Signal-Vehicle Coordination Control Modeling and Roadside Unit Deployment Evaluation under V2I Communication Environment

Signal-vehicle coordinated control holds substantial promise for enhancing urban transportation efciency. However, its development faces notable challenges: (1) most existing studies have been conducted based on the assumption of perfect communication conditions. Tis assumption overlooks the signifcant impact of vehicle-to-infrastructure (V2I) communication quality on control performance, which leads to poor applicability in practice. (2) Te evaluation of roadside unit (RSU) deployment for optimizing signal-vehicle control has not been well studied. Hence, the modeling of signal-vehicle coordination control and RSU deployment evaluation under V2I environment are studied in this paper. First, we introduce a communication model that characterizes the imperfections in communication between RSUs and connected vehicles (CVs). Second, we propose a model for signal-vehicle coordination control within this connected environment. Tis model integrates strategies from both signal control optimization and the speed optimization of CV platoons. Finally, to assess the impact of the RSU deployment parameters on the performance of signal-vehicle coordination control, we introduce a systematic evaluation method. Te reduction in vehicle delays is introduced as the evaluation indicator for control performance. Six other indicators—the number of vehicles in the RSU communication domain, connectivity probability between the CV and RSU, number of vehicles whose speeds are successfully optimized, number of speed adjustments, green extension time, and overlap rate of the communication domains of multiple RSUs—are introduced as the observation indicators. Te simulation experiments verify the efectiveness of the proposed model in implementing signal-vehicle coordination control under imperfect communication and environments in low-trafc, medium-trafc, and high-trafc scenarios. Furthermore, these experiments show the quantitative impact of RSU deployment parameters (communication distance, command transmission cycle, installation position, and number of RSUs) on control performance.


