Intelligent connected vehicle speed calculation method and system considering fairness of bottleneck area traffic

Abstract

The application provides a smart connected vehicle speed calculation method and system considering the fairness of the bottleneck area traffic, comprising: setting a statistical period, counting the traffic flow of the abnormal event point in the set historical period to the current time, and determining the traffic capacity of the bottleneck area formed by the abnormal event; setting control areas with different functions on the upstream of the bottleneck area according to the size of the abnormal event; calculating the average traffic speed and traffic density of the vehicles in the control area; in the flow limiting area, calculating the current traffic demand, comparing the size of the traffic demand and the traffic capacity of the bottleneck area, and adjusting the speed of the smart connected vehicle; in the speed coordination area, when the number of queued vehicles on the lane where the abnormal event occurs reaches a preset number, comparing the size of the vehicle speed on the lane where the abnormal event occurs and the vehicle speed on the adjacent lane, and reducing the speed of the smart connected vehicle on the corresponding lane. The application can control the micro driving behavior of the smart connected vehicle, guide the movement of the manually driven vehicle, and improve the traffic efficiency and safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent traffic management, and in particular to an intelligent connected vehicle speed calculation method and system considering traffic fairness in a bottleneck area. BACKGROUND

[0002] With the high-quality development of China's social economy and the increasing demand for transportation, expressways, as an important part of comprehensive transportation hubs, provide a major channel for medium and long-distance transportation. However, the increasing demand for travel has made the traffic environment increasingly complex, and traffic flow management is facing severe challenges. In particular, when the road is temporarily maintained or a traffic accident occurs, the number of available lanes on the expressway is reduced, and it is urgent to design reasonable traffic flow control measures to deal with abnormal events. The development of intelligent connected driving technology provides an opportunity for the development of reasonable control measures and provides a new direction for the development of traffic efficiency. However, before the implementation of intelligent connected driving technology in the entire road network, a mixed flow of manually driven vehicles and intelligent connected vehicles will exist for a long time, and the uncertainty of the movement behavior of manually driven vehicles will bring new challenges to the development of control measures.

[0003] At present, the research on traffic flow control methods in the bottleneck area of the expressway has accumulated a certain amount of theory, among which the variable speed limit research is the most representative. Variable speed limit control is to dynamically calculate the optimal speed limit value of vehicles in the control area according to the real-time traffic flow state, but the compliance rate of the driver will greatly affect the control effect. The development of intelligent connected driving technology provides favorable conditions for efficient and precise implementation of variable speed limit control. In a mixed flow environment, how to indirectly guide the movement behavior of manually driven vehicles by taking advantage of the controllability, safety, and sensitivity of intelligent connected vehicles to optimize the implementation effect of variable speed limit control is the key to improving the traffic efficiency and safety of vehicles in the bottleneck area. SUMMARY

[0004] In view of this, the embodiments of the present application provide an intelligent connected vehicle speed calculation method and system considering traffic fairness in a bottleneck area to eliminate or improve one or more defects in the prior art.

[0005] In one aspect, the present application provides an intelligent connected vehicle speed calculation method considering traffic fairness in a bottleneck area, which comprises the following steps:

[0006] Set a statistical period to statistically traffic flow of an abnormal event point from a set historical period to the current time; determine the traffic capacity of a bottleneck area formed by the abnormal event according to the traffic flow; set a flow limiting area and a speed coordination area upstream of the bottleneck area according to the size of the abnormal event; wherein one side of the speed coordination area is the bottleneck area, and the other side is the flow limiting area;

[0007] statistically count vehicle moving information in the traffic restriction zone and the speed coordination zone, calculate vehicle average passing speed and traffic density in the traffic restriction zone, and calculate vehicle average passing speed and traffic density in the speed coordination zone;

[0008] in the traffic restriction zone, calculate current traffic demand according to vehicle average passing speed and traffic density in the traffic restriction zone, and adjust intelligent connected vehicle speed by comparing the traffic demand and the passing capacity of the bottleneck zone;

[0009] in the speed coordination zone, when the number of queued vehicles in the lane where the abnormal event occurs reaches a preset number, compare the speed of vehicles in the lane where the abnormal event occurs with the speed of vehicles in adjacent lanes, and decelerate intelligent connected vehicles on the corresponding lane according to a preset deceleration rule.

