Signal Control Method for Urban Road Networks Based on Dynamic Identification of Critical Nodes
Abstract
:1. Introduction
2. Brief Review of Previous Research
2.1. Identification of Critical Nodes in the Road Network
2.2. Dynamic Signal Control Methods
3. Problem Description
4. Optimization Model
4.1. Identification of Critical Nodes Based on Multi-Attribute Decision-Making
- Standardization of the Critical Node Evaluation Matrix
- ii.
- Determination of the Weight of the Evaluation Index
- iii.
- Comprehensive Sorting of Critical Nodes
4.2. Signal Collaborative Control Process for the Road Network
5. Experiment and Analysis
5.1. Experimental Road Network
5.2. Dynamic Identification of Critical Nodes
5.3. Road Network Control Based on Critical Node Identification
6. Conclusions
- The multi-attribute decision-making approach allows for a reasonable identification of critical nodes in dynamic road networks. When identifying critical nodes within a road network, it is essential to consider multiple attributes. Traffic flow at nodes serving multiple origin–destination (OD) pairs may not always be high.
- The road network signal cooperative control strategy developed in this study, which is based on the dynamic identification of critical nodes, enhances travel time reliability. The signal control strategy that focuses on critical node recognition proved to be effective, particularly in low-traffic scenarios, doubling travel time reliability compared to the fixed-time control strategy. Additionally, the adaptive control scheme is better suited to accommodate fluctuations in traffic flow within the road network.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Critical Components | Signal Control Methods for Road Networks | Optimized Performance Metrics | Experimental Platform/Applicable Scenarios |
---|---|---|---|
Critical Intersections (Critical Nodes) |
|
|
|
Critical Road Sections or Critical Paths |
|
|
|
This Research | |||
Real-Time Critical Nodes |
|
| Experiments based on Dynameq 2.13 and Matlab R2018a |
: | The node in the road network, ; |
: | The criterion for identifying the critical node, ; |
: | Link in the road network, ; |
: | The traffic flow on link connecting node during time window , pcu/h; |
: | The evaluation matrix of critical nodes during time window ; |
: | The number of OD pairs through node during time window ; |
: | The traffic volume through node during time window , pcu/h; |
: | The average delay of vehicles through node during time window , s; |
: | The ratio of average delay to average travel time of vehicles through node during time window ; |
: | The weight coefficient of OD pairs; |
: | The weight coefficient of the traffic volume; |
: | The weight coefficient of the average delay; |
: | The weight coefficient of the ratio of average delay to average travel time; |
: | The standardized evaluation matrix of nodes during time window ; |
: | The contribution degree of node under criterion ; |
: | The weighting coefficient of criterion ; |
: | The criticality of node during time window ; |
: | The optimal signal cycle, s; |
: | The total lost time, s; |
: | The sum of the maximum flow ratios for all signal phases within a cycle; |
: | The cycle length, , s; |
: | The green time ratio; |
: | The degree of saturation; |
: | The correction factor for node signal control types, with a value of 0.5 for pre-timed signal controls; |
: | The capacity of lanes, pcu/h. |
Control Strategy | Control Scheme | ||||||
---|---|---|---|---|---|---|---|
Applicable Objects | Signal Timing | ||||||
Cycle/s | Green Light/s | Red Light/s | Yellow Light/s | Full Red/s | |||
Pre-timed Control | All Nodes | 70 s | 32 | 32 | 3 | 3 | |
Pre-timed Control Based on Critical Node Identification | Critical Nodes | 100 | 47 | 47 | 3 | 3 | |
Other Nodes | 70 s | 32 | 32 | 3 | 3 | ||
Scheme Selection Adaptive Control | Control Scheme 1 | Critical Nodes | 100 | 47 | 47 | 3 | 3 |
Other Nodes | 70 s | 32 | 32 | 3 | 3 | ||
Control Scheme 2 | All Nodes | 100 | 47 | 47 | 3 | 3 |
Number of Nodes | OD Pairs | Number of Nodes | OD Pairs |
---|---|---|---|
1 | 11 | 9 | 10 |
2 | 11 | 10 | 6 |
3 | 19 | 11 | 10 |
4 | 12 | 12 | 10 |
5 | 9 | 13 | 17 |
14 | 11 | ||
7 | 11 | 15 | 13 |
8 | 7 | 16 | 15 |
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Hang, J.; Wang, J.; Tang, T. Signal Control Method for Urban Road Networks Based on Dynamic Identification of Critical Nodes. Sustainability 2025, 17, 3286. https://doi.org/10.3390/su17083286
Hang J, Wang J, Tang T. Signal Control Method for Urban Road Networks Based on Dynamic Identification of Critical Nodes. Sustainability. 2025; 17(8):3286. https://doi.org/10.3390/su17083286
Chicago/Turabian StyleHang, Jiayu, Jiawen Wang, and Tianpei Tang. 2025. "Signal Control Method for Urban Road Networks Based on Dynamic Identification of Critical Nodes" Sustainability 17, no. 8: 3286. https://doi.org/10.3390/su17083286
APA StyleHang, J., Wang, J., & Tang, T. (2025). Signal Control Method for Urban Road Networks Based on Dynamic Identification of Critical Nodes. Sustainability, 17(8), 3286. https://doi.org/10.3390/su17083286