province under Grant 2021 CXGC010104, the National Natural Science of Foundation of China under Grant 62072016, Beijing Natural Science Foundation under Grant 4212016, and the Humanities and Social Sciences Foundation of the Ministry of Education under Grant 21 YJA790009. **Data Availability Statement:** The OpenStreetMap data presented in this study are available from [[https://www.openstreetmap.org/](https://www.openstreetmap.org/)]([https://www.openstreetmap.org/](https://www.openstreetmap.org/)) (OpenStreetMap, accessed on 28 December 2021). Restrictions apply to the availability of Didi Chuxing data. Data were obtained from [[http://gaia.didichuxing.com/](http://gaia.didichuxing.com/)]([http://gaia.didichuxing.com/](http://gaia.didichuxing.com/)) (Didi Chuxing, accessed on 23 December 2021). These data are available from the authors upon contact.