[0010] In some embodiments of the present application, statistically counting vehicle moving information in the traffic restriction zone and the speed coordination zone comprises:

[0011] capturing vehicle moving trajectories in the traffic restriction zone and the speed coordination zone by using a traffic detector, including passing speed and position of vehicles in different lanes in the traffic restriction zone and the speed coordination zone; and statistically counting the number of queued vehicles in the lane where the abnormal event occurs in the speed coordination zone.

[0012] In some embodiments of the present application, in the traffic restriction zone, current traffic demand is calculated according to vehicle average passing speed and traffic density in the traffic restriction zone, wherein the calculation formula of the traffic demand is:

[0013]

[0014] wherein, denotes traffic demand of the traffic restriction zone at time t; denotes vehicle average passing speed of the traffic restriction zone at time t; denotes traffic density of the traffic restriction zone at time t.

[0015] In some embodiments of the present application, intelligent connected vehicle speed is adjusted by comparing the traffic demand and the passing capacity of the bottleneck zone, comprising:

[0016] if the traffic demand is greater than the passing capacity of the bottleneck zone, the intelligent connected vehicle speed is reduced;

[0017] if the traffic demand is less than the passing capacity of the bottleneck zone, the intelligent connected vehicle speed is increased.

[0018] In some embodiments of the application, in the flow restriction area, when determining the individual intelligent connected vehicle passing speed, the method further comprises:

[0019] According to the passing capacity of the bottleneck area and the traffic density of the flow restriction area, the intelligent connected vehicle speed limit value of the flow restriction area is calculated, and the calculation formula is:

[0020]

[0021] Among them, denotes the intelligent connected vehicle speed limit value of the flow restriction area at time t; denotes the passing capacity of the bottleneck area at time t; denotes the traffic density of the flow restriction area at time t.

[0022] In some embodiments of the application, the method further comprises:

[0023] A safety constraint condition is set for the intelligent connected vehicle speed, the constraint condition includes that the vehicle's own speed change rate in the flow restriction area is less than the maximum acceleration and the vehicle maintains a safe distance from the front vehicle, and the calculation formula is:

[0024]

[0025] Among them, denotes the speed of vehicle i at time t; a max denotes the maximum acceleration; denotes the position of vehicle i at time t; h min denotes the minimum safe headway between vehicles; L denotes the average vehicle length; Δt denotes the time step; denotes the acceleration of vehicle i at time t.

[0026] In some embodiments of the application, when the vehicle maintains a safe distance from the front vehicle, the method further comprises:

[0027] When the front vehicle of the target intelligent connected vehicle is an artificial driving vehicle, the artificial driving vehicle follows the following formula:

[0028]

[0029] Among them, denotes the acceleration of the artificial driving vehicle at time t; a max denotes the maximum acceleration; u denotes the free flow speed; denotes the speed of the artificial driving vehicle at time t; denotes the desired headway; denotes the speed difference between the target intelligent connected vehicle and the front artificial driving vehicle; s0 denotes the safe headway; h mindenotes the desired headway; b denotes the maximum deceleration.

[0030] In some embodiments of the present application, the speed of the vehicle on the lane where the abnormal event occurs is compared with the speed of the vehicle on the adjacent lane, and the intelligent connected vehicle on the corresponding lane is decelerated according to a preset deceleration rule, including:

[0031] When the speed of the vehicle on the lane where the abnormal event occurs is greater than the speed of the vehicle on the adjacent lane, a first quotient value of the difference between the two speeds and the time step is calculated, and when the first quotient value is greater than the maximum deceleration, it is determined whether the vehicle on the lane where the abnormal event occurs can safely pass at the maximum deceleration. If the safety constraint condition cannot be met, the speed is updated using the intelligent driving model rule; when the first quotient value is not greater than the maximum deceleration, it is determined whether the vehicle on the lane where the abnormal event occurs can safely pass at the first quotient value as the deceleration. If the safety constraint condition cannot be met, the speed is updated using the intelligent driving model rule;

[0032] When the speed of the vehicle on the lane where the abnormal event occurs is less than the speed of the vehicle on the adjacent lane, a second quotient value of the difference between the two speeds and the time step is calculated, and when the second quotient value is less than the maximum deceleration, the speed of the vehicle on the adjacent lane is decelerated to the speed of the vehicle on the lane where the abnormal event occurs. Otherwise, the speed is updated using the intelligent driving model rule.

