A method, system and storage medium for dynamic speed limit control of highways based on intelligent passenger and freight connected vehicle barriers

Abstract

The present invention discloses a method, system and storage medium for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers, including the following steps: activating a row distribution control area section and a dynamic speed limit control area section when a bottleneck section occurs; grouping CAV passenger and freight vehicles in pairs; making two CAV passenger and freight vehicles that meet the conditions form a row parallel state in the row distribution control area section, and keep driving side by side at the same speed to enter the dynamic speed limit control area section; and controlling the CAV passenger and freight vehicles driving side by side at the same speed in the dynamic speed limit control area section. Facing the upcoming mixed flow scenario, considering the differences in physical characteristics, driving characteristics and barrier effects of passenger and freight vehicles, fully utilizing the networked communication and automatic driving functions of intelligent networked vehicles to control the driving behavior of passenger and freight intelligent networked vehicles, guiding the subsequent following manual vehicles to passively decelerate in advance, strengthening the mobile barrier effect, and improving the control effect of the dynamic deceleration strategy.

Description

Technical Field

[0001] The present invention relates to the field of intelligent traffic management and control technology, and in particular to a method, system and storage medium for dynamic speed limit control of expressways based on a passenger and freight intelligent networked vehicle barrier. Background Art

[0002] In order to deal with the collision threat caused by the deceleration wave propagating in the bottleneck area, the industry has developed a series of intelligent traffic system control technologies, such as ramp control (RM), path guidance (RG) and variable speed limit control (VSL). Among them, the core concept of variable speed limit control technology is to dynamically adjust and control the vehicle speed limit value in a specific section or area of ​​the highway, and display this information in real time through the variable speed limit board, so as to achieve fine optimization management of traffic flow.

[0003] At present, with the development of intelligent network technology, the popularization and application of intelligent network vehicles (CAV) has become a general trend in the field of smart transportation. Intelligent network vehicles are equipped with various advanced sensors and integrate high-tech technologies such as network connection and communication. They can interact with multiple factors such as vehicles and roads in real time. Their heterogeneous characteristics undoubtedly provide new and potential solutions for improving traffic safety and efficiency. Therefore, for the mixed traffic flow composed of intelligent network vehicles and manually driven vehicles in the future, the intelligent network vehicles can be used as mobile barriers to potentially guide manually driven vehicles by controlling the driving trajectory of a single intelligent network vehicle (particle), thereby controlling the overall traffic flow to operate more safely and efficiently, and realizing the coordinated control of flow and particles.

[0004] However, most of the current research is mainly aimed at the ideal traffic environment of full intelligent networking under the condition of high penetration rate of intelligent connected vehicles, and only considers one type of conventional passenger car, ignoring the impact caused by differences in passenger and freight vehicle models, driving characteristics and barrier effects. How to give full play to the low latency, high compliance and other characteristics of intelligent connected vehicles and the differences between passenger and freight vehicles, so that variable speed limits can establish a more effective mobile barrier and further improve its safety is the focus of the present invention.

[0005] The patent application number is CN202110390114.1, a dynamic speed limit control method, system, terminal and readable storage medium based on intelligent networked vehicles. It mainly discloses the technical means of establishing a neural network model to realize dynamic adjustment of vehicle speed on the highway, thereby reducing accident risks and improving traffic safety. It does not disclose reasonable control based on the driving information of intelligent networked vehicles when bottleneck sections appear. In view of this, it is necessary to provide a dynamic speed limit control method for highways based on passenger and freight intelligent networked vehicle barriers to solve or at least partially alleviate the above technical problems. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a method for dynamic speed limit control on highways based on a passenger and freight intelligent networked vehicle barrier, aiming to solve the technical problem that the existing technology does not fully utilize passenger and freight intelligent networked vehicles to carry out traffic control when bottleneck sections appear on highways.

[0007] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0008] A method for dynamic speed limit control of highways based on a passenger and freight intelligent networked vehicle barrier, comprising the steps of:

[0009] S10, obtaining a traffic flow operation state of a highway section, and determining that the highway section is a bottleneck section if the traffic flow operation state is a congested state, wherein the traffic flow of the highway section is a mixed traffic flow consisting of intelligent networked vehicles and manually driven vehicles;

[0010] S20, activating the upstream road section of the bottleneck section is the row distribution control area section A1 and the dynamic speed limit control area section A2, wherein the row distribution control area section A1, the dynamic speed limit control area section A2 and the bottleneck section are adjacently arranged and the dynamic speed limit control area section A2 is between the bottleneck section and the row distribution control area section A1;

[0011] S30, based on the current vehicle driving information in the row distribution control area segment A1, the CAV passenger and freight vehicles in the row distribution control area segment A1 are grouped according to preset conditions, so that every two CAV passenger and freight vehicles form a target control vehicle group;

[0012] S40, regulating the CAV passenger and cargo vehicles in the same target regulated vehicle group so that two CAV passenger and cargo vehicles in the same target regulated vehicle group that meet the staggered distribution condition are in different driving lanes;

[0013] S51, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are in a row and parallel state at the current moment, if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are in a row and parallel state at the current moment, then proceeding to step S60, if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are not in a row and parallel state at the current moment, then proceeding to step S52;

[0014] Wherein, if the longitudinal distance between the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes is not greater than the preset row threshold, it is determined that the two CAV passenger and cargo vehicles of the same target regulated vehicle group are in a row parallel state;

[0015] S52, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes meet the condition of parallel driving in a row before reaching the end of the row distribution control area section A1; if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes meet the condition of parallel driving in a row before reaching the end of the row distribution control area section A1, then entering step S53,

[0016] S53, performing control so that two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes form a row and parallel state before reaching the end of the row distribution control area section A1;

[0017] S60, making the two CAV passenger and cargo vehicles in the row parallel state keep traveling side by side at the same speed to form a row parallel state with the same speed, and enter the dynamic speed limit control area section A2;

[0018] S70, deceleration control is performed on the CAV passenger and freight vehicles corresponding to the target regulated vehicle group that are traveling in a row and at the same speed in parallel within the dynamic speed limit control area section A2; deceleration control is performed on the single-row CAV passenger and freight vehicles that enter the dynamic speed limit control area section A2.

[0019] Furthermore, step S30 specifically includes:

[0020] S31, obtaining the current vehicle driving information in the row distribution control area segment A1, the current vehicle driving information including the vehicle position information, vehicle lane information, vehicle attribute information, vehicle speed information, vehicle acceleration information and vehicle longitudinal distance information of the CAV passenger and freight vehicles, and constructing the CAV vehicle arrangement sequence database of the row distribution control area segment A1 by sorting the vehicles in a front-to-back order according to the vehicle driving direction;

[0021] S32, obtaining a leading CAV passenger and freight vehicle and a second CAV passenger and freight vehicle adjacent to the leading CAV passenger and freight vehicle in a CAV vehicle arrangement sequence database;

[0022] S33, determining whether the distance between the second CAV passenger and cargo vehicle and the leading CAV passenger and cargo vehicle is within a preset distance range, if the distance between the second CAV passenger and cargo vehicle and the leading CAV passenger and cargo vehicle is within the preset distance range, proceeding to step S34, if the distance between the second CAV passenger and cargo vehicle and the leading CAV passenger and cargo vehicle is not within the preset distance range, proceeding to step S35;

[0023] S34, determining that the CAV passenger and cargo vehicle at the next position and the CAV passenger and cargo vehicle at the leading position are a group of target control vehicles, removing the CAV passenger and cargo vehicle at the leading position and the CAV passenger and cargo vehicle at the next position from the current CAV vehicle arrangement sequence database to obtain a remaining arrangement database, and updating the remaining arrangement database to the CAV vehicle arrangement sequence database and entering step S32,

[0024] S35, remove the head CAV passenger and freight vehicle from the current CAV vehicle arrangement sequence database to obtain the remaining arrangement database, and update the remaining arrangement database to the CAV vehicle arrangement sequence database and enter step S32,

[0025] Repeat steps S32 to S35 to group all CAV passenger and freight vehicles in the CAV vehicle arrangement sequence database, and obtain all target control vehicle groups of CAV passenger and freight vehicles in the row distribution control area segment A1.

