A New Hybrid Hierarchical Roadside Unit Deployment Scheme Combined with Parking Cars
Abstract
:1. Introduction
2. Related Work
3. Backgrounds
Mobile Mode Analysis for Traffic Multi-Agent
4. Scenario Description and Basic Definition
4.1. The Concept of the t-RSU and Its Mechanism
Algorithm 1: t-RSU Score |
Input: Output: the outcome score of weighted S(SCA, ECA), S(RCA) as 0 do then End End |
- SCA represents the self-coverage area of the parked car, and are the partitions of the self-coverage area.
- ECA is the existing coverage area covered by other temporary t-RSUs; are the partitions of the temporary coverage area.
- RCA is the redundant area that overlaps between the currently parked car and other temporary t-RSUs. Meanwhile, since the overlapped area is 3D in the real world (due to the existence of underground and above-ground garages), here we use for calculating it by projecting the area in the 2D map.
- and are the coefficients for the S(SCA, ECA) and S(RCA), respectively, which can be used to determine the score and set the threshold for whether a new parked car should become a t-RSU.
4.2. Optimize RSUs Deployment with Already-Existing t-RSUs
Branch and Bound Algorithm
5. Simulation Analyses and Results
5.1. Simulation Analyses
- Vehicle coverage ratio, which is the ratio between the total number of vehicles that come in contact with the RSUs or t-RSUs and the total number of vehicles in the confined area.
- Point-to-point connectivity, which is the reflection of the reachability between two random positions in the area.
5.2. Results
6. Conclusions and Future Work
6.1. Conclusions
6.2. Future Works
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Step | Description |
---|---|
Step 1 | If the problem is to minimize the solution, the current optimal solution is set as . |
Step 2 | According to the branch rule, a node is selected from the nodes that have not been searched at present, and it is divided into several new nodes in the next level of the node. |
Step 3 | Calculate the lower limit of each new branch node. |
Step 4 | If either of the following conditions is satisfied, it is not considered: 1. The node does not contain a feasible solution. 2. The lower limit of the node is greater than or equal to the current A value. 3. If a feasible solution with a minimum lower limit value in the node is found, it is necessary to further compare the feasible solution with the current A value. If the latter is small, it needs to be discarded. |
Step 5 | Determine whether there are nodes that have not yet been searched. If there are, step 2 is performed. If not, the calculation is stopped, and the optimal solution is obtained. |
Parameter | Value |
---|---|
Density of Vehicles (veh/km2) | 37.5, 112.5, 187.5 |
Total Given Cost | 5 units |
Simulated Area | Downtown area of Shanghai, China |
Communication Range | 100 m, 300 m, 500 m |
Traffic Data Source | Historical traffic data in Shanghai |
Car-Following Model | CarFollowingModel-Krauss [27] |
Lane-Changing Model | LC2013 [28] |
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Li, H.; Ji, Y.; Wang, Z. A New Hybrid Hierarchical Roadside Unit Deployment Scheme Combined with Parking Cars. Appl. Sci. 2024, 14, 7032. https://doi.org/10.3390/app14167032
Li H, Ji Y, Wang Z. A New Hybrid Hierarchical Roadside Unit Deployment Scheme Combined with Parking Cars. Applied Sciences. 2024; 14(16):7032. https://doi.org/10.3390/app14167032
Chicago/Turabian StyleLi, Hongming, Yuqing Ji, and Ziwei Wang. 2024. "A New Hybrid Hierarchical Roadside Unit Deployment Scheme Combined with Parking Cars" Applied Sciences 14, no. 16: 7032. https://doi.org/10.3390/app14167032
APA StyleLi, H., Ji, Y., & Wang, Z. (2024). A New Hybrid Hierarchical Roadside Unit Deployment Scheme Combined with Parking Cars. Applied Sciences, 14(16), 7032. https://doi.org/10.3390/app14167032