[0033] In another aspect, the present application also provides an intelligent connected vehicle speed calculation system considering the fairness of passing through a bottleneck area, the system comprising:

[0034] An input layer for counting the traffic information of the bottleneck area formed by the abnormal event, and setting a flow limiting area and a speed coordination area upstream of the bottleneck area according to the size of the abnormal event, and counting the traffic information of the flow limiting area and the speed coordination area;

[0035] A model layer for calculating the speed of the target intelligent connected vehicle using any of the intelligent connected vehicle speed calculation methods considering the fairness of passing through a bottleneck area mentioned above according to the traffic information counted by the input layer;

[0036] An output layer for outputting the speed of the target intelligent connected vehicle calculated by the model layer.

[0037] In another aspect, the present application also provides a computer readable storage medium having a computer program / instruction stored thereon, which, when executed by a processor, implements the steps of the method according to any of the above embodiments.

[0038] The application provides a smart connected vehicle speed calculation method and system considering the fairness of passing through a bottleneck area, which can control the micro driving behavior of the smart connected vehicle, guide the movement of the manually driven vehicle, and improve the passing efficiency and safety.

[0039] Additional advantages, objects, and features of the application will be set forth in part by the description that follows, and will become apparent to those skilled in the art upon examination of the following or can be learned by practice of the application. The objects and other advantages of the application can be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0040] It will be understood by those skilled in the art that the objects and advantages of the present application realized can not be limited to the above specific description, and the above and other objects realized by the present application can be more clearly understood according to the following detailed description. BRIEF DESCRIPTION OF DRAWINGS

[0041] The drawings described herein are used to provide further understanding of the present application, constitute a part of the present application, and do not constitute a limitation of the present application. In the drawings:

[0042] Figure 1 The figure is a schematic diagram of the steps of the smart connected vehicle speed calculation method considering the fairness of passing through a bottleneck area in an embodiment of the present application.

[0043] Figure 2 The figure is a structural schematic diagram of the abnormal event occurring road section and the control area in an embodiment of the present application.

[0044] Figure 3 The figure is an average passing time improvement rate in an embodiment of the present application.

[0045] Figure 4 The figure is an average GINI coefficient improvement rate in an embodiment of the present application.

[0046] Figure 5 The figure is a schematic diagram of the smart connected vehicle speed calculation system considering the fairness of passing through a bottleneck area in an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the embodiments and drawings. Herein, the illustrative embodiments of the present application and their descriptions are used to explain the present application but not as a limitation of the present application.

[0048] It should be further noted that, in order not to obscure the present application due to unnecessary details, only the structures and / or processing steps closely related to the solutions according to the present application are shown in the drawings, and other details not closely related to the present application are omitted.

[0049] It should be emphasized that the term "comprise / comprising" as used herein is used to indicate the presence of a feature, element, step or component but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0050] It should be further noted that, if not specifically stated, the term "connected" as used herein can not only mean direct connection but also indirect connection in the presence of an intermediate.

[0051] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts or the same or similar steps.

[0052] Since the existing intelligent network connected driving technology has not fully covered the road network, the mixed flow composed of manual driving vehicles and intelligent network connected vehicles will exist for a long time, and the uncertainty of the moving behavior of manual driving vehicles will bring new challenges to the development of control measures. In order to solve this technical problem and improve the operation efficiency and safety of the entire control system, the present application provides a kind of intelligent network connected vehicle speed calculation method considering the passing fairness of bottleneck area, as shown in Figure 1 The method comprises the following steps S101-S104:

[0053] Step S101: set a statistical period, and count the traffic flow of the abnormal event point in the set historical period to the current time; determine the passing capacity of the bottleneck area formed by the abnormal event according to the traffic flow; set a flow limiting area and a speed coordination area on the upstream of the bottleneck area according to the scale of the abnormal event. One side of the speed coordination area is the bottleneck area, and the other side is the flow limiting area.