[0026] Furthermore, the CAV passenger and freight vehicle is a CAV bus or a CAV truck, the target regulated vehicle group is a combination of a CAV bus and a CAV bus, or the target regulated vehicle group is a combination of a CAV bus and a CAV truck, or the target regulated vehicle group is a combination of a CAV truck and a CAV truck.

[0027] Furthermore, the current vehicle driving information includes vehicle lane information, vehicle attribute information, and vehicle longitudinal distance information of the CAV passenger and freight vehicle. Step S40 specifically includes:

[0028] S41, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group are in different lanes, if the two CAV passenger and cargo vehicles of the same target control vehicle group are in different lanes, proceeding to step S42; if the two CAV passenger and cargo vehicles of the same target control vehicle group are in the same lane, proceeding to step S50;

[0029] S42, regulating the CAV passenger and freight vehicles in the same target control vehicle group so that two CAV passenger and freight vehicles in the same target control vehicle group that meet the lane-shifting distribution condition are in different driving lanes.

[0030] Among them, the formula as well as Determine whether a single vehicle in the vehicle group meets the safe lane change conditions. If a single vehicle meets the safe lane change conditions, determine whether the two CAV passenger and freight vehicles in the vehicle group meet the lane-changing distribution conditions. The vehicle position of any vehicle of the two CAV passenger and cargo vehicles in the target control vehicle group, The position of the vehicle behind the vehicle in the lane to be cut into. The position of the vehicle ahead of the vehicle in the lane to be cut into. is the preset safe lane change distance. ,and , then it is determined that the error distribution condition is met.

[0031] Furthermore, in step S42, “controlling the CAV passenger and cargo vehicles of the same target control vehicle group so that two CAV passenger and cargo vehicles of the same target control vehicle group that meet the lane-shifting distribution condition are in different driving lanes” specifically includes:

[0032] If only one of the CAV passenger and cargo vehicles in the target control vehicle group meets the lane-changing distribution conditions, the CAV passenger and cargo vehicle that meets the safe lane-changing conditions is controlled to change lanes;

[0033] If both CAV passenger and freight vehicles in the target controlled vehicle group meet the lane-shifting distribution conditions, the vehicle types of the two CAV passenger and freight vehicles in the target controlled vehicle group are obtained; if the two vehicles are of different types, given that trucks are large in size and heavy in weight, their acceleration, deceleration and steering performance are not as flexible as buses, and more space and time are required for lane changing. In addition, trucks have large inertia, which increases the risk of lane changing and may cause greater interference to the surrounding traffic flow. In comparison, buses are more direct and quick in lane changing, so the CAV vehicle of bus type is controlled to change lanes; if the two vehicles are of the same type, the CAV vehicle in front is controlled to perform lane changing based on their front and rear positions in the queue.

[0034] Further, in step S52, assuming that the current time is t, the time when the leading vehicle A and the trailing vehicle B of the same target control vehicle group travel to the row distribution state is , is the deceleration of the preceding vehicle A, is the minimum speed limit, for The distance between the preceding vehicle A and the starting point of the row distribution area at time, for The distance between the rear vehicle B and the starting point of the row distribution area at time, are the speeds of the front vehicle A and the rear vehicle B at time t, are the distances from the front vehicle A to the starting point of the row distribution area and the distances from the rear vehicle B to the starting point of the row distribution area at time t, for The speed of the preceding vehicle A at time t, is the time required for vehicle group i to form a row, using the formula

[0035]

[0036] Get The distance between the front vehicle A and the starting point of the row distribution area and the distance between the rear vehicle B and the starting point of the row distribution area at the moment;

[0037] make (Assuming that the state is in parallel and within the cutoff line), solving the equation with equal signs on both sides yields The value of The length of the row distribution control area section A1;

[0038] right The value of is tested, if it satisfies the constraint formula , it is judged that the front vehicle A and the rear vehicle B meet the parallel row condition, indicating that before the front vehicle A reaches the end of the vehicle row area, the vehicle distance between vehicles A and B meets the row requirement. for The current real-time distance between the front vehicle A and the rear vehicle B at the moment, To determine the spacing in a preset row;

[0039] Among them, the traversal search method is used for solution and verification, and the deceleration is set The initial deceleration value is 0.5m / s 2 ,Will Substitute the equations in ascending order from 1s and increment by whole seconds, and calculate and , and determine whether the row constraint is met; if the constraint formula is met , then the current The value is a feasible solution and the search stops; if the constraint formula is not satisfied , then 0.1m / s 2 Gradually increase the deceleration by units , and re-solve the equation to calculate the feasible solution. The upper limit is 2m / s 2 ;

[0040] If the constraint formula is still not satisfied after traversal , it is judged that the two CAV passenger and freight vehicles of the same target control vehicle group on different lanes do not meet the row parallel driving condition before reaching the end of the row distribution control area section A1 (row distribution end line D).

[0041] Furthermore, if the constraint formula is satisfied , then get The feasible solution of the target control vehicle group is the calculated vehicle platooning time t+ , row speed and , row acceleration And row position and ,

[0042] The vehicle platooning time t+ of two CAV passenger and freight vehicles in the target control vehicle group , row speed and , row acceleration And row position and The speed of the corresponding CAV passenger and freight vehicles in the group is controlled.

[0043] Furthermore, in step S70, the actual deceleration of the CAV passenger and freight vehicles traveling in a row in the dynamic speed limit control area A2 is determined. , control the two CAV passenger and cargo vehicles in the target control vehicle group that have been traveling in a row to have the same actual deceleration Driving;

[0044] Determine the actual deceleration of CAV passenger and freight vehicles not traveling in a row in the dynamic speed limit control area segment A2 , control the CAV passenger and cargo vehicle to the actual vehicle deceleration Driving;

[0045] Form a CAV moving barrier to guide the following HVs to passively decelerate in advance before reaching the bottleneck area;

[0046] The dynamic speed limit model formula is as follows:

[0047]

[0048] In the formula, is the vehicle deceleration calculated according to the dynamic speed limit formula, are the vehicle speed and vehicle position of the vehicle, , ,..., is the speed of all CAV vehicles in front of the vehicle within the wireless communication range, , ,..., The positions of all CAV vehicles in front of the vehicle within the wireless communication range;

[0049] Among them, the actual dynamic speed limit model formula is as follows:

[0050]

[0051] In the formula, is the gap error of vehicle i at the current time k, , , , are the speed and position of vehicle i and vehicle i-1 at the current time k, is the driver of the preceding vehicle A, =1.1 is the expected workshop time interval, =0.04, =0.8, and To control the gain parameter, is the actual deceleration of CAV vehicles not traveling in a platoon, is the actual deceleration of CAV vehicles traveling in a row, is the vehicle deceleration calculated according to the car-following model, is the maximum deceleration of the vehicle, is the vehicle deceleration calculated according to the dynamic speed limit formula, are the vehicle decelerations calculated by the following model for the front vehicle A and the rear vehicle B in the vehicle group, are the vehicle decelerations calculated by the dynamic speed limit formula for the front vehicle A and the rear vehicle B in the vehicle group, is the maximum acceleration change of the passenger and cargo CAV in adjacent time steps, where =2, CAV bus =3.