Introduction
Emerging vehicle-to-everything (V2X) technologies are a promising approach to addressing urban transportation network congestion.Owing to the limited computing capability of on-board units and the time-varying characteristics of vehicles [1], vehicle-to-vehicle (V2V) communication is insufcient for trafc control.To enhance the reliability of connected control, V2I communication technology has been incorporated, creating an extensive V2X communication domain through RSU deployment.RSUs receive real-time data from CVs and the signal controller and upload them to multiaccess edge computing (MEC) devices to generate control strategies.Tis facilitates signal-vehicle coordination control with a broader scope and more cooperative elements.Terefore, the scientifc and efcient implementation of signal-vehicle coordination control has become a popular topic.
Current signal-vehicle coordination control strategies primarily concentrate on optimizing trafc indicators.Teir goals include minimizing trafc pollution [2][3][4], enhancing trafc fow safety performance [5][6][7], and maximizing transportation efciency [8][9][10][11].Tese strategies compensate for the limited data resources and control range of traditional signal control methods [12,13].In particular, the vehicle platooning is an efective way to improve trafc capacity and energy consumption [14,15].Platoons are employed as control objects in studies to develop control strategies.To minimize the total travel time of connected autonomous vehicles (CAVs), Ding et al. [16][17][18] introduced an optimal phase allocation and trajectory control method for CAV platoons, assuming instant interaction between all CAVs and the control center.Based on real-time and lossless communication conditions, Feng et al. [19,20] proposed a signal-platoon coordinated control strategy to enhance intersection throughput.Chen et al. [21] developed a multiplatoon trajectory optimization approach to achieve safe, fuel-efcient, and efcient operations.In scenarios with low CV penetration rates, Li et al. [22][23][24] proposed a real-time predictive coordination method based on vehicle-triggered platoon dispersion to enhance control performance.However, these studies were conducted based on the assumption of perfect communication conditions between RSUs and CVs.Te impacts of V2I communication conditions on signal-vehicle control performance have been ignored.For instance, factors such as the communication distance of RSUs and the connectivity probability between CVs and RSUs can afect the number of CVs that can participate in signal-vehicle control.Finkelberg et al. [25] experimentally demonstrated that realistic communication distortion conditions worsen the performance of trafc control.Neglecting the infuence of imperfect communication conditions in these studies may limit their practical applicability.
Modeling an imperfect V2I communication environment is essential for signal-vehicle coordination control.In the V2I environment, RSUs play a pivotal role in gathering essential information from CVs and signal controllers, calculating control strategies, and delivering control commands [26].Tus, further exploring the impacts of RSU deployment on signal-vehicle control performance is a meaningful topic.
To date, several studies have discussed the impact of RSU deployment on V2I communication quality, such as communication coverage [27], communication connectivity [28,29], and communication delays [30,31].Liang et al. [32] presented an RSU deployment method to guarantee that V2I communication delays would remain below a threshold with the lowest cost.However, this method lacks applicability to emerging technologies that include 5G.Sankaranarayanan et al. [26] proposed a fusion algorithm-based optimal RSU distribution planner (ORDP).Te ORDP is capable of constructing an objective function by selecting parameters such as RSU deployment cost, RSU transmission capacity, and communication coverage to meet the requirements of the scenario.However, it disregards the communication performance parameters including connectivity probability and transmission delay.Consequently, these studies fail to thoroughly analyze the efects of communication quality resulting from specifc RSU deployments on control performance.Tus, these studies still cannot determine the impact mechanism of RSU deployment on signal-vehicle control performance.
Most RSU deployment studies have optimized deployment parameters for better perception of urban trafc fow.Barrachina et al. [33] formulated a density-based RSU deployment approach.Li et al. [34] established a model to investigate the relationship between RSU deployment, vehicle travel time, and trafc capacity.Olia et al. [35] proposed an RSU deployment optimization model to minimize RSU estimation errors for vehicle travel time.Salari et al. [36] developed a mathematical model to identify optimal RSU deployment for path fow reconstruction.However, few RSU deployment studies have explored the impact of deployment parameters on signal-vehicle control performance.Fang et al. [37] and Du et al. [38] noted that changes in RSU deployment can lead to communication disturbances affecting control performance, but a comprehensive theoretical and experimental analysis of these mechanisms is lacking.To address this gap, our study delves into the impact mechanism of RSU deployment parameters on signalvehicle control performance.
In conclusion, the development of signal-vehicle coordination control encounters several challenges: (1) most existing studies assume ideal communication conditions between RSUs and CVs.Te impacts of V2I communication conditions on signal-vehicle control performance are ignored in these studies, which limits practical applicability.
(2) Te evaluation of RSU deployment for signal-vehicle control optimization has not been well studied.Hence, this paper focuses on modeling signal-vehicle coordination control and evaluating RSU deployment under V2I environment.
Te main contributions are summarized as follows: (  Te study scenario at an isolated signal intersection under V2I environment is shown in Figure 2.

Methodology
Tree assumptions are made in this paper.
(1) Te communication between the RSU, the MEC server, and the signal controller is considered to be without transmission loss and delay.In addition, the signal controller executes the optimization strategy received from an RSU.
(2) All the vehicles are CVs, and all the vehicle members of a CV platoon are assumed to be within the communication range of the leading vehicle.
(3) Considering the CV platoon as a control unit, the complex behaviors between CV vehicles, such as decomposition and reorganization in the CV platoon, are not described.Te RSU transmits information to the platoon's leading CV, and the following CVs always follow the commands from their preceding cars.

Communication Model of the RSU and CV Platoon 2.2.1. Defnition of an RSU Deployment
Scheme.An RSU deployment scheme is defned as a quadruple U � (D rsu , T com , X rsu , N rsu ), where D rsu is the RSU communication distance, T com is the RSU command transmission cycle, X rsu is the RSU deployment position, and N rsu is the RSU number.Te communication domain of an RSU is determined by its position and communication distance.Within the communication domain, an RSU can exchange information with CVs with a certain connectivity probability.Te MEC server connected to the RSU subsequently generates a control strategy in response to the trafc fow and transmits it to the CVs in a regular cycle.Ten, the communication topology between the RSU and the CV is updated.

