CN115641734A - Mainline Traffic Control Method and System in Expressway Construction Scene - Google Patents

Abstract

The embodiment of the invention discloses a highway construction scene main line traffic control method and a highway construction scene main line traffic control system, wherein the method comprises the following steps: the road end sensor acquires the traffic state of the highway in real time and uploads the traffic state to the cloud control platform; the cloud control platform calculates an optimal speed limit value in a traffic control range in a construction scene in real time according to the traffic state and pre-stored construction event information, wherein the control range comprises a time range and a space range; the cloud control platform generates a traffic control instruction according to the optimal speed limit value and the construction event information, and sends the traffic control instruction to the road side unit in the control range; the road side unit issues corresponding control information to the vehicle closest to the road side unit according to the traffic control instruction; the vehicle displays the control information on a virtual information board in the vehicle. The embodiment uses the virtual information board as a carrier, and carries out accurate and effective control on the construction area of the expressway under the cooperative environment of the vehicle and the road.

Description

Mainline Traffic Control Method and System in Expressway Construction Scene

technical field

Embodiments of the present invention relate to the field of intelligent transportation, and in particular to a method for controlling traffic on a main line in a construction scene of an expressway.

Background technique

Expressway, as a continuous traffic flow facility with high average speed and strong mobility, carries a huge amount of travel and transportation demand. Expressways need to be maintained and repaired. Traffic safety issues and road congestion during maintenance and repairs will have a great adverse effect on the normal operation of expressways.

The existing traffic control strategies in expressway construction areas usually use fixed traffic facilities as the carrier, such as variable information boards set on the gantry, sign boards set on the roadside, etc. Due to expressway construction budgets and road conditions, these transportation facilities often have the characteristics of low layout density, uneven spacing, poor timeliness, and low compliance rate, which cannot fully meet the needs of precise and effective control of smart expressways. At the same time, the traffic control strategies in the prior art usually take the macroscopic traffic parameters of the expressway as the factors affecting the control, and it is difficult to consider the microscopic information of the vehicle and precisely control the vehicle.

Contents of the invention

An embodiment of the present invention provides a method for controlling traffic on a main line of an expressway construction scene, using a virtual information board as a carrier to accurately and effectively control an expressway construction area in a vehicle-road collaborative environment.

In the first aspect, the embodiment of the present invention provides a main line traffic control method for expressway construction scenes, which is applied to the main line traffic control system for expressway construction scenes. The control system includes: roadside sensors, cloud control platforms, roadside units and a vehicle; the method comprising:

The roadside sensor obtains the traffic state of the expressway in real time, and uploads it to the cloud control platform;

The cloud control platform calculates in real time the optimal speed limit value within the traffic control range under the construction scene according to the traffic state and the pre-stored construction event information, wherein the control range includes a time range and a space range;

The cloud control platform generates traffic control instructions according to the optimal speed limit value and the construction event information, and sends them to roadside units within the control range;

The roadside unit issues corresponding control information to the nearest vehicle according to the traffic control instruction;

The vehicle displays the control information on a virtual dashboard in the vehicle.

In the first aspect, an embodiment of the present invention provides a mainline traffic control system for a highway construction scene, including: roadside sensors, a cloud control platform, roadside units, and intelligent networked vehicles;

The roadside sensor is used to obtain the traffic state of the expressway in real time, and uploads to the cloud control platform;

The cloud control platform is used to calculate in real time the optimal speed limit value within the traffic control range under the construction scene according to the traffic state and the pre-stored construction event information, wherein the control range includes a time range and a space range; and Generate a traffic control instruction according to the optimal speed limit value and the construction event information, and send it to the roadside unit within the control range;

The roadside unit is used to issue corresponding control information to the nearest vehicle according to the traffic control instruction;

The vehicle displays the control information on a virtual dashboard in the vehicle.

In the embodiment of the present invention, after a road-occupying construction event occurs on the main line of the expressway, the construction event information of the cloud control platform integrates the traffic state data acquired by the road section sensor, and calculates the space-time range of the expressway that needs to be controlled under the construction scene; The optimal speed limit value generates the optimal control command within the traffic control range; then the control command is sent to the intelligent networked vehicle through the roadside unit, and the control command is communicated for a single vehicle; the vehicle communicates to the driver through the virtual information board Convey control information to guide vehicles upstream of the construction site to slow down and change lanes in advance, to ensure traffic safety and improve the traffic capacity of the expressway construction area. Compared with the traditional control method, the present invention gets rid of the limitation of issuing control commands through fixed variable information boards, and can accurately issue control commands to vehicles within a suitable time and space range, ensuring the safety of expressway construction areas. Improve the efficiency of highway mainline traffic control.