[0052] The present invention also provides a highway dynamic speed limit control system based on a passenger and freight intelligent networked vehicle barrier.

[0053] The data acquisition module is used to holographically perceive the driving environment of the road section, and use roadside sensing equipment and intelligent connected vehicle sensing equipment to obtain real-time information on vehicle movement and traffic flow operation status on the highway section;

[0054] The monitoring module monitors in real time whether a traffic bottleneck occurs on the road section based on the information obtained about vehicle movement and traffic flow operation status;

[0055] The computing module is used for searching strategies for lane changing and speed control solutions for passenger and freight CAVs. The roadside sensing equipment and CAV sensing equipment upload the collected and processed vehicle movement and traffic flow information in the row distribution control area A1 and the dynamic speed limit control area A2 to the cloud, and the cloud computing obtains the control solution.

[0056] The control module is used to send and execute the platoon distribution strategy and dynamic speed limit instructions of passenger and freight intelligent connected vehicles (CAVs). The cloud will feed back the control plan to the corresponding intelligent connected vehicle (CAV), and the intelligent connected vehicle (CAV) will receive the command to change lanes or control speed.

[0057] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program is used to be programmed or configured by a microprocessor to execute the steps of the above-mentioned method for dynamic speed limit control of highways based on intelligent connected passenger and freight vehicle barriers.

[0058] Compared with the prior art, the advantages of the present invention are:

[0059] Aiming at the upcoming mixed flow scenarios, the present invention is based on the intelligent transportation Internet of Things application service technology, adopts the Beidou positioning system to obtain vehicle position, takes into account the differences in physical properties, driving characteristics and barrier effects of passenger and freight vehicles, and makes full use of the networked communication and automatic driving functions of intelligent connected vehicles (CAV), and provides a dynamic speed limit control method for highways based on passenger and freight intelligent connected vehicle barriers. At the same time, when a bottleneck section appears in the road conditions, the two CAV passenger and freight vehicles are combined to form a group of target control vehicles. The target control vehicle group is controlled to form a row and parallel driving state in the row distribution control area section A1. The target control vehicle group in the row and parallel driving state is controlled to slow down and drive side by side in the dynamic speed limit control area section A2. The row distribution strategy is introduced to adjust the distribution of passenger and freight intelligent networked vehicles (CAV) in the mixed traffic flow, strengthen the mobile barrier effect, and improve the control effect of the dynamic deceleration strategy. Then, on the basis of optimizing the distribution pattern, the driving behavior of the passenger and freight intelligent networked vehicles (CAV) is further controlled to guide the subsequent following manual vehicles (HV) to achieve early passive deceleration, reduce the impact of the deceleration wave, reduce the collision risk near the bottleneck area and the probability of traffic accidents on the highway, and realize flow-particle coordinated control. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a detailed flow chart of the method for dynamic speed limit control of expressways based on intelligent passenger and freight connected vehicle barriers of the present invention;

[0061] Figure 2 It is a schematic diagram of the vehicle grouping process in the method for dynamic speed limit control of expressways based on passenger and freight intelligent networked vehicle barriers of the present invention;

[0062] Figure 3 is a schematic diagram of driving status, where a is the schematic diagram when triggered, and b is the schematic diagram of segmented control after triggering;

[0063] Figure 4 It is a schematic diagram of the driving status of the row distribution area control of the passenger and cargo intelligent networked vehicles of the present invention. DETAILED DESCRIPTION

[0064] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0067] Please refer to Figure 1 , Figure 2 , Figure 3 as well as Figure 4 According to an embodiment of the present invention, a method for dynamic speed limit control on a highway based on row distribution of passenger and freight intelligent networked vehicles comprises the following steps:

[0068] S10, obtaining a traffic flow operation state of a highway section, and determining that the highway section is a bottleneck section if the traffic flow operation state is a congested state, wherein the traffic flow of the highway section is a mixed traffic flow composed of intelligent connected vehicles (CAV vehicles) and manually driven vehicles (HV vehicles);

[0069] S20, activating the upstream road section of the bottleneck section is the row distribution control area section A1 and the dynamic speed limit control area section A2, wherein the row distribution control area section A1, the dynamic speed limit control area section A2 and the bottleneck section are adjacently arranged and the dynamic speed limit control area section A2 is between the bottleneck section and the row distribution control area section A1;

[0070] S30, based on the current vehicle driving information in the row distribution control area segment A1, the CAV passenger and freight vehicles in the row distribution control area segment A1 are grouped according to preset conditions, so that every two CAV passenger and freight vehicles form a target control vehicle group;

[0071] S40, regulating the CAV passenger and cargo vehicles in the same target regulated vehicle group so that two CAV passenger and cargo vehicles in the same target regulated vehicle group that meet the staggered distribution condition are in different driving lanes;

[0072] S51, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are in a row and parallel state at the current moment, if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are in a row and parallel state at the current moment, then proceeding to step S60, if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are not in a row and parallel state at the current moment, then proceeding to step S52;

[0073] Wherein, if the longitudinal distance between the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes is not greater than the preset row threshold, it is determined that the two CAV passenger and cargo vehicles of the same target regulated vehicle group are in a row parallel state;

[0074] S52, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes meet the condition of parallel driving in a row before reaching the end of the row distribution control area section A1; if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes meet the condition of parallel driving in a row before reaching the end of the row distribution control area section A1, then entering step S53,

[0075] S53, performing control so that two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes form a row and parallel state before reaching the end of the row distribution control area section A1;

[0076] S60, making the two CAV passenger and cargo vehicles in the row parallel state keep traveling side by side at the same speed to form a row parallel state with the same speed, and enter the dynamic speed limit control area section A2;

[0077] S70, deceleration control is performed on the CAV passenger and freight vehicles corresponding to the target regulated vehicle group that are traveling in a row and at the same speed in parallel within the dynamic speed limit control area section A2; deceleration control is performed on the single-row CAV passenger and freight vehicles that enter the dynamic speed limit control area section A2.

[0078] Aiming at the upcoming mixed flow scenarios, the present invention is based on the intelligent transportation Internet of Things application service technology, adopts the Beidou positioning system to obtain vehicle position, takes into account the differences in physical properties, driving characteristics and barrier effects of passenger and freight vehicles, and makes full use of the networked communication and automatic driving functions of intelligent connected vehicles (CAV), and provides a dynamic speed limit control method for highways based on passenger and freight intelligent connected vehicle barriers. At the same time, when a bottleneck section appears in the road conditions, the two CAV passenger and freight vehicles are combined to form a group of target control vehicles. The target control vehicle group is controlled to form a parallel driving state in the row distribution control area section A1, and further controlled to drive in parallel at the same speed; the target control vehicle group in the parallel driving state is controlled to slow down and drive side by side in the dynamic speed limit control area section A2, and a row distribution strategy is introduced to adjust the distribution of passenger and freight intelligent networked vehicles (CAV) in the mixed traffic flow. On the basis of optimizing the distribution pattern, the driving behavior of passenger and freight intelligent networked vehicles (CAV) is further controlled to guide the subsequent following manual vehicles (HV) to achieve early passive deceleration, thereby strengthening the mobile barrier effect, improving the control effect of the dynamic deceleration strategy, reducing the impact of the deceleration wave, reducing the collision risk near the bottleneck area and the probability of traffic accidents on the highway, and realizing flow-particle coordinated control.