[0054] Step S102: count the vehicle moving information in the flow limiting area and the speed coordination area, calculate the average passing speed and traffic density of the vehicles in the flow limiting area, and calculate the average passing speed and traffic density of the vehicles in the speed coordination area.

[0055] Step S103: in the flow limiting area, the current traffic demand is calculated according to the average passing speed and traffic density of the vehicles in the flow limiting area, and the speed of the intelligent network connected vehicle is adjusted by comparing the size of the traffic demand and the passing capacity of the bottleneck area.

[0056] Step S104: in the speed coordination zone, when the number of queued vehicles in the lane where the abnormal event occurs reaches the preset number, the speed of the vehicle in the lane where the abnormal event occurs is compared with the speed of the vehicle in the adjacent lane, and the intelligent connected vehicle on the corresponding lane is decelerated according to the preset deceleration rule.

[0057] The application provides an intelligent connected vehicle speed calculation method considering the passing fairness of a bottleneck area, so as to match the inflow of the bottleneck area with the passing capacity thereof, build a flow limiting area and a speed coordination area upstream of the bottleneck, build an intelligent connected vehicle speed solving method, directly control the micro driving behavior of the intelligent connected vehicle, guide the movement of the manually driven vehicle, and improve the operation efficiency and safety of the whole system.

[0058] Specifically,

[0059] In step S101, a statistical period is preset, such as the past one hour or three hours, the traffic flow of the abnormal event point in the set historical period to the current time is counted by using a device such as a traffic detector, and is recorded to the corresponding traffic flow set respectively, and the change characteristics of the traffic flow near the bottleneck point after the incident are analyzed, so as to determine the passing capacity of the bottleneck area after the incident.

[0060] Further, according to the scale of the abnormal event, the propagation distance of the congestion wave is estimated, and the control area range is determined, the control area is set upstream of the bottleneck area, and the control area includes a functionally different flow limiting area and a speed coordination area, such as Figure 2 As shown in the figure, one side of the speed coordination area is the bottleneck area, and the other side is the flow limiting area, wherein the rounded rectangle represents a vehicle, the white filled rounded rectangle represents a manually driven vehicle, and the gray filled rounded rectangle represents an intelligent connected vehicle.

[0061] In step S102, the vehicle movement information in the control area is first counted.

[0062] In some embodiments, the vehicle movement trajectory in the set control area is captured by using a device such as a traffic detector, including the passing speed and position of the vehicle in different lanes in the flow limiting area and the speed coordination area, and the number of queued vehicles in the lane where the abnormal event occurs in the speed coordination area is counted.

[0063] According to the counted vehicle movement information, the average passing speed and the traffic density of the vehicle in the flow limiting area and the speed coordination area are calculated respectively.

[0064] In step S103, the application analyzes the traffic demand characteristics based on the traffic state in the flow limiting area after the abnormal event, so as to control the average passing speed of the vehicle in the flow limiting area, and further control the traffic flow flowing into the speed coordination area, so as to match the real-time passing capacity near the bottleneck.

[0065] In the flow restriction zone, according to the vehicle average speed and the traffic density calculated in step S102, the current traffic demand is calculated, and the calculation formula can be shown as formula (1):

[0066]

[0067] wherein, denotes the traffic demand of the flow restriction zone at time t; denotes the vehicle average speed of the flow restriction zone at time t; denotes the traffic density of the flow restriction zone at time t.

[0068] In order to match the real-time traffic demand with the passing capacity of the bottleneck, the relationship between the traffic demand and the passing capacity of the bottleneck is compared, if the traffic demand is greater than the passing capacity of the bottleneck, the flow restriction zone reduces the moving speed of the intelligent connected vehicle to reduce the traffic flow under the premise of ensuring safety; if the traffic demand is less than the passing capacity of the bottleneck, the flow restriction zone needs to increase the moving speed of the intelligent connected vehicle to reduce the traffic flow under the premise of ensuring safety; if the traffic demand is equal to the passing capacity of the bottleneck, the intelligent driving model (IDM) rule is used to update the vehicle speed.