Description of drawings

In order to more clearly illustrate the specific implementation of the present invention or the technical solutions in the prior art, the following will briefly introduce the accompanying drawings that need to be used in the specific implementation or description of the prior art. Obviously, the accompanying drawings in the following description The drawings show some implementations of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative work.

FIG. 1 is a schematic diagram of a mainline traffic control system for a highway construction scene provided by an embodiment of the present invention.

Fig. 2 is a schematic diagram of a main line traffic control method in a highway construction scene provided by an embodiment of the present invention.

Fig. 3 is a schematic diagram of a highway equipment layout provided by an embodiment of the present invention.

Fig. 4 is a flow chart of calculating an optimal speed limit value provided by an embodiment of the present invention.

Fig. 5 is a flow chart of generating a display sign according to a lane change control instruction according to an embodiment of the present invention.

Fig. 6 is a flow chart of generating a display sign according to a lane state control instruction according to an embodiment of the present invention.

Fig. 7 is a flow chart of generating prompt text provided by an embodiment of the present invention.

Fig. 8 is a schematic diagram of various types of virtual information board templates according to the embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" etc. The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, or in a specific orientation. construction and operation, therefore, should not be construed as limiting the invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and should not be construed as indicating or implying relative importance.

In the description of the present invention, it should also be noted that, unless otherwise clearly specified and limited, the terms "installation", "connection" and "connection" should be interpreted in a broad sense, for example, it can be a fixed connection or a flexible connection. Detachable connection, or integral connection; it can be mechanical connection or electrical connection; it can be direct connection or indirect connection through an intermediary, and it can be the internal communication of two components. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present invention in specific situations.

The present application provides a traffic control method for a main line of an expressway construction scene. In order to illustrate the method, the main line traffic control system of the expressway construction scene applying the method is given priority. Fig. 1 is a schematic diagram of a mainline traffic control system in a highway construction scene provided by an embodiment of the present invention. As shown in Fig. 1, the control system includes: roadside sensors, cloud control platform, roadside units and vehicles. Among them, the road section sensor, cloud control platform and roadside unit all come from the intelligent expressway system under the vehicle-road collaborative environment. The vehicle is an intelligent networked vehicle, which needs to have the function of information interaction with the roadside unit.

Based on the control system in FIG. 1 , FIG. 2 is a flow chart of a traffic control method for a main line of an expressway construction scene provided by an embodiment of the present invention. This method is suitable for traffic flow control when there are construction events on the expressway. The method is executed by the control system shown in FIG. 1 , as shown in FIG. 2 , and specifically includes the following steps.

S110, the roadside sensor acquires the traffic status of the expressway in real time, and uploads it to the cloud control platform.

Roadside sensors are used to collect road section traffic flow data and vehicle operation data. In the specific implementation shown in Figure 3, the roadside sensor is a plurality of millimeter-wave radars arranged on the expressway with a distance of 1000 meters, an accurate detection range of 500 meters, and a data collection interval of 30 seconds. The gantry above the cross section can detect the traffic status information of the road sections on both sides of the gantry.

Optionally, the length of the road section is defined as the detection range of the millimeter-wave radar in a certain direction, that is, the length of the road section is 500 meters, and there are 2 road sections between adjacent gantry frames, and the data collection is based on the road section. The traffic state S _i,t of the expressway at a certain collection time on a road section =[Q _i,t ,K _i,t ,V _mean,i,t ,V _std,i,t ], where i represents the road section number and t represents Data collection time, Q represents the average flow of the road section (unit: veh/h/lane), K represents the average density of the road section (unit: veh/km/lane), V _mean represents the average speed of all vehicles on the road section (unit: km/h ), V _std represents the standard deviation of the speed of all vehicles on the road section (unit: km/h).

S120. The cloud control platform calculates in real time an optimal speed limit value within a traffic control range in a construction scene according to the traffic state and pre-stored construction event information, wherein the control range includes a time range and a space range.