[0079] Optionally, in the present invention, the traffic flow status of the highway section can be monitored in real time through roadside monitoring equipment and intelligent connected vehicle (CAV) sensing equipment to determine whether a bottleneck section appears on the section; it can be understood that when the bottleneck section appears, a trigger signal can be transmitted to the cloud through the road side or the vehicle side, and the cloud side starts the dynamic speed limit control module to activate the operation.

[0080] It can be understood that in the present invention, the length of the row distribution control area segment A1 is L, and the length of the dynamic speed limit control area segment A2 is H, which are set according to actual conditions; optionally, in the scheme of the present invention, an innovative concept of setting grouping conditions, row thresholds and lane changing conditions in a mixed flow scenario is proposed.

[0081] It can be understood that in the present invention, the Beidou positioning system can be used to locate and track CAV passenger and freight vehicles.

[0082] In a specific embodiment of the present invention, a roadside monitoring device and a CAV vehicle sensing device are used to monitor in real time whether a bottleneck section of traffic congestion occurs on the highway section. The bottleneck section refers to a section with slow traffic, which is generally a section where vehicles are slow due to sudden traffic accidents, the inflow and outflow of vehicles on the ramps, or the maintenance of the section. When the roadside device monitors the average speed of the traffic flow in the section or the CAV vehicle senses that the average speed V of the downstream vehicles within the communication range is lower than 50% of the normal maximum speed limit of the current section, and the duration exceeds 5 minutes, the section is determined to be a bottleneck section at this time, and the critical position where the speed decreases is defined as the starting point D of the bottleneck section. The traffic flow of the monitoring section (highway section) is a mixed flow composed of CAV vehicles and manually driven (HV) vehicles, in which CAV can not only act as a mobile sensor to collect and transmit information in real time through V2V and I2V technologies, but also act as an execution unit for decision control, which can receive instructions from the management and control system and realize unified control. At the same time, roadside equipment such as high-definition cameras, millimeter microwave radars and RSUs (roadside units) play an important role in collecting road section vehicle and traffic flow data. These monitoring devices can use roadside edge computing devices to extract features, calibrate and correlate the collected traffic data, and obtain traffic flow parameters of the monitored road section in real time. Therefore, the traffic information provided by CAV vehicles and the data collected by roadside monitoring equipment are coordinated and supplemented to achieve effective fusion of multi-source data. This comprehensive analysis can accurately assess the congestion of the monitored road section, identify whether there is a bottleneck section, and provide more refined information support for the safety management and control of subsequent vehicles.

[0083] Furthermore, step S30 specifically includes:

[0084] S31, obtaining the current vehicle driving information in the row distribution control area segment A1, the current vehicle driving information includes the vehicle position information, vehicle lane information, vehicle attribute information, vehicle speed information, vehicle acceleration information and vehicle longitudinal distance information of the CAV passenger and cargo vehicle, and constructing the CAV vehicle arrangement sequence database of the row distribution control area segment A1 by sorting the vehicles in a front-to-back order according to their driving directions; S32, obtaining the head CAV passenger and cargo vehicle and the second CAV passenger and cargo vehicle adjacent to the head CAV passenger and cargo vehicle in the CAV vehicle arrangement sequence database; S33, judging whether the distance between the second CAV passenger and cargo vehicle and the head CAV passenger and cargo vehicle is within a preset distance range; if the distance between the second CAV passenger and cargo vehicle and the head CAV passenger and cargo vehicle is within the preset distance range, entering step S34; if the distance between the second CAV passenger and cargo vehicle and the head CAV passenger and cargo vehicle is within the preset distance range, entering step S34; If the distance between the CAV passenger and cargo vehicles is not within the preset distance range, then go to step S35; S34, determine that the second CAV passenger and cargo vehicle and the head CAV passenger and cargo vehicle are a group of the target regulated vehicle groups, remove the head CAV passenger and cargo vehicle and the second CAV passenger and cargo vehicle from the current CAV vehicle arrangement sequence database to obtain the remaining arrangement database, and update the remaining arrangement database to the CAV vehicle arrangement sequence database and go to step S32; S35, remove the head CAV passenger and cargo vehicle from the current CAV vehicle arrangement sequence database to obtain the remaining arrangement database, and update the remaining arrangement database to the CAV vehicle arrangement sequence database and go to step S32; repeat steps S32 to S35, group all CAV passenger and cargo vehicles in the CAV vehicle arrangement sequence database, and obtain all target regulated vehicle groups of CAV passenger and cargo vehicles in the row distribution control area segment A1. The method for dynamic speed limit control of highways based on intelligent passenger and freight connected vehicle barriers of the present invention can be used for sections with two lanes in the same direction, sections with four lanes in the same direction, and sections with six lanes in the same direction. When used for even-numbered sections other than sections with two lanes in the same direction, the even-numbered sections can be divided into multiple groups of sections with two lanes in the same direction, and then the method of the present invention is used for corresponding processing. It can be understood that the preset distance range of the present invention can be set according to actual conditions.

[0085] In a specific implementation, the real-time movement information of vehicles in the row-distributed control area section A1 upstream of the bottleneck is collected and processed in real time by roadside equipment and CAV sensor equipment, specifically including the ID, type, position, speed, acceleration, lane, and quantity information of CAV vehicles, as well as the position, speed, and quantity information of HV vehicles. Traffic flow parameters, including headway, average speed of the current road section, traffic volume, traffic density, etc., are calculated by roadside edge computing equipment and uploaded to the cloud. CAV vehicles are grouped, and based on the ID, type, position, and quantity information of all CAV vehicles in the control area collected and processed by the vehicle-side and road-side and uploaded to the cloud, CAV vehicles that are located in similar positions in the row-distributed control area A1 are divided into groups in pairs according to the direction of travel, so that the passenger and freight CAV vehicles in the entire traffic flow in the control area A1 are divided into X groups, and the front and rear vehicles of each group are marked. Among them, similar position means that the longitudinal position difference of the two CAV vehicles in the driving direction is Within the threshold d meters, the CAV grouping conditions are as follows:

[0086]

[0087] Where: is the position of vehicle i-1, is the position of vehicle i, n is the number of CAV vehicles in the row distribution area, is the longitudinal position difference between the two vehicles, and d is the position difference threshold.

[0088] Furthermore, the CAV passenger and freight vehicle is a CAV bus or a CAV truck, the target control vehicle group is a combination of a CAV bus and a CAV bus, or the target control vehicle group is a combination of a CAV bus and a CAV truck, or the target control vehicle group is a group of a CAV truck and a CAV truck. In the present invention, the types of vehicles in the target control vehicle group are fully identified to arrange for subsequent adaptive control.

[0089] It can be understood that in the present invention, the vehicle parameters of the passenger and freight vehicles are as shown in Table 1:

[0090]

[0091] It can be understood that if the longitudinal distance between the two CAV passenger and cargo vehicles in the same target control vehicle group is not greater than the preset row threshold (row spacing value), it is determined that the two CAV passenger and cargo vehicles in the same target control vehicle group are in a row and parallel driving state. In specific implementation, based on the CAV position information of each group of target control vehicle groups, the longitudinal position difference in the driving direction between two vehicles in the CAV vehicle group located in different lanes is calculated. Is it less than or equal to the row spacing value? , if it is less than or equal to the row spacing value It is considered that the two CAV passenger and cargo vehicles of the same target control vehicle group are in a row and parallel driving state. At this time, it is sufficient to make the two CAV passenger and cargo vehicles of the same target control vehicle group drive in parallel in the row distribution control area segment A1; if it is greater than the row spacing value , it is considered that the two CAV passenger and cargo vehicles of the same target regulated vehicle group are not in a row of parallel driving state. At this time, control is required to determine whether the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes meet the row of parallel driving conditions before reaching the end of the row distribution control area section A1 (row distribution end line).