[0069] In some embodiments, in the flow restriction zone, when determining the passing speed of the individual intelligent connected vehicle, first, the intelligent connected vehicle speed limit value of the flow restriction zone is calculated according to the passing capacity of the bottleneck zone and the traffic density of the flow restriction zone, and the calculation formula is shown as formula (2):

[0070]

[0071] wherein, denotes the intelligent connected vehicle speed limit value of the flow restriction zone at time t; denotes the passing capacity of the bottleneck zone at time t; denotes the traffic density of the flow restriction zone at time t.

[0072] Secondly, the speed of the intelligent connected vehicle is determined under the condition of ensuring safety.

[0073] In some embodiments, the speed of the intelligent connected vehicle is set with a safety constraint condition, wherein the constraint condition includes that the speed change rate of the vehicle itself in the flow restriction zone is less than the maximum acceleration and the vehicle maintains a safe distance from the front vehicle. The calculation method follows formulas (3)-(5):

[0074]

[0075] wherein, denotes the speed of vehicle i at time t; a max denotes the maximum acceleration; represents the position of vehicle i at time t; h min represents the minimum safe headway between vehicles; L represents the average vehicle length; Δt represents the time step; represents the acceleration of vehicle i at time t.

[0076] In some embodiments, when considering that the target vehicle maintains a safe distance from the preceding vehicle, when the preceding vehicle of the target intelligent connected vehicle is a manually driven vehicle, a microscopic traffic flow model is introduced to determine the acceleration, speed, and position of the manually driven vehicle, specifically in accordance with the following formulas (6) and (7):

[0077]

[0078] in, represents the acceleration of the manually driven car at time t; a max represents the maximum acceleration; u represents the free flow speed; represents the speed of the manually driven car at time t; Indicates the desired headway; represents the speed difference between the target intelligent connected vehicle and the preceding manually driven vehicle; s0 represents the safe headway; h min represents the expected headway; b represents the maximum deceleration.

[0079] Based on the above description, it can be seen that for intelligent connected vehicles in traffic-restricted areas, the actual travel speed is determined based on the speed limit value. If the safety conditions are not met, the vehicle passes at the critical speed that meets the safety conditions according to the above relationship.

[0080] In step S104, the present invention optimizes the microscopic trajectories of intelligent connected vehicles within the speed coordination zone, based on controlling vehicle speeds in the flow-restricted zone, to ensure smooth and safe passage through the bottleneck. In particular, vehicles in the lane where the abnormal event occurred must complete a forced lane change to pass through the bottleneck. When a vehicle fails to change lanes, a queue forms at the bottleneck. When vehicles accumulate at the bottleneck and frequently change lanes, this impacts the normal passage of vehicles in other lanes, creating a congestion wave that propagates upstream. Therefore, it is necessary to rationally optimize the microscopic driving behavior of intelligent connected vehicles within the speed coordination zone to coordinate the movement of each vehicle and improve overall traffic efficiency and fairness.

[0081] To reduce the number of vehicles changing lanes at bottlenecks, the speed of vehicles in the incident lane is coordinated with that of vehicles in adjacent lanes, improving fairness in traffic flow across different lanes. In this invention, when the number of vehicles queuing in the incident lane increases, the speed of intelligent connected driving vehicles in other lanes is coordinated to reduce the number of vehicles queuing.

[0082] For vehicles in different lanes, assuming that it is time t-1, the vehicle in the lane where the abnormal event occurs is vehicle i, and its speed is The vehicle in the adjacent lane is j, and its speed is Then, at the next moment, the update of the target vehicle speed follows:

[0083] The update rule for the target vehicle speed in the lane where the abnormal event occurs is:

[0084] When the speed of vehicle i in the lane where the abnormal event occurs is greater than the speed of vehicle j in the adjacent lane, vehicle i needs to decelerate to smoothly complete the mandatory lane change and find the right lane to change. The deceleration rule follows the following algorithm:

[0085] Calculate the first quotient of the speed difference between the two vehicles and the time step, and get The maximum deceleration is denoted as b. When , according to the safety constraints set above, it is determined whether vehicle i can pass safely at the maximum deceleration b. If the safety constraints cannot be met, the intelligent driving model (IDM) rule is used to update its speed; when When , according to the safety constraints set above, it is determined whether vehicle i can The vehicle decelerates to pass safely. If the safety constraints cannot be met, the intelligent driving model (IDM) rules are used to update its speed.