Communication Connectivity Probability between the RSU and CV Platoon.
Te number of CVs and the number of RSUs are p and q, respectively.To establish a plane rectangular coordinate system, this paper sets the center of the intersection as the origin, east as the positive direction of the x-axis, and north as the positive direction of the y-axis.Let X j rsu represent the position of the RSU.D j rsu denotes the communication distance of RSU j, and X i veh represents the position of CV i. CVs interact with RSUs via shortwave communication.
In equation ( 1), d ij vr represents the distance between RSU j and CV i.If d ij vr ≤ D j rsu , RSU j has the opportunity to establish a communication connection with CV i.
During information transmission, the information will undergo signal attenuation due to factors such as obstacle occlusion.An RSU and a CV are directly connected only when the received power P r exceeds a predefned threshold P th .Te received power P r and the communication probability P(d ij vr ) between RSU j and CV i is given by the following equations [39]: where P t is the transmitted power, PL(d 0 ) is the reference path loss at a critical distance d 0 , α is the path loss exponent, and Z σ is a Gaussian random variable with zero mean and standard deviation σ.

Command Transmission Cycle between the RSU and CV Platoon.
Based on successful communication behaviors, the signal phase and timing (SPAT) message generated in the RSU, together with the real-time CVs' basic safety message (RSM), are sent back to the MEC, where the trafc control strategies are calculated.Te strategies are sent to the CVs via the downlink according to the transmission cycle T com .
As the guidance command is distributed periodically, the successful transmission probability of the guidance information at time t is described by the following equation: Te RSU regularly sends guidance commands to CVs.In such a case, the probability that a CV receives command and updates its motion at any time t is P ij c .Te frst step is to initialize the trafc state and the signal timing scheme.Subsequently, the RSU communicates with the CV platoon within its communication domain and estimates the time required by the CV platoon to pass the intersection.Combined with the SPAT, the RSU determines whether to transmit a suggested speed to the platoon.If the suggested speed is transmitted, the CV platoon will implement the speed adjustment command.Otherwise, the platoon will stop at the stop line to wait for the next green time.

Speed Optimization of the CV Platoon.
Te RSU ofers a suggested speed to the target CV platoon in the communication, with the aim of minimizing the total travel time of the CV platoon and enabling the platoon to cross the intersection within the green time (including the green extension time).
When an RSU communicates with the CV platoon, the remaining passing time for the platoon is T l .To calculate the suggested speed, two scenarios are considered in this paper.Te frst scenario is that no vehicle is ahead of the target CV platoon.Te objective function can be formulated as in the following equation: 4 Journal of Advanced Transportation Let T i a denote the travel time that the platoon i takes to pass the intersection from its current position.In equations ( 8) and ( 9), the parameter ρ indicates whether the platoon i is capable of crossing the intersection by accelerating from the current speed v i p to the suggested speed v. T i acc(1) represents the time that platoon i takes to accelerate to the suggested speed.T i constant represents the time that platoon i takes to pass the intersection in a uniform velocity after the acceleration to the suggested speed.T i acc(2) represents the time that platoon i takes to pass the intersection at the suggested speed.L i represents the distance from the last vehicle in the platoon i to the stop line.In equation (10), L i 1 denotes the distance from the leading vehicle in the platoon i to the stop line.L car denotes the vehicle length.L in is the distance between CVs within a platoon.m i and a i p are the vehicle number and the acceleration of the platoon i, respectively.
In the second scenario, other CVs travel in front of the platoon i.To mitigate the interference of the vehicles ahead of platoon i, in addition to the target platoon, the RSU controls the CVs ahead of platoon i.If all vehicles ahead of the CV platoon i are in the RSU communication domain, the RSU incorporates the front vehicles into the target platoon i. Te size of the platoon is expanded, and the frst vehicle of the updated platoon becomes the leading vehicle.Te RSU transmits the suggested speed to the leading vehicle of the updated platoon.Te guidance strategy is calculated by the equations ( 7)- (13).The CV platoon stops at the stop line to wait for next green time