[0092] Preferably, the Does not meet the row spacing value The CAV train set is used to control the speed of the train set. The difference in length between passenger and freight CAVs and the minimum lane change gap of 3.5m are taken into consideration. The preset row threshold (row spacing value) is taken according to the row distribution train set type. The details are as follows:

[0093]

[0094] Where: is the row spacing value (m), It is the length of the front vehicle in the CAV vehicle group (m).

[0095] Preferably, a CAV train group that meets the conditions for the passenger and cargo CAVs to be arranged in a row is selected. If the CAV vehicles in the train group are located in different lanes and the longitudinal position difference between the two vehicles in the driving direction is Less than or equal to the row spacing value , then the vehicle group meets the row distribution condition (is in a row and parallel driving state), and the CAV vehicles in the vehicle group are driven at the same speed as the slower speed of the two vehicles. Drive in a row until entering the dynamic speed limit control area A2. The row distribution conditions are as follows:

[0096]

[0097] Where: The lane where the front vehicle in the vehicle group is located. The lane where the rear vehicle in the vehicle group is located. is the longitudinal position difference between the two vehicles in the train group (m), is the row spacing value (m).

[0098] Furthermore, the current vehicle driving information includes vehicle lane information, vehicle attribute information, and vehicle longitudinal distance information of the CAV passenger and freight vehicle. Step S40 specifically includes:

[0099] S41, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group are in different lanes. If the two CAV passenger and cargo vehicles of the same target control vehicle group are in different lanes, proceeding to step S42; if the two CAV passenger and cargo vehicles of the same target control vehicle group are in the same lane, proceeding to step S50; S42, regulating the CAV passenger and cargo vehicles of the same target control vehicle group so that the two CAV passenger and cargo vehicles of the same target control vehicle group that meet the lane shift distribution condition are in different driving lanes, wherein the formula is used. as well as Determine whether the error distribution condition is met. The vehicle position of any vehicle of the two CAV passenger and cargo vehicles in the target control vehicle group, The position of the vehicle behind the vehicle in the lane to be cut into. The position of the vehicle ahead of the vehicle in the lane to be cut into. is the preset safe lane change distance. ,and It can be understood that if the front vehicle distance corresponding to the CAV passenger and cargo vehicle in the target regulated vehicle group is greater than the first safety threshold, and the rear vehicle distance is greater than the second safety threshold, it is determined that the target regulated vehicle group meets the staggered distribution condition.

[0100] In a specific implementation, the CAV vehicle group located in the same lane and the position information of all vehicles in the control area A1 uploaded to the cloud are screened, and it is determined whether the CAV vehicles in the vehicle group have lane change space and meet the safe lane change conditions, and the CAV lane change control is performed to meet the condition that the CAV vehicles in the vehicle group are located in different lanes in the row distribution condition. Among them, the lane change space is defined as the longitudinal position corresponding to the subject vehicle is between the front and rear vehicles in the target lane; the safe lane change condition is defined as the longitudinal position difference between the front and rear vehicles in the target lane and the subject vehicle in the current lane is no more than Meters, as follows:

[0101]

[0102] Where: is the vehicle position (m), is the position of the vehicle behind in the target lane (m), is the position of the front vehicle in the target lane (m), is the safe lane-changing distance (m).

[0103] Furthermore, in step S42, “controlling the CAV passenger and cargo vehicles of the same target control vehicle group so that two CAV passenger and cargo vehicles of the same target control vehicle group that meet the lane-shifting distribution condition are in different driving lanes” specifically includes:

[0104] If only one of the CAV passenger and cargo vehicles in the target control vehicle group meets the lane-changing distribution condition, the CAV passenger and cargo vehicle that meets the safe lane-changing condition is controlled to change lanes;

[0105] If both of the two CAV passenger and freight vehicles in the target controlled vehicle group meet the lane-shifting distribution conditions, the vehicle types of the two CAV passenger and freight vehicles in the target controlled vehicle group are obtained; if the two vehicles are of different types, given that trucks are large in size and heavy in weight, their acceleration, deceleration and steering performance are not as flexible as buses, and more space and time are required for lane changing. In addition, trucks have large inertia, which increases the risk of lane changing and may cause greater interference to the surrounding traffic flow. In comparison, buses change lanes more directly and quickly, so the CAV vehicle of bus type is controlled to change lanes; if the two vehicles are of the same type, the CAV vehicle in front is controlled to perform lane changing based on their front and rear positions in the queue.

[0106] Further, in step S52, assuming that the current time is t, the time when the leading vehicle A and the trailing vehicle B of the same target control vehicle group travel to the row distribution state is , is the deceleration of the preceding vehicle A, is the minimum speed limit, for The distance between the preceding vehicle A and the starting point of the row distribution area at time, for The distance between the rear vehicle B and the starting point of the row distribution area at time, are the speeds of the front vehicle A and the rear vehicle B at time t, are the distances from the front vehicle A to the starting point of the row distribution area and the distances from the rear vehicle B to the starting point of the row distribution area at time t, for The speed of the preceding vehicle A at time t, is the time required for vehicle group i to form a row,

[0107] Using formula

[0108]

[0109] Get The distance between the front vehicle A and the starting point of the row distribution area and the distance between the rear vehicle B and the starting point of the row distribution area at the moment;

[0110] make (Assuming that the parallel state is within the cutoff line), solving the equation with equal signs on both sides yields The value of The length of the row distribution control area section A1;

[0111] right The value of is tested, if it satisfies the constraint formula , it is judged that the front vehicle A and the rear vehicle B meet the parallel row condition, indicating that before the front vehicle A reaches the end of the vehicle row area, the vehicle distance between vehicles A and B meets the row requirement. for The current real-time distance between the front vehicle A and the rear vehicle B at the moment, To determine the spacing in a preset row;

[0112] Among them, the traversal search method is used for solution and verification, and the deceleration is set The initial deceleration value is 0.5m / s 2 ,Will Substitute the equations in ascending order from 1s and increment by whole seconds, and calculate and , and determine whether the row constraint is met; if the constraint formula is met , then the current The value is a feasible solution and the search stops; if the constraint formula is not satisfied , then 0.1m / s 2 Gradually increase the deceleration by units , and re-solve the equation to calculate the feasible solution. The upper limit is 2m / s 2 ;

[0113] If the constraint formula is still not satisfied after traversal , it is determined that the two CAV passenger and cargo vehicles of the same target regulated vehicle group in different lanes do not meet the row-by-row parallel driving condition before reaching the end (row-by-row distribution finish line) of the row-by-row distribution control area segment A1.

[0114] Furthermore, if the constraint formula is satisfied , then get The feasible solution of the target control vehicle group is calculated to be the vehicle platooning time t+ , row speed and , row acceleration And row position and ,

[0115] The vehicle platooning time t+ of the two CAV passenger and cargo vehicles of the target control vehicle group , row speed and , row acceleration And row position and The speed of the corresponding CAV passenger and freight vehicles in the group is controlled.

[0116] Optionally, in step S52, by solving the feasible solution of the formula, it is determined whether the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes meet the condition of parallel driving in a row before reaching the end (end line of distribution in a row) of the control area section A1 distributed in a row; if there is a feasible solution, it is determined whether the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes meet the condition of parallel driving in a row before reaching the end (end line of distribution in a row) of the control area section A1 distributed in a row; in step S53, the feasible solution of the formula is used for control to achieve the purpose of forming a parallel driving state in a row for the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes before reaching the end (end line of distribution in a row) of the control area section A1 distributed in a row.