The construction event information is pre-published on the cloud control platform by the construction department, including: the start time and end time of the construction, and the road sections and lanes occupied by the construction. Further, the construction event information includes the construction plan start time T _begin , the construction plan end time T _end , and the vertical influence range D _vertical and the horizontal influence range D _horizontal of the construction area. The vertical influence range takes the road section occupied by construction as the basic element, that is, D _vertical = {Section _i ,...,Section _i+k }, which means that the vertical influence range of the construction area includes road section i to road section i+k. The horizontal influence range takes the road sections and lanes occupied by construction as the basic elements, that is, D _horizontal = {Section _i : lane _a , lane _b }, which means that the lateral influence range of the construction area includes lane a and lane b in road section i. In the specific implementation shown in FIG. 3 , the construction event information is D _vertical ={Section ₅ ,Section ₆ ,Section ₇ }, D _horizontal ={Section ₅ :lane ₃ ,Section ₆ :lane ₃ ,Section ₇ :lane ₃ }, T _begin =11:00, T _end =17:00.

Specifically, after the cloud control platform acquires the traffic status and construction event information, it performs the following steps:

Step 1. Determine the time range for traffic control on the construction site according to the start time, end time, and construction preparation time. The traffic control range in the construction scene indicates the effective range of the control method, which is divided into time range and space range. When calculating the time range, it is necessary to consider the lead time T _advance , which is used for pre-construction preparations. The determined time range is T _control =[T _begin −T _advance , T _end ]. In the specific implementation shown in FIG. 3 , T _advance =0.5h, T _control =[T _begin −T _advance , T _end ]=[10:30, 17:00].

Step 2. Dynamically determine the spatial range of traffic control on the construction site according to the road section and lane occupied by the construction, and the traffic flow of at least one road section before the road section occupied by the construction. When calculating the spatial range, it is necessary to set the number of leading road sections in m, and dynamically adjust the spatial range according to the flow change. Optionally, when the 15-minute average flow Q ₁₅ in Section _im ,...,Section _i-2 must be greater than the critical flow, that is, Q _15,im ,...,Q _15,i-2 ≥ Q 15 _,critical , The spatial scope of the traffic control is D _control =[Section _im , . . . , Section _i−2 , Section _i −1, D _vertical ] (m≥1). In the specific implementation shown in Fig. 3, the number of pre-set road sections m is equal to 1, and the ₁₅ -minute average flow Q in the road section Section ₄ is all greater than the key flow, then the spatial scope of traffic control is D _control =[ Sect n ₄ , Section ₅ , Section ₆ , Section ₇ ].

Step 3. Construct the following prediction model to predict the future average vehicle density and average vehicle speed of any road section within the traffic control range:

Among them, i represents the road segment number, k represents the discrete time segment index, and the length of each time segment is T; Q _i,k represents the average traffic flow of road segment i in the time segment [(k-1)T,kT], ρ _i,k represents the average vehicle density of road segment i at time index k, ρ _i,k+1 represents the average vehicle density of road segment i at time index k+1, v _i,k represents road segment i at time index k , v _i,k+1 represents the average speed of road segment i at time index k+1; λ _i represents the number of lanes of road segment i, _Li represents the length of road segment i (km), and q _i,k represents the In the time period [(k-1)T, kT], the average vehicle speed flowing from road section i to road section i+1; τ, κ and υ represent the calibrated model parameters; V _SL,i,k represents the time The speed limit value at index k; Q _max,i+1 represents the maximum flow that road segment i+1 can accommodate, ω _i+1 represents the traffic wave speed of road segment i+1, ρ _jam,i+1 represents road segment i+ The congestion density of 1, θi ₊₁ represents the reduction of road section i+1.

Step 4. Construct the first objective function based on the overall characteristics of the road section:

Among them, i∈D _control represents the road section within the traffic control range; v _{veh_i,x,j} represents the vehicle speed of vehicle veh_i at time j and position x; Std.(v _veh _ _i,x,j ) represents the time segment At index j, the standard deviation of vehicle speed in section _i . From an overall point of view, it is necessary to reduce the speed standard deviation and the number of vehicles in the road section to ensure the safety within the traffic control range in the expressway construction scene, that is, the optimization direction of the first objective function is min J.