Journal of Advanced Transportation
According to the speed v l of the preceding platoon, RSU transmits the following speed v g to the leading vehicle of the platoon i. Te following model is utilized to calculate the speed v g [40].
In equation ( 14), v free denotes the free-fow speed.a max represents the maximum acceleration of the vehicle.d s and d lf are namely the safe distance and the distance between the follower and the leader.
Since a CV outside the RSU communication domain fails to receive guidance information, the motion of the target platoon i will be infuenced.Terefore, the RSU steers all CVs within the communication range as a platoon, which follows the last CV inside the RSU communication domain.Te speed data of the CVs outside the RSU communication domain is transmitted by a holographic detection device to the RSU.Te RSU calculates the suggested speed according to equation (14).Te travel time T b of platoon i is given by the following equation: where Q and M denote the number of CVs outside and inside the RSU communication domain, respectively.T lr represents the remaining red time, T s represents the saturation fow rate, and T q represents the vehicle start-up loss time.
Te mentioned objective function is supposed to meet two constraints: (i) the suggested speed is within the range composed by the minimum speed v min and the maximum speed v max and (ii) the suggested speed is sufcient for the target platoon to pass the intersection within the remaining passing time.Hence, the constraints can be denoted as equation (16).T ∈ T a , T b   represents the time that the platoon takes to pass the intersection.
Based on the estimated time of the platoon and the SPAT, the RSU evaluates the platoon's current motion status.When the platoon is capable of passing the intersection within the remaining travel time, the RSU transmits a suggested speed to the target CV platoon.

Signal Control Optimization.
If the time required by the platoon to pass the intersection is greater than the current remaining green time T lg , the RSU evaluates whether to execute a green extension strategy according to the following equation: where G max is the maximum green extension threshold.Q c and T og are the average vehicle queue length and green time of uncontrolled phases, respectively.If y > 0, the green extension time required by the platoon to pass the intersection exceeds the threshold.Tus, the platoon drives based on the car-following model and the signal timing scheme remains unchanged.If y ≤ 0, the green extension time required by the platoon to pass the intersection lies within the threshold.In such case, the RSU transmits a command to the signal controller for the green extension.Te green extension time T len is presented as follows:

Impacts of RSU Deployment on the Performance of Signal-Vehicle Coordination Control.
Te RSU deployment scheme infuences the implementation performance of the signalvehicle coordination control strategy via communication interaction with CVs and signal controllers.Trafc delay is an essential index for evaluating the service level of an intersection [41].Consequently, the reduction in vehicle delays is employed to evaluate the signal-vehicle coordination control performance, and six other indicators are selected as observation indexes to construct the evaluation index system for the RSU deployment scheme (see Table 1).CVs are categorized into three types in the proposed scenario.(1) CVs geographically located in the RSU communication domain, whose average number per second is defned as C; (2) CVs in the RSU communication domain that may pass through the intersection without stopping via RSU control; and (3) CVs in the RSU communication domain that successfully execute the speed adjustment command and pass through the intersection without stopping during the corresponding signal cycle (including the green extension time), whose number is defned as K.
Te number H of speed adjustments and the number K of vehicles whose speeds are successfully optimized are two indicators that quantify the changes in vehicle operation under the coordinated control.Te green extension time G ext is an indicator that quantifes the changes in signal parameters under coordinated control.Moreover, multiple RSUs may have an overlapping area of communication.Te lower the overlap rate Z is, the higher the number C of vehicles in the communication domain is.