[0117] In specific implementation, based on screening out vehicles located in different lanes but with different longitudinal positions in the driving direction Does not meet the row spacing value The CAV group and the position, speed, and acceleration information of the intelligent connected vehicles (CAVs) in the control area A1 uploaded to the cloud are used to control the speed of the CAVs to meet the conditions of the row distribution of the intelligent connected vehicles (CAVs) in the group. Must be less than or equal to , ultimately allowing intelligent connected vehicles (CAVs) to travel in a row before reaching the end of the row distribution control area A1.

[0118] Furthermore, the current longitudinal position difference of each group of selected intelligent connected vehicles (CAVs) along the driving direction is calculated in turn. As the target distance, it is determined whether the speed of the vehicle ahead at the target distance can be reduced, and the speed is not less than the minimum speed limit to ensure the traffic efficiency, so that the target distance is continuously reduced until the platooning requirements of intelligent connected vehicles (CAVs) are met.

[0119] Furthermore, assume that in each group of selected CAVs, the rear vehicle B maintains the current speed, while the front vehicle A decelerates at a comfortable deceleration, and the speed must not be less than the minimum speed limit. The current time is t, and the time when vehicles A and B are in a row is .

[0120] Further, The speed of the front vehicle A at the moment and the distances of the front vehicle A and the rear vehicle B from the starting point of the row distribution area are calculated according to the following formula:

[0121]

[0122] Where: , , are the speeds of the front car A and the rear car B at time t (m / s) and the distances from the starting point of the row distribution area (m), is the time required for vehicle group i to form a row (s), for The speed of vehicle A at the moment before (m / s), is the deceleration of the front vehicle A (m / s 2 ), is the minimum speed limit (m / s), , They are The distance (m) between the front vehicle A and the rear vehicle B and the starting point of the row distribution area at the moment.

[0123] Further, let , take the equal sign on both sides and solve the equation, we can get value and check whether the row constraints are met.

[0124] Furthermore, the row constraint is calculated as follows:

[0125]

[0126] Furthermore, if the above constraints are met, it means that before the front vehicle A reaches the end of the vehicle platooning area, the distance between vehicles A and B meets the platooning requirement. The value is a feasible solution.

[0127] Furthermore, due to The value will not be too large, and the traversal search method can be used to solve it. Take the smaller value 0.5m / s 2 ,Will Substitute 1s into the above equation in ascending order and calculate , The value of and judge whether the platoon constraint condition is met; if the above conditions are met, it means that the vehicles of the vehicle group can be in a platoon before the front vehicle A arrives at the end of the platoon control section. The value is a feasible solution and the search stops; if the above conditions are not met, the speed is increased by 0.1m / s 2 Gradually increase the unit value, and re-solve the equation to calculate the feasible solution. The upper limit is temporarily set at 2m / s 2 After obtaining a feasible solution, the calculated vehicle formation time t+ , row speed and , row acceleration and And row position and The signal is sent to the corresponding intelligent connected vehicle (CAV) in the group to control its speed. If the signal is still not satisfied, the group will not control its speed.

[0128] Furthermore, when two vehicles in a CAV group are located in different lanes and the longitudinal position difference in the driving direction is less than or equal to the row spacing value, the two vehicles are ordered to move at the same speed. Maintain driving in a row to enhance the mobile barrier effect formed by the subsequent dynamic speed limit control of passenger and freight intelligent connected vehicles (CAV).

[0129] Furthermore, in step S70, the actual deceleration of the CAV passenger and freight vehicles traveling in a row in the dynamic speed limit control area A2 is determined. , control the two CAV passenger and cargo vehicles of the target control vehicle group that have been traveling in a row to have the same actual deceleration Driving;

[0130] Determine the actual deceleration of CAV passenger and freight vehicles not traveling in a row in the dynamic speed limit control area segment A2 , control the CAV passenger and cargo vehicle to the actual vehicle deceleration Driving, forming a mobile barrier, guiding the following HVs to passively slow down in advance before reaching the bottleneck area;

[0131] The dynamic speed limit model formula is as follows:

[0132]

[0133] In the formula, is the vehicle deceleration calculated according to the dynamic speed limit formula, are the vehicle speed and vehicle position of the vehicle, respectively. , ,..., is the speed of all CAV vehicles in front of the vehicle within the wireless communication range, , ,..., The positions of all CAV vehicles in front of the vehicle within the wireless communication range;

[0134] Among them, the actual dynamic speed limit model formula is as follows:

[0135]

[0136] In the formula, is the gap error of vehicle i at the current time k, , , , are the speed and position of vehicle i and vehicle i-1 at the current time k, is the driver of the preceding vehicle A, =1.1 is the expected workshop time interval, =0.04, =0.8, and To control the gain parameter, is the actual deceleration of CAV vehicles not traveling in a platoon, is the actual deceleration of CAV vehicles traveling in a row, is the vehicle deceleration calculated according to the car-following model, is the maximum deceleration of the vehicle, is the vehicle deceleration calculated according to the dynamic speed limit formula, are the vehicle decelerations calculated by the following model for the front vehicle A and the rear vehicle B in the vehicle group, are the vehicle decelerations calculated by the dynamic speed limit formula for the front vehicle A and the rear vehicle B in the vehicle group, is the maximum acceleration change of the passenger and cargo CAV in adjacent time steps, where =2, CAV bus =3.

[0137] In specific implementation, when a CAV enters the dynamic speed limit control area section A2, each controlled CAV can obtain the status information of all downstream CAVs within the reliable communication range (300m) in real time through vehicle-to-vehicle communication technology (V2V) and invisible visualization technology (I2V), including speed and location information.

[0138] Furthermore, by analyzing this information, the CAV can evaluate the downstream traffic status and prepare for passive deceleration in advance. At the same time, this information will also be used to assist in calculating the corresponding deceleration values ​​of passenger and freight CAVs when they are in the control area A2, and perform dynamic speed limit control.

[0139] Furthermore, the dynamic speed limit deceleration is calculated according to the following formula:

[0140]

[0141] Where: is the vehicle deceleration calculated according to the dynamic speed limit formula (m / s 2 ), are the speed and position of the vehicle, , ,..., is the speed of all connected vehicles (CAVs) in front of the vehicle within the wireless communication range, , ,..., The positions of all connected vehicles (CAVs) in front of the vehicle within the wireless communication range.

[0142] Furthermore, in order to avoid traffic oscillation and traffic accidents and make the deceleration value more reasonable, the maximum deceleration limit and the following deceleration are added. On this basis, the CAV groups that have been traveling in a row and the intelligent connected vehicles (CAV) that are not in a row are selected respectively, and the difference in the dynamic performance of passenger and freight vehicles is comprehensively considered, that is, the acceleration and deceleration capabilities of trucks are relatively limited compared with those of buses, and their acceleration and deceleration change rate is relatively small. The final actual deceleration value of the passenger and freight intelligent connected vehicles (CAV) is calculated by comparison to ensure the smoothness and safety of the deceleration process.

[0143] Furthermore, the actual dynamic speed limit deceleration is calculated according to the following formula:

[0144]

[0145] In the formula, is the gap error of vehicle i at the current time k, , , , are the speed and position of vehicle i and vehicle i-1 at the current time k, is the driver of the preceding vehicle A, =1.1 is the expected workshop time interval, =0.04, =0.8, and To control the gain parameter, is the actual deceleration of CAV vehicles not traveling in a platoon, is the actual deceleration of CAV vehicles traveling in a row, is the vehicle deceleration calculated according to the car-following model, is the maximum deceleration of the vehicle, is the vehicle deceleration calculated according to the dynamic speed limit formula, are the vehicle decelerations calculated by the following model for the front vehicle A and the rear vehicle B in the vehicle group, are the vehicle decelerations calculated by the dynamic speed limit formula for the front vehicle A and the rear vehicle B in the vehicle group, is the maximum acceleration change of the passenger and cargo CAV in adjacent time steps, where =2, CAV bus =3.