[0086] Update rules for the target vehicle speed in adjacent lanes:

[0087] When the speed of vehicle i in the lane where the abnormal event occurs is lower than that of vehicle j in the adjacent lane, and there is a queue of vehicles in the bottleneck area of ​​the lane where the abnormal event occurs due to lane change failures, vehicle j needs to slow down to increase the lane change success rate of vehicles in the lane where the abnormal event occurs. Similarly, the deceleration rule follows the following algorithm:

[0088] Calculate the first quotient of the speed difference between the two vehicles and the time step, and get The maximum deceleration is denoted as b. When , the speed of vehicle j is updated to the speed of vehicle i Otherwise, the intelligent driving model (IDM) rule is used to update its speed.

[0089] When the speed of the vehicle in the lane where the abnormal event occurs is equal to the speed of the vehicle in its adjacent lane, the intelligent driving model (IDM) rule is used to update its speed.

[0090] The present invention will be further described below with reference to a specific embodiment.

[0091] In order to verify the effectiveness of the intelligent networked driving vehicle speed calculation method proposed in the application, the intelligent networked vehicle and the artificial driving vehicle moving characteristics are integrated to construct a microscopic driving simulation system. In the scene without control, the vehicle following behavior of the intelligent networked vehicle and the artificial driving vehicle is described by using the IDM model, and the lane changing behavior is described by using the MOBIL vehicle lane changing model.

[0092] The MOBIL algorithm is shown in formula (8):

[0093]

[0094] wherein, represents the acceleration change amount of the target vehicle after lane changing; represents the acceleration change amount of the adjacent rear vehicle after lane changing of the target vehicle; represents the acceleration change amount of the adjacent rear vehicle before lane changing of the target vehicle; p is the courtesy; and Δa th is an acceleration threshold value for allowing lane changing to be performed, and when the acceleration increment satisfies the lane changing threshold value, lane changing is performed.

[0095] Simulation scene setting: taking a highway scene as an example, refer to Figure 2 , an abnormal event occurs in the outermost lane of the three lanes of the highway, an accident area with a length of 1 km is set, the flow limiting area (1 area) in the control area has a length of 500 meters, the speed coordination area (2 area) has a length of 1000 meters, the traffic demand is 3000 vehicles / hour for simulation vehicles moving in the first 5 minutes, and the simulation is performed at a constant speed of 4800 vehicles / hour, a total of 55 minutes of simulation is performed each time, and the data collected during the period of 5 minutes to 50 minutes of simulation is taken for comparison and analysis, and each simulation scene is independently run for 5 times.

[0096] In this embodiment, different intelligent networked driving vehicle ratios (Market Penetration Rates, MPR) are set, and the MPR values are 0.6, 0.7, 0.8 and 0.9.

[0097] In this embodiment, the vehicle passing efficiency and fairness are analyzed. The efficiency is measured by the average passing time of vehicles passing through a specified area upstream of the bottleneck, and the fairness is quantified by the classical index GINI coefficient.

[0098] Figure 3 and Figure 4 are the improvement rates of the vehicle average passing time and the average GINI coefficient after the method provided by the application is applied compared with the scene without control. As can be seen from the figure, the method provided by the application can effectively improve the vehicle passing efficiency and fairness in the bottleneck area in the specified scene.

[0099] The application also provides an intelligent networked vehicle speed calculation system considering the passing fairness of the bottleneck area, as shown inFigure 5 As shown, the system comprises:

[0100] The input layer is configured to count traffic information of a bottleneck area formed by an abnormal event, and set a flow restriction area and a speed coordination area upstream of the bottleneck area according to a size of the abnormal event, and count traffic information of the flow restriction area and the speed coordination area. Exemplarily, the traffic information of the bottleneck area comprises a traffic flow set, and the traffic information of the flow restriction area and the speed coordination area comprises average passing speed, traffic density and queue length of vehicles of each area.