Simulation and Analysis
3.1.Scenario Description.We use simulation of urban mobility (SUMO) to build a four-approach signalized intersection, and the length of each approach is 1 km.Te simulation time is 3600 s.Te experimental parameter 6 Journal of Advanced Transportation  2. For the threshold of received power and average distance between CVs within a platoon given in Table 2, refer to [42,43], respectively.We consider three diferent trafc fow modes: low, medium, and high trafc fows, represented by trafc fows of 400 veh•h − 1 • lane − 1 , 800 veh•h − 1 • lane − 1 , and 1200 veh•h − 1 • lane − 1 , respectively.Under these three modes, the intersection saturation values are approximately 0.3, 0.6, and 0.9, respectively.Te ratio of north-south trafc fow to east-west trafc fow is 4 : 3, and the north-south trafc fow is the major trafc fow.In this paper, we focus on the northsouth trafc fow as the RSU control target.In the single-RSU deployment scenario, the RSU is positioned at the south approach of the intersection.In the multiple-RSU deployment scenarios, RSUs are installed at the south and north approaches of the intersection.Te parameters of the RSU deployment schemes are presented in Table 3.
In order to investigate the impacts of RSU deployment parameters on performance of signal-vehicle coordination control, RSU deployment scheme for diferent analysis is shown in Table 4.
As shown in Figure 4, the RSU is designed on SUMO, and the blue area is the communication range of the RSU.

Impacts of RSU Communication Distance on Control
Performance.As illustrated in Table 4, this section utilizes the RSU deployment schemes of U1-U5 for low, medium, and high trafc fows, where the RSU number, position, and command transmission cycle are unchanged.A single RSU with a communication distance of D rsu � 100,200, { 300,400,500} is deployed at the roadside location of stop line on the south approach.
Figure 5(d) presents the impacts of RSU communication distance D rsu on the reduction in vehicle delays R in the north-south direction.Under diferent trafc fows, R tends to increase and then decrease, as D rsu increases.From Figure 5(a), it is clear that as D rsu increases, the control range of the RSU expands, and C increases.Figure 5(b) shows that, given the characteristics of wireless transmission, P c drops as D rsu increases.Tis reduces the number of CVs that can successfully receive RSU commands.As shown in Figure 6(c), combining the above two efects, K tends to increase and then decrease as D rsu increases, and R tends to increase and then decrease.
Te peak of vehicle delay reduction is observed at an RSU communication distance of 200 m, because the number of vehicles in the RSU communication domain C has the largest growth, and the connectivity probability between a CV and RSU P c remains at a high level.C increases slowly and P c decreases dramatically when D rsu is larger than 200 m.Te analysis results for the two indicators show that the best choice of RSU communication distance is 200 m.
Overall, the RSU communication distance D rsu afects both the number of vehicles in the RSU communication domain C and connectivity probability between CV and RSU P c .Te combination of two indexes infuences the number of vehicles whose speeds are successfully optimized K, which ultimately changes the reduction in vehicle delays R. 4, this section utilizes RSU deployment schemes of U2, U6-U9 for low, medium, and high trafc fows, where RSU number, position, and communication distance are unchanged.Considering that the travel distance of CV within the cycle needs to be less than the minimum communication distance of RSU, the command transmission cycle is selected as T com � 1, 3, 5, 7, 9 { }.From Figure 6(c), under diferent trafc fows, the reduction in vehicle delays R for the north-south trafc fow follows a decreasing trend as the RSU command transmission cycle T com increases.Further insight into the impacts of the RSU command transmission cycle is provided below.As shown in Figures 6(a) and 6(b), as T com increases, H and G ext decrease.Terefore, R decreases.As T com increases, the number of issued control strategies decreases rapidly.Tis infuences the optimization of the signalvehicle control performance.

Impacts of the RSU Command Transmission Cycle on the Control Performance. As shown in Table
To summarize, the RSU command transmission cycle T com afects both the number of speed adjustments H and green extension time G ext , which eventually infuences the reduction in vehicle delays.As T com expands, H and G ext both display a downward trend, which leads to a decrease in R.