Step 5. Construct the second objective function of vehicle individual characteristics:

Among them, v _free,i represents the free flow velocity of road section i, v _{veh_i,x,j} = min{v _{desire,veh_i,x,j} ,V _SL,i,j }, v _{desire,veh_i,x,j} represents the vehicle The expected speed of veh_i at time j and position x, Np is a natural number. For individual vehicles, it is necessary to reduce the delay of each vehicle to improve traffic efficiency and ensure that the construction area passes through the construction area as soon as possible, that is, the optimization direction of the second objective function is min L. Wherein, the calculation method of the speed limit value V _SL,i,k and the desired speed v _{desire,veh_i,x,j} is as follows:

表示路段i的关键密度，distance_{veh_i}表示车辆veh_i距离施工区域起点的距离，α,β为速度参数。in,

Indicates the key density of road section i, distance _{veh_i} indicates the distance between vehicle veh_i and the starting point of the construction area, and α, β are speed parameters.

θ_i、α和β；在无控制条件下，采用顺序二次规划算法，根据实测数据标定预测控制模型参数τ、κ和υ，标定过程需在满足预测值与真实值误差小于设定范围时时收敛。在图3所示的具体实施方式中，各参数表1和表2所示：Under uncontrolled conditions, the attribute parameters Q _max,i , ω _i , ρ _jam,i ,

θ _i , α, and β; under no control conditions, the sequential quadratic programming algorithm is used to calibrate the predictive control model parameters τ, κ, and υ according to the measured data. convergence. In the specific embodiment shown in Fig. 3, each parameter table 1 and table 2 show:

Table 1

Model parameters parameter value Model parameters parameter value T 10s υ 60km2/h lambda 3 Q_max 2000veh/h/lane L 500m ω 11.5km/h τ 18s ρ_jam 180veh/lane/km kappa 40veh/lane/km θ 15%

Table 2

After the prediction model and the objective function are constructed, when the time enters the time range, the cloud control platform performs the following steps, as shown in Figure 4:

Step 1. Initialize the speed limit value of the Nc time segment after the current time segment, and set the speed limit value from the Nc+1 time segment to the Np time segment to be equal to the speed limit value of the Nc time segment, Nc< Np: Substituting the speed limit values of Np time segments after the current time segment into the prediction model to predict the average vehicle density and average vehicle speed of the N _P time segments. After the time t enters the range of T _control , the time is discretized, and the predictive control model is started; according to the real-time acquisition of the traffic state S _i,t and the vehicle state v _{veh_i,x,j} , predict the N _P numbers after the current time index Traffic status during the time period.

Step 2. Calculate the first objective function and the second objective function according to the prediction results; iteratively update the speed limit values of the Np time segments according to the set rules, and return the average vehicle density and average vehicle speed The prediction step until the first objective function and the second objective function satisfy the minimization condition. Optionally, the iterative calculation may use genetic algorithm, ant colony algorithm, random forest, etc., and each algorithm corresponds to different setting rules, which will not be repeated here. In addition, according to the predictive control theory, when the forecast step size is greater than a certain value, the forecast result will tend to be stable, so in the calculation of the optimal speed limit value, set The speed limit value is equal to the speed limit value of the Ncth time segment to reduce the amount of parameters in the iterative calculation.

Step 3: Use the speed limit value that satisfies the minimization condition as the optimal speed limit value for the next time segment of the current time segment. Apply the speed limit value V _SL,i,j output by the model to a time segment after the current index, judge whether the time t exceeds T _control , if so, end the calculation, otherwise return to step 1. In the specific embodiment shown in Fig. 3, N _P =42=7 min, N _C =6=3 min.

S130. The cloud control platform generates traffic control instructions according to the optimal speed limit value and the construction event information, and sends them to roadside units within the control range.

The traffic control instruction includes at least one of a speed limit control instruction, a lane change control instruction, a lane state control instruction and a text prompt instruction. In the specific implementation shown in FIG. 3 , the layout interval of the roadside units is 250 meters, and the calculation and sending frequency of control commands Δt=30s. According to the type of traffic control instruction, several optional implementation modes are as follows in this embodiment:

In the first optional implementation manner, according to the speed limit value of each road section within the traffic control range, a speed limit control instruction for each road section is generated and sent to the roadside unit of each road section. Specifically, firstly, after time t enters the range of T _conol , the optimal speed limit value of Np time segments after the current time for any section is calculated in real time, and a time segment after the current time is generated according to the optimal speed limit value The speed limit control instruction (the specific process is shown in Figure 4), and is issued to the roadside unit of each road section in the said one time segment.