[0146] Furthermore, according to the actual dynamic speed limit value finally obtained, the passenger and cargo intelligent networked vehicles (CAV) in the control area A2 use their automation functions to accurately execute the dynamic speed limit instruction, that is, the corresponding deceleration. or , where the two vehicles in the CAV group that have been traveling in a row execute the same deceleration value to retain the row effect, while the intelligent connected vehicles (CAVs) that are not in a row execute their corresponding deceleration values, so that the passenger and freight intelligent connected vehicles (CAVs) form a mobile barrier, guiding the subsequent manually driven vehicles (HVs) to achieve early passive deceleration, so that the speed of upstream vehicles is as consistent as possible with the speed of downstream traffic flow, and vehicles can smoothly transition from the normal road section to the bottleneck section B, thereby reducing the impact of the deceleration wave, avoiding the risk of collision caused by sudden braking, and improving traffic safety near the bottleneck.

[0147] Furthermore, based on the vehicle operation and traffic flow data collected by roadside equipment and CAV vehicle sensor equipment and uploaded to the cloud at a fixed period, the database is updated in real time, and the platoon distribution and dynamic speed limit models are dynamically corrected according to the feedback of the control effect, the model parameters are adjusted, the model code is corrected, and a new round of dynamic speed limit monitoring and control is implemented.

[0148] In a specific embodiment of the present invention, using TTC The derived indicators TET and TIT respectively measure the duration and risk of dangerous situations to evaluate the collision risk in the bottleneck area, which is specifically carried out through the following formula:

[0149]

[0150] Where: , are the position and speed of the preceding vehicle at time t, , are the position and speed of the following car at time t, is the driver of the vehicle in front, =4s is used to judge the safety and unsafe situation of the vehicle following TTC Threshold, is the selection variable (0 or 1) at time t, is the time step, N is the number of vehicles on the road section, For total time.

[0151] In a specific embodiment of the present invention, under different CAV penetration rates and CAV truck (CAV-T) ratios, the bottleneck section collision risk values ​​TET and TIT extracted by implementing row distribution and dynamic speed limit strategies on two lanes are shown in Table 2:

[0152]

[0153] In a specific embodiment of the present invention, with no control as the control group, under different CAV penetration rates and CAV truck proportions, the bottleneck section collision risk values ​​TET and TIT improvement ratios extracted by implementing row distribution and dynamic speed limit strategies on two lanes are shown in Table 3:

[0154]

[0155] The present invention also provides a dynamic speed limit control system for expressways based on passenger and freight intelligent networked vehicle barriers, a data acquisition module for holographically sensing the driving environment of a road section, and using roadside sensing equipment and intelligent networked vehicle sensing equipment to obtain information on vehicle movement and traffic flow operation status of the expressway section in real time; a monitoring module for real-time monitoring and determining whether a traffic bottleneck section appears on the road section based on the acquired information on vehicle movement and traffic flow operation status; a computing module for searching strategies for lane changing and speed control schemes for passenger and freight intelligent networked vehicles (CAVs), the roadside sensing equipment and intelligent networked vehicle (CAV) sensing equipment upload the collected and processed vehicle movement and traffic flow information in the row distribution control area A1 and the dynamic speed limit control area A2 to the cloud, and the cloud performs computing to obtain a control scheme; a control module for sending and executing the row distribution strategy and dynamic speed limit instructions for passenger and freight intelligent networked vehicles (CAVs), the cloud feeds back the control scheme to the corresponding intelligent networked vehicle (CAV), and the intelligent networked vehicle (CAV) receives the command to change lanes or control the speed.

[0156] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program is used to be programmed or configured by a microprocessor to execute the steps of the above-mentioned method for dynamic speed limit control of highways based on intelligent connected vehicle barriers for passengers and freight.

[0157] The above are preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

Claims

1. A method for dynamic speed limit control on expressways based on intelligent passenger and freight connected vehicle barriers, characterized in that: Includes steps: S10, obtaining a traffic flow operation state of a highway section, and determining that the highway section is a bottleneck section if the traffic flow operation state is a congested state, wherein the traffic flow of the highway section is a mixed traffic flow consisting of intelligent networked vehicles and manually driven vehicles; S20, activating the upstream road section of the bottleneck section is the row distribution control area section A1 and the dynamic speed limit control area section A2, wherein the row distribution control area section A1, the dynamic speed limit control area section A2 and the bottleneck section are adjacently arranged and the dynamic speed limit control area section A2 is between the bottleneck section and the row distribution control area section A1; S30, based on the current vehicle driving information in the row distribution control area segment A1, the CAV passenger and freight vehicles in the row distribution control area segment A1 are grouped according to preset conditions, so that every two CAV passenger and freight vehicles form a target control vehicle group; S40, regulating the CAV passenger and cargo vehicles in the same target regulated vehicle group so that two CAV passenger and cargo vehicles in the same target regulated vehicle group that meet the staggered distribution condition are in different driving lanes; S51, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are in a row and parallel state at the current moment, if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are in a row and parallel state at the current moment, then proceeding to step S60, if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes are not in a row and parallel state at the current moment, then proceeding to step S52; Wherein, if the longitudinal distance between the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes is not greater than the preset row threshold, it is determined that the two CAV passenger and cargo vehicles of the same target regulated vehicle group are in a row parallel state; S52, determining whether the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes meet the parallel driving condition in a row before reaching the end of the row distribution control area section A1; if the two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes meet the parallel driving condition in a row before reaching the end of the row distribution control area section A1, proceeding to step S53; S53, performing control so that two CAV passenger and cargo vehicles of the same target control vehicle group on different lanes form a row and parallel state before reaching the end of the row distribution control area section A1; S60, making the two CAV passenger and cargo vehicles in the row parallel state keep traveling side by side at the same speed to form a row parallel state with the same speed, and enter the dynamic speed limit control area section A2; S70, deceleration control is performed on the CAV passenger and freight vehicles corresponding to the target regulated vehicle group that are traveling in a row and at the same speed in parallel within the dynamic speed limit control area section A2; deceleration control is performed on the single-row CAV passenger and freight vehicles that enter the dynamic speed limit control area section A2.

2. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 1 is characterized in that: Step S30 specifically includes: S31, obtaining the current vehicle driving information in the row distribution control area segment A1, the current vehicle driving information including the vehicle position information, vehicle lane information, vehicle attribute information, vehicle speed information, vehicle acceleration information and vehicle longitudinal distance information of the CAV passenger and freight vehicles, and constructing the CAV vehicle arrangement sequence database of the row distribution control area segment A1 by sorting the vehicles in a front-to-back order according to the vehicle driving direction; S32, obtaining a leading CAV passenger and cargo vehicle and a second CAV passenger and cargo vehicle adjacent to the leading CAV passenger and cargo vehicle in the CAV vehicle arrangement sequence database, wherein the leading CAV passenger and cargo vehicle is the first CAV passenger and cargo vehicle in the arrangement sequence; S33, determining whether the distance between the second CAV passenger and cargo vehicle and the leading CAV passenger and cargo vehicle is within a preset distance range, if the distance between the second CAV passenger and cargo vehicle and the leading CAV passenger and cargo vehicle is within the preset distance range, proceeding to step S34, if the distance between the second CAV passenger and cargo vehicle and the leading CAV passenger and cargo vehicle is not within the preset distance range, proceeding to step S35; S34, determining that the CAV passenger and freight vehicle at the next position and the CAV passenger and freight vehicle at the leading position are a group of the target control vehicles, removing the CAV passenger and freight vehicle at the leading position and the CAV passenger and freight vehicle at the next position from the current CAV vehicle arrangement sequence database to obtain a remaining arrangement database, and updating the remaining arrangement database to the CAV vehicle arrangement sequence database and entering step S32; S35, removing the head CAV passenger and freight vehicle from the current CAV vehicle arrangement sequence database to obtain a remaining arrangement database, and updating the remaining arrangement database to the CAV vehicle arrangement sequence database and proceeding to step S32; Repeat steps S32 to S35 to group all CAV passenger and freight vehicles in the CAV vehicle arrangement sequence database, and obtain all target control vehicle groups of CAV passenger and freight vehicles in the row distribution control area segment A1.

3. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 2 is characterized in that: The CAV passenger and cargo vehicle is a CAV passenger car or a CAV truck, The target control vehicle group is a combination of a CAV bus and a CAV bus, or The target control vehicle group is a combination of a CAV passenger car and a CAV truck, or The target control vehicle group is a combination of a CAV truck and a CAV truck.

4. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 2 is characterized in that: Step S40 specifically includes: S41, judging whether the two CAV passenger and cargo vehicles of the same target control vehicle group are in different lanes, if the two CAV passenger and cargo vehicles of the same target control vehicle group are in different lanes, proceeding to step S42; if the two CAV passenger and cargo vehicles of the same target control vehicle group are in the same lane, proceeding to step S50; S42, regulating the CAV passenger and cargo vehicles in the same target regulated vehicle group so that two CAV passenger and cargo vehicles in the same target regulated vehicle group that meet the lane-shifting distribution condition are in different driving lanes; Among them, the formula as well as Determine whether a single vehicle in the vehicle group meets the safe lane change conditions. If a single vehicle meets the safe lane change conditions, determine whether the two CAV passenger and freight vehicles in the vehicle group meet the lane-changing distribution conditions. The vehicle position of any vehicle of the two CAV passenger and cargo vehicles in the target control vehicle group, The position of the vehicle behind the vehicle in the lane to be cut into. The position of the vehicle ahead of the vehicle in the lane to be cut into. is the preset safe lane change distance. ,and , then it is determined that the error distribution condition is met.

5. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 4 is characterized in that: In step S42, the CAV passenger and cargo vehicles of the same target control vehicle group are controlled so that two CAV passenger and cargo vehicles of the same target control vehicle group that meet the lane-shifting distribution condition are in different driving lanes, specifically including: If only one of the CAV passenger and cargo vehicles in the target control vehicle group meets the lane-changing distribution condition, the CAV passenger and cargo vehicle that meets the safe lane-changing condition is controlled to change lanes; If the two CAV passenger and freight vehicles in the target controlled vehicle group both meet the lane-changing distribution condition, the vehicle types of the two CAV passenger and freight vehicles in the target controlled vehicle group are obtained; if the vehicle types of the two vehicles are different, the CAV vehicle whose vehicle type is a passenger car is controlled to perform a lane-changing action; if the vehicle types of the two vehicles are the same, the CAV vehicle in front is controlled to perform a lane-changing action.

6. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 1 is characterized in that: In step S52, assuming that the current time is t, the time when the leading vehicle A and the trailing vehicle B of the same target control vehicle group travel to the row distribution state is , is the deceleration of the preceding vehicle A, is the minimum speed limit, for The distance between the preceding vehicle A and the starting point of the row distribution area at time, for The distance between the rear vehicle B and the starting point of the row distribution area at time, are the speeds of the front vehicle A and the rear vehicle B at time t, are the distances from the front vehicle A to the starting point of the row distribution area and the distances from the rear vehicle B to the starting point of the row distribution area at time t, for The speed of the preceding vehicle A at time t, is the time required for vehicle group i to form a row, Using formula Get The distance between the front vehicle A and the starting point of the row distribution area and the distance between the rear vehicle B and the starting point of the row distribution area at the moment; make , when both sides are equal, we can solve the equation to get The value of is the length of the row distribution control area segment A1; right The value of is tested, if it satisfies the constraint formula , it is judged that the front vehicle A and the rear vehicle B meet the parallel row condition, indicating that before the front vehicle A reaches the end of the vehicle row area, the vehicle distance between vehicles A and B meets the row requirement. for The current real-time distance between the front vehicle A and the rear vehicle B at the moment, To determine the spacing in a preset row; Among them, the traversal search method is used for solution and verification, and the deceleration is set The initial deceleration value is 0.5m / s 2 ,Will Substitute the equations in ascending order from 1s and increment by whole seconds, and calculate and , and determine whether the row constraint is met; if the constraint formula is met , then the current The value is a feasible solution and the search stops; if the constraint formula is not satisfied , then 0.1m / s 2 Gradually increase the deceleration by units , and re-solve the equation to calculate the feasible solution. The upper limit is 2m / s 2 ; If the constraint formula is still not satisfied after traversal , it is determined that the two CAV passenger and cargo vehicles of the same target regulated vehicle group on different lanes do not meet the row parallel driving condition before reaching the end of the row distribution control area section A1.

7. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 6 is characterized in that: If the constraint formula is satisfied , then get The feasible solution of the target control vehicle group is calculated to be the vehicle platooning time t+ , row speed and , row acceleration And row position and , The vehicle platooning time t+ of the two CAV passenger and cargo vehicles of the target control vehicle group , row speed and , row acceleration And row position and , and speed control is performed on the corresponding CAV passenger and freight vehicles in the group.

8. The method for dynamic speed limit control of highways based on passenger and freight intelligent networked vehicle barriers according to claim 1 is characterized in that: In step S70, the actual deceleration of the CAV passenger and freight vehicles traveling in a row in the dynamic speed limit control area A2 is determined. , control the two CAV passenger and cargo vehicles of the target control vehicle group that have been traveling in a row to have the same actual deceleration Driving; Determine the actual deceleration of CAV passenger and freight vehicles not traveling in a row in the dynamic speed limit control area segment A2 , control the CAV passenger and cargo vehicle to the actual vehicle deceleration Driving.

9. A dynamic speed limit control system for highways based on intelligent passenger and freight connected vehicle barriers, characterized in that: The data acquisition module is used to holographically perceive the driving environment of the road section, and use roadside sensing equipment and intelligent connected vehicle sensing equipment to obtain real-time information on vehicle movement and traffic flow operation status on the highway section; The monitoring module monitors in real time whether a traffic bottleneck occurs on the road section based on the information obtained about vehicle movement and traffic flow operation status; A computing module is used for searching strategies for lane changing and speed control schemes of passenger and freight intelligent networked vehicles. The roadside sensing equipment and the intelligent networked vehicle sensing equipment upload the collected and processed vehicle movement and traffic flow information in the row distribution control area A1 and the dynamic speed limit control area section A2 to the cloud, and the cloud computing obtains a control scheme, which is used to implement the dynamic speed limit control method for highways based on passenger and freight intelligent networked vehicle barriers as described in any one of claims 1 to 8; The control module is used for the platoon distribution of passenger and freight intelligent connected vehicles and the sending and execution of dynamic speed limit instructions. The cloud will feed back the control plan to the corresponding intelligent connected vehicle, and the intelligent connected vehicle will receive the command to change lanes or control speed.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which is used to be programmed or configured by a microprocessor to execute the steps of the method for dynamic speed limit control of highways based on a passenger and freight intelligent connected vehicle barrier as described in any one of claims 1 to 8.

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