Impacts of the RSU Position on the Control
Performance.As illustrated in Table 4, this section utilizes RSU deployment schemes of U6, U10-U12 for low, medium, and high trafc fows, where RSU number, communication distance, and command transmission cycle are unchanged.A single RSU under diferent positions is deployed to explore the impacts of the RSU deployment position on the control performance.Since the number of vehicles at the intersection is the largest, C tends to decrease as X rsu increases in Figure 7(a).As shown in Figure 7(b), under low trafc fow, the vehicles are free to travel, the control space is large, and P c remains unchanged.When the RSU is located closer to the intersection, C increases.Te coordination control considers a broader range of trafc fows, which leads to an increase in K and R. Terefore, installing a single RSU close to the intersection is efective for reducing vehicle delays in low trafc fows.
Under medium and high trafc fows, queuing vehicles pass through the intersection with a saturation fow rate when the signal turns green.Tese vehicles lack guided space and value.As X rsu increases, the proportion of queuing vehicles in the RSU communication domain is reduced.Te number of vehicles with guided space grows.Consequently, K increases and eventually R displays an upward trend.Further analysis fnds that considering only a static trafc fow is not sufcient for RSU deployment; the behavior and demands of dynamic trafc fow need to be addressed as well.
Te position X rus of an RSU infuences the number of vehicles in the RSU communication domain C. Tis will infuence the number of vehicles whose speeds are successfully optimized K. Consequently, the reduction in vehicle delays R is afected.

Impacts of the RSU Number on the Control
Performance.As illustrated in Table 5, to determine the impacts of the RSU number on the control performance, we adopt RSU deployment schemes U2 and U16 for low trafc fow and U12 and U16 for medium and high trafc fows.In Table 5, compared with the single-RSU deployment scheme, the deployment of two RSUs yields better performance in reducing vehicle delays.Te experiments confrm that increasing the number of RSUs is crucial for enhancing the signal-vehicle coordination control performance.

Conclusions
In this paper, we investigate the modeling of signal-vehicle coordination control and RSU deployment evaluation under V2I environment.First, we develop a communication model of RSU and CV platoons under imperfect communication conditions.Second, a signal-vehicle coordination control strategy is designed to minimize the travel time of the CV platoon.Ultimately, we propose a method of evaluating the impacts of RSU deployment parameters on the performance of signal-vehicle coordination control.Trough simulations, we reveal the impact mechanism of the RSU deployment parameters on the control performance.Te major conclusions are summarized as follows: (1) Te reduction in vehicle delays tends to increase and then decrease as the RSU communication distance increases.(2) Te reduction in vehicle delays decreases as the RSU command transmission cycle increases.(3) Under low trafc fow, the reduction in vehicle delays decreases as the distance between the intersection and RSU position increases.Under medium and high trafc fows, the reduction in vehicle delays increases as the distance between the intersection and RSU position increases.(4) Te reduction in vehicle delays increases as the position of dual RSUs moves away from the intersection.
Tis article presents initial experimental research on the number of RSU deployments.Future research will integrate the installation cost and the number of RSUs to develop an RSU deployment optimization method.Moreover, future research aims to incorporate resource scheduling, communication delay, and other communication models to obtain a more realistic cosimulation model for both transportation and communication networks.

2. 1 .
Overview.As shown in Figure 1, the research framework includes three modules: the communication model of RSU and CV platoons, the signal-vehicle coordination control strategy under a connected environment, and the method to 2 Journal of Advanced Transportation evaluate the impacts of RSU deployment parameters on the performance of signal-vehicle coordination control.Te function of the communication model is to develop an RSU deployment scheme, realize communication connection between the RSU and CV, and determine the command transmission cycle and the communication RSU selection of CVs under multiple RSUs.Based on the communication interactions of RSUs and CVs, a signal-vehicle coordination control strategy is formulated.Te strategy includes the speed optimization of the CV platoon and the signal control optimization.In the third module, a method of evaluating the impacts of RSU deployment parameters on the performance of signal-vehicle coordination control is designed.Te reduction in vehicle delays is used as the evaluation index of the control performance.Six other indicators-the number of vehicles in the RSU communication domain, connectivity probability between the CV and RSU, number of vehicles whose speeds are successfully optimized, number of speed adjustments, green extension time, and overlap rate of the communication domains of multiple RSUs-are employed as observation indicators.Simulation experiments under various RSU deployment parameters are conducted to demonstrate the impact mechanism of RSU deployment on the control performance.
InitializationRSU communicates with the CV platoon in the communication domain RSU predicts the time required by the CV platoon to pass the intersection