In a second optional implementation manner, for the remaining road sections other than the road section occupied by the construction, a lane change control instruction is generated according to the lane occupied by the construction. Specifically, for a section within the traffic control area but outside the vertical influence range of the construction area, that is, Section _i ∈ (D _control \D _vertical ), extract the corresponding lane number of the road section in the horizontal influence range D _horizontal , according to the lane Numbering calculates the display signs of each lane in the road section to form a lane change control command. Taking the specific implementation manner in FIG. 3 as an example, the lateral influence range of the construction area D _horizontal ={Section ₅ :lane ₃ , Section ₆ :lane ₃ ,Section ₇ :lane ₃ }. For the road section within the traffic control area but outside the vertical influence range of the construction area, namely Section _i ∈ (D _control \D _vertical ), extract the lane number corresponding to Section _i in D _horizontal , and calculate each lane in the road section according to the number The displayed signs form the lane change control command.

则该车道显示白色左指示箭头；否则，判断车道lane_i右侧是否存在车道lane_i,right，若存在且

则该车道显示白色右指示箭头；否则，该车道显示黄色警告标志。若

则该车道显示白色前向箭头。当前车道判断完毕后，转至下一车道重复以上操作，如图5所示。Optionally, if any lane in the rest of the road section occupied by the construction is a lane occupied by construction, determine whether there are lanes on both sides of the lane; if there is a lane on either side and it is not a lane occupied by construction, A lane change command is generated to change lanes to the one side lane. In addition, a display sign for each lane may also be generated, and the display sign is used to display the lane change instruction. Specifically, for each lane lane _i of the road cross-section of the section, it is judged whether the lane matches the construction occupied lane. If lane _i ∈ D _horizontal , judge whether there is lane _{i ,left} on the left side of lane i, if it exists and

Then the lane displays a white left arrow; otherwise, judge whether there is lane _{i ,right} on the right side of lane i, if it exists and

Then the lane displays a white right pointing arrow; otherwise, the lane displays a yellow warning sign. like

Then the lane displays a white forward arrow. After the current lane is judged, go to the next lane and repeat the above operations, as shown in Figure 5.

Taking the specific implementation manner in Fig. 3 as an example, for each lane lane _i of the road cross-section of the road section, it is judged whether the lane matches the construction occupied lane. If lane _i = lane ₃ , judge whether there is lane _{i ,left} on the left side of lane i, if it exists and lane _i,left ≠ lane ₃ , then the lane will display a white left arrow and turn to the next lane; otherwise , to determine whether lane _{i ,right} exists on the right side of lane i, if there is lane _i,right ≠ lane ₃ , then the lane displays a white right arrow; otherwise, the lane displays a yellow warning sign. If lane _i ≠lane ₃ , the lane displays a white forward arrow. After the current lane is judged, go to the next lane and repeat the above operation.

In a third optional implementation manner, for the road section occupied by the construction, a lane state control command is generated according to the lane occupied by the construction. Specifically, for the road section within the traffic control area and within the vertical influence range of the construction area, that is, Section _i ∈ D _vertical , according to the lateral influence range D _horizontal of the construction area, a display sign for each lane in the road section is generated to display the lane State control instructions. Including the following operations: For each lane _i of the road cross-section of the road section, judge whether the lane matches the construction lane. If lane _i ∈ D _horizontal , the lane will display a red cross, otherwise the lane will display a white forward arrow, such as Figure 6 shows.

Taking the specific implementation manner in FIG. 3 as an example, the lateral influence range of the construction area D _horizontal ={Section ₅ :lane ₃ , Section ₆ :lane ₃ ,Section ₇ :lane ₃ }. For the road section within the traffic control area and within the longitudinal influence range of the construction area, that is, Section _i ∈ {Section ₅ , Section ₆ , Section ₇ }, according to the lateral influence range D _horizontal of the construction area, the display signs of each lane in the road section are generated . For each lane lane _i of the road cross-section of the section, judge whether the lane matches the construction lane. If lane _i = lane ₃ , the lane will display a red cross, otherwise the lane will display a white forward arrow.

In the fourth embodiment, for the road sections within the control range, a text prompt instruction is generated for prompting the distance of the construction area ahead and prompting the vehicle to slow down. Specifically, for the road section within the traffic control area but outside the vertical influence range of the construction area, that is, Section _i ∈ (D _control \D _vertical ), output the text message "the road is occupied by construction at x kilometers ahead, please slow down", Where x (km) represents the distance between the vehicle and the starting point of D _vertical . For the road section within the traffic control area and within the vertical influence range of the construction area, namely Section _i ∈ D _vertical , output the text message “Construction area, slow down”, as shown in Figure 7.

