The aim of this work is to investigate dynamic division of highway control subareas based on improved Label Propagation Algorithm (LPA) for implementing different signal control strategies in the subareas to improve operation efficiency. A highway network is used as the studied object, where each road segment is defined as a node and the network is divided into three types of nodes: only mainline segment, an on-off-ramp and its connecting mainline, and an overpass. The system is abstracted as a topological set of nodes and their relationships. The concept of multiroad segment correlation degree with predictive function of congestion and dissipation ranges is proposed. The correlation degree model of multiroad segments based on Pearson Correlation Coefficient (PCC) and the importance degree model of road segment based on technique for order preference by similarity to ideal solution (TOPSIS) are established, respectively. Then a dynamic division method of control subareas for highway network is proposed based on improved LPA, where the label updating model based on the importance degree of road segment is established by semisupervised classification algorithm. Multiple scenarios were discussed using the highway network of Baoding City in Hebei Province of China as an example. The results show that the number of subareas is moderate, the internal state is uniform, and the calculation is simple and efficient. The control effect is remarkable especially when the vehicle distribution is uneven. Total delay time is reduced by 10.47%, 4.38%, 4.24%, 9.73%, and 2.33%, respectively, and total travel time is reduced by 12.20%, 7.15%, 7.02%, 11.85%, and 3.78%, respectively, compared with no control method, global control method, the static division method by clustering algorithm, the method by normal LPA algorithm, and the method by Newman algorithm.
Dynamic Division of Control Subareas for Highway Networks Based on Improved Label Propagation Algorithm
J. Transp. Eng., Part A: Systems
2024-09-01
Article (Journal)
Electronic Resource
English
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