Figure 3 :
Figure 3: Workfow of signal-vehicle coordination control under connected environment.

Table 1 :
Relative indicators for impact analysis of RSU deployment on control performance.Indicators Types Defnitions Reduction in vehicle delays R Evaluation index of control performance Te diference between the total delays with and without the signal-vehicle coordinated control under CV-RSU communication Te number of vehicles in the RSU communication domain C Observation index of CV-RSU communication Te average number of vehicles in the RSU communication domain per second Connectivity probability between CV and RSU P c Observation index of CV-RSU communication Te average connectivity probability between CV and RSU Te number of vehicles whose speeds are successfully optimized K Observation index of signal-vehicle coordinated control Te number of CVs whose speeds are successfully optimized and pass through the intersection without stopping during the signal cycle (including the green extension time) Te number of speed adjustments H Observation index of signal-vehicle coordinated control Te number that CVs adjust their speed toward the suggested speed received from RSU Green extension time G ext Observation index of signal-vehicle coordinated control Te total green extension time that the signal controller executes Overlap rate of the communication domains of multiple RSUs Z Observation index of CV-RSU communication Te ratio of the overlapping communication area of multiple RSUs to their total communication area Journal of Advanced Transportation settings are shown in Table
AnalysisScheme Impacts of RSU communication distance on the control performance U1-U5 Impacts of RSU command transmission cycle on the control performance U2, U6-U9 Impacts of single-RSU position on the control performance U2, U10-U12 Impacts of dual-RSU position on the control performance U13-U16 Impacts of RSU number on the control performance U2, U12, and U16

Figure 4 :
Figure 4: Simulation of signal-vehicle coordination control under CV-RSU communication.(a) Te scene with a single-RSU located at the south approach, where the deployment position, communication distance, and command transmission cycle of the RSU are variable.(b) Te scene with two RSUs located at the south approach and north approach, respectively, where the deployment positions of two RSUs are variable.

Figure 5 :Figure 6 :
Figure 5: Impacts of RSU communication distance D rsu on the analysis indicators.

Figure 7 :Figure 8 :
Figure 7: Impacts of the single-RSU position X rsu on the analysis indicators.

Table 3 :
Parameters of RSU deployment schemes.

Table 4 :
RSU deployment scheme for diferent analysis.

Table 5 :
Reduction in vehicle delays under diferent numbers of RSU.

Table 6 :
Te infuence of diferent RSU deployment parameters on the control performance.Te reduction in vehicle delays displays an upward trend and then a downward trend as the RSU communication distance increases T com H and G ext Te reduction in vehicle delays decreases as the RSU command transmission cycle increases 3.3.3.Experiment Summary.In conclusion, Table6shows the infuence of diferent RSU deployment parameters on the control performance.It reveals the impact mechanism of RSU deployment on the control performance.Tis provides theoretical support for the modeling and RSU deployment optimization algorithm under signal-vehicle coordination control.
c , and K

Table 6 :
Continued.Under low trafc fow, the reduction of vehicle delays decreases as the RSU position moves away from the intersection.Under medium trafc and high trafc fows, the reduction in vehicle delays increases as the RSU position moves away from the intersection X rsu of dual-RSU Z, C, and K Te reduction in vehicle delays increases as the RSU position moves away from the intersection