Taking the specific implementation in Figure 3 as an example, for the road section within the traffic control area but outside the vertical influence range of the construction area, that is, Section _i ∈ (D _control \D _vertical ), output "construction at x kilometers ahead, please Slow down" text message, where x (km) represents the distance between the vehicle and the starting point of Section ₅ . For the road section within the traffic control area and within the longitudinal influence range of the construction area, that is, Section _i ∈ {Section ₅ , Section ₆ , Section ₇ }, output the text information of "construction area, slow down".

It should be noted that, according to the types of traffic control instructions, the above four optional implementation manners may exist independently or in combination, and all of them belong to the protection scope of this embodiment.

S140. The roadside unit issues corresponding control information to the nearest vehicle according to the traffic control instruction. The range of control information sent by the roadside unit to the ICV needs to satisfy T _control in time and D _control in space, and the sending frequency is Δτ.

S150. The vehicle displays the control information on a virtual information board in the vehicle.

Based on the control information, the intelligent networked vehicle terminal calculates the information that needs to be filled in the corresponding virtual information board display template, and displays the complete virtual information board in the intelligent networked vehicle. Optionally, as shown in Figure 8, the speed limit virtual information board template includes a display panel to display the current vehicle speed limit value, the value of the speed limit value is a multiple of 5, the maximum value is 120km/h, and the minimum value is 20km/h; the lane state virtual information board template needs to contain λ _{veh_i,x} block boards, λ _{veh_i,x} represents the number of lanes of the intelligent networked vehicle veh_i at the road stake x (λ _vehi,x = 3 in Figure 8 , corresponding to the specific embodiment of Fig. 3), each segmented board corresponds to the opening or closing state of the lane in order, the opening state is represented by a white forward arrow, and the closed state is represented by a red cross; the virtual information board template for prompting lane change To include λ _{veh_i,x} segmented boards, each segmented board corresponds to the lane change prompts of the lanes in sequence. The segmented boards can display 4 types of graphics, which are white left indicator arrow, white right indicator arrow, white forward arrow and A yellow warning sign means changing lanes to the left, changing lanes to the right, going straight without changing lanes, and warnings of construction ahead; the text information virtual information board template includes a display panel to display text information.

Specifically, according to the control information, the vehicle calculates the information that needs to be filled in the corresponding virtual information board display template, and displays the complete virtual information board in the intelligent connected vehicle, specifically including: filling the speed limit value, vehicle veh_i at time t, When the position is at x, fill in the speed limit value V _SL,i,t , where x∈Section _i ; fill in the lane change information, if the control information sent by the roadside unit is received, fill in according to the control information, otherwise the lane change information will not be displayed ; Fill in the lane state information, if the control information sent by the roadside unit is received, it will be filled according to the control information, otherwise the lane state information will not be displayed; fill in the text information, if the control information sent by the roadside unit is received, it will be filled according to the control information , otherwise no text information will be displayed.

It should be noted that S120-S150 are all performed within the time range of the traffic control at the current time. If the current time has not entered the time range, or has exceeded the time range, the execution of S120-S150 is stopped.

In this embodiment, when a road-occupying construction event occurs on the main line of the expressway, the construction event information on the cloud control platform integrates the traffic state data obtained by the road section sensors, calculates the space-time range of the expressway that needs to be controlled under the construction scene, and predicts the situation through the model The control method, with the goal of optimizing the safety of the traffic system and the minimum vehicle delay, performs double-layer planning to generate the optimal control command within the traffic control range; then the control command is sent to the intelligent networked vehicle through the roadside unit, for a single The vehicle communicates control commands; the vehicle communicates control information to the driver through the virtual information board, thereby guiding vehicles coming from the upstream of the construction site to slow down and change lanes in advance, ensuring traffic safety and improving the traffic capacity of the expressway construction area. Compared with the traditional control method, the present invention gets rid of the limitation of issuing control commands through fixed variable information boards, and can accurately issue control commands to vehicles within a suitable time and space range, ensuring the safety of expressway construction areas. Improve the efficiency of highway mainline traffic control.

The embodiment of the present invention also provides a traffic control system for the main line of an expressway construction scene. As shown in FIG. 1 , the control system includes: roadside sensors, a cloud control platform, roadside units, and intelligent networked vehicles. The roadside sensor is used to obtain the traffic state of the expressway in real time and upload it to the cloud control platform; the cloud control platform is used to calculate the traffic conditions under the construction scene in real time according to the traffic state and pre-stored construction event information. The optimal speed limit value within the control range, wherein the control range includes time range and space range; and according to the optimal speed limit value and the construction event information, a traffic control instruction is generated and issued to the A roadside unit within the control range; the roadside unit is used to issue corresponding control information to the nearest vehicle according to the traffic control instruction; the vehicle displays the control information on a virtual information board inside the vehicle.

Optionally, the traffic control instruction includes a lane change control instruction and/or a lane state control instruction; the virtual information board includes a display panel and/or a plurality of partition panels; the display panel is used for maximum speed limit and/or Prompt text; each segment board corresponds to a lane, and is used to display the lane change control instruction and/or lane state control instruction of the lane.

The control system provided in this embodiment is used to implement the control method described in any of the above embodiments, and has corresponding technical effects.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention.

Claims (10)

1. A highway construction scene main line traffic control method is applied to a highway construction scene main line traffic control system, and is characterized in that the control system comprises: the system comprises a road end sensor, a cloud control platform, a road side unit and a vehicle;

the method comprises the following steps:

the road end sensor acquires the traffic state of the highway in real time and uploads the traffic state to the cloud control platform;

the cloud control platform calculates an optimal speed limit value in a traffic control range under a construction scene in real time according to the traffic state and pre-stored construction event information, wherein the control range comprises a time range and a space range;

the cloud control platform generates a traffic control instruction according to the optimal speed limit value and the construction event information, and sends the traffic control instruction to the road side unit in the control range;

the road side unit issues corresponding control information to the vehicle closest to the road side unit according to the traffic control instruction;

and the vehicle displays the control information on a virtual information board in the vehicle.

2. The method of claim 1, wherein the construction event information comprises: the starting time and the ending time of construction, and road sections and lanes occupied by the construction;

the method for predicting the speed limit value in the traffic control range in the construction scene in real time according to the traffic state and the pre-stored construction event information comprises the following steps:

determining the time range of traffic control of a construction site according to the starting time, the ending time and the construction preparation time;

and dynamically determining the space range of traffic control of a construction site according to the road section and the lane occupied by the construction and the traffic flow of at least one road section in front of the road section occupied by the construction.

3. The method of claim 1, wherein the traffic state comprises: the average traffic flow and the average vehicle density of each road section in the expressway, and the average vehicle speed and the standard deviation of the vehicle speed of all vehicles;

before the cloud control platform calculates the optimal speed limit value in the traffic control range in the construction scene in real time according to the traffic state and the pre-stored construction event information, the method further comprises the following steps:

the following prediction models are constructed for predicting the future average vehicle density and the future average vehicle speed of any road section in the traffic control range:

wherein i represents a link number, k represents a discrete time segment index, and the length of each time segment is T; q _i,k Representing the section i in the time period [ (k-1) T, kT]Mean traffic flow in p _i,k Representing the average vehicle density, ρ, of the section i at the time index k _i,k+1 Representing the average vehicle density, v, of the section i at the time index k +1 _i,k Indicating a road segment i at a time index kV average vehicle speed of _i,k+1 Represents the average vehicle speed of the link i at the time index k + 1; lambda [ alpha ] _i Indicating the number of lanes, L, of the section i _i Indicating the length (km), q of the section i _i,k Expressed in a time period [ (k-1) T, kT]Average speed of the vehicle flowing from the section i to the section i + 1; tau, k and upsilon represent calibrated model parameters; v _SL,i,k Representing the speed limit value of the road section i at the time index k; q _max,i+1 Represents the maximum flow, ω, that the section i +1 can accommodate _i+1 Representing the speed of the traffic wave, ρ, for the section i +1 _jam,i+1 Represents the congestion density, θ, of the road segment i +1 _i+1 Represents the reduction amount of the link i + 1;

constructing a first objective function based on the overall characteristics of the road section:

wherein ,i∈D_control Representing road segments located within a traffic control range; v. of _{veh_i,x,j} Represents the vehicle speed of the vehicle veh _ i at time j, position x; (v.) Std _{veh_i,x,j} ) Indicates at section, at time segment index j _i The standard deviation of the vehicle speed;

constructing a second objective function of the individual characteristics of the vehicle:

wherein ,v_free,i Representing the speed of the free flow, v, of the section i _{veh_i,x,j} ＝min{v _{desire,veh_i,x,j} ,V _SL,i,j }，v _{desire,veh_i,x,j} Representing the desired speed of the vehicle veh _ i at time j, position x, np being a natural number.

4. A method according to claim 3, characterized in that the speed limit value V _SL,i,k And a desired velocity v _{desire,veh_i,x,j} The calculation of (c) is as follows:

wherein ,

representing the critical density, distance, of a section i _{veh_i} And the distance between the veh _ i of the vehicle and the starting point of the construction area is shown, and alpha and beta are speed parameters.

5. The method according to claim 4, wherein before constructing the prediction model of the average vehicle density and the average vehicle speed in the future of any road section in the traffic control range under the construction scene, the method further comprises the following steps:

calibrating attribute parameter Q of road section i through measured data under the condition of no control _max,i 、ω _i 、ρ _jam,i 、ρ _Ci 、θ _i、α and β；

under the condition of no control, a sequential quadratic programming algorithm is adopted, parameters tau, kappa and upsilon of the predictive control model are calibrated according to measured data, and the calibration process needs to be converged when the error between the predicted value and the true value is smaller than a set range.

6. The method of claim 3, wherein the construction event information comprises: the starting time and the ending time of construction, and road sections and lanes occupied by the construction;

the method for calculating the optimal speed limit value in the traffic control range in the construction scene in real time according to the traffic state and the pre-stored construction event information comprises the following steps:

initializing N after the current time segment in case the current time belongs to the time range _c Setting the speed limit value of each time slice _c +1 time slice to Nth _p The speed limit value of each time slice is equal to Nth _c The limit values of the time segments are equal, N _c <N _p ；

N after the current time slice _p Substituting the speed limit value of each time segment into the prediction model to predict the N _P Average vehicle density and average vehicle speed for each time slice;

calculating the first objective function and the second objective function according to the prediction result;

iteratively updating the N according to a set rule _p Returning the forecasting steps of the average vehicle density and the average vehicle speed to the speed limit values of the time segments until the first objective function and the second objective function meet the minimization condition;

and taking the speed limit value meeting the minimization condition as the optimal speed limit value of the next time segment of the current time segment.

7. The method of claim 1, wherein the construction event information comprises: the starting time and the ending time of construction, and road sections and lanes occupied by the construction; the traffic control instruction comprises at least one of a speed limit control instruction, a lane change control instruction, a lane state control instruction and a text prompt instruction;

the generating a traffic control instruction according to the optimal speed limit value and the construction event information, and issuing the traffic control instruction to the road side unit comprises:

generating a speed limit control instruction of each road section according to the speed limit value of each road section in the traffic control range;

generating lane change control instructions for other road sections except the road section occupied by the construction according to the lanes occupied by the construction;

generating a lane state control instruction for the road section occupied by the construction according to the lane occupied by the construction;

and generating a text prompt instruction for the road sections in the control range, wherein the text prompt instruction is used for informing the distance of the construction area in front and prompting the vehicle to slow down.

8. The method of claim 7, wherein the generating lane change control instructions for the remaining road segments other than the road segment occupied by the construction according to the lane occupied by the construction comprises:

if any lane in the rest of road sections except the road section occupied by the construction is the lane occupied by the construction, judging whether lanes exist on two sides of the lane or not;

and if the lane exists on any side and is not the lane occupied by construction, generating a lane change instruction for changing the lane to the lane on one side.

9. A highway construction scene mainline traffic control system is characterized by comprising: the system comprises a road end sensor, a cloud control platform, a road side unit and an intelligent networking vehicle;

the road end sensor is used for acquiring the traffic state of the highway in real time and uploading the traffic state to the cloud control platform;

the cloud control platform is used for calculating an optimal speed limit value in a traffic control range in a construction scene in real time according to the traffic state and pre-stored construction event information, wherein the control range comprises a time range and a space range; generating a traffic control instruction according to the optimal speed limit value and the construction event information, and sending the traffic control instruction to a road side unit in the control range;

the road side unit is used for issuing corresponding control information to the vehicle closest to the road side unit according to the traffic control instruction;

and the vehicle displays the control information on a virtual information board in the vehicle.

10. The system of claim 9, wherein the traffic control instructions comprise lane change control instructions and/or lane state control instructions;

the virtual information board comprises a display panel and/or a plurality of partition boards; the display panel is used for limiting the speed to the maximum and/or prompting characters; each partitioning plate corresponds to one lane and is used for displaying lane change control instructions and/or lane state control instructions of the lanes.

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