[0101] The model layer is configured to calculate a speed of a target intelligent connected vehicle according to the traffic information of each area counted by the input layer, by using the intelligent connected vehicle speed calculation method considering passing fairness of a bottleneck area provided by the present application.

[0102] The output layer is configured to output the speed of the target intelligent connected vehicle calculated by the model layer.

[0103] Corresponding to the above method, the present application further provides an electronic device, which comprises a computer device, the computer device comprising a processor and a memory, the memory storing computer instructions, and the processor being configured to execute the computer instructions stored in the memory, so that the electronic device implements the steps of the above method.

[0104] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the above edge computing server deployment method. The computer readable storage medium can be a tangible storage medium, such as a random access memory (RAM), a memory, a read only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0105] Those skilled in the art should understand that the exemplary components, systems and methods described in connection with the embodiments disclosed herein can be implemented in hardware, software or a combination thereof. The actual implementation depends on the specific application and design constraints imposed on the overall system. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc. When implemented in software, the elements of the present application are program or code segments used to perform the required tasks. The program or code segments can be stored in a machine readable medium or transmitted through a data signal carried in a carrier wave in a transmission medium or communication link.

[0106] It is to be understood that the application is not limited to particular configurations and processes described herein and shown in the drawings, which can vary. For the sake of brevity and clarity, detailed descriptions of well-known methods and apparatuses will not be repeated. In the above embodiments, several specific steps are described and / or illustrated as examples. However, the method processes of the present application are not limited to the specific steps described and / or illustrated, and the order of the steps can be changed, and / or other steps can be added, and / or some steps can be omitted, without departing from the spirit of the application.

[0107] In the present application, features described and / or illustrated for one embodiment can be used in the same or a similar way for one or more other embodiments and / or combined with or substituted for features of other embodiments.

[0108] The above description is merely illustrative of the application, and is not intended to limit the scope of the application. Various modifications and changes can be made by persons of ordinary skill in the art to the application as described without departing from the spirit and scope of the application. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the application should be included in the protection scope of the application.

Claims

1. A method for calculating the speed of intelligent connected vehicles considering traffic fairness in bottleneck areas, characterized by: The method comprises the following steps: A statistical period is set to calculate the traffic flow of the abnormal event from the set historical period to the current moment; the traffic capacity of the bottleneck area formed by the abnormal event is determined based on the traffic flow; and a flow restriction area and a speed coordination area are set upstream of the bottleneck area based on the scale of the abnormal event; wherein one side of the speed coordination area is the bottleneck area, and the other side is the flow restriction area; Collecting vehicle movement information in the flow restriction area and the speed coordination area, calculating the average vehicle speed and traffic density in the flow restriction area, and calculating the average vehicle speed and traffic density in the speed coordination area; In the flow-restricted area, the current traffic demand is calculated based on the average vehicle speed and traffic density in the flow-restricted area, and the speed of the intelligent connected vehicle is adjusted by comparing the traffic demand with the traffic capacity of the bottleneck area. Wherein, in the flow-restricted area, when determining the speed of an individual intelligent connected vehicle, the method further includes: calculating the speed limit value of the intelligent connected vehicle in the flow-restricted area based on the traffic capacity of the bottleneck area and the traffic density of the flow-restricted area, and the calculation formula is: ； in, express The speed limit of the intelligent connected vehicle in the traffic restriction zone at that moment; express The traffic capacity of the bottleneck area at the time; express Traffic density in the traffic restriction area at the time; Safety constraints are set for the speed of the intelligent connected vehicle. The constraints include that the vehicle's own speed change rate is less than the maximum acceleration in the traffic restriction area and that the vehicle maintains a safe distance from the vehicle in front. The calculation formula is: ； ； ； in, express Time Vehicle speed; represents the maximum acceleration; express Time Vehicle location; Indicates the minimum safe headway between vehicles; Indicates the average vehicle body length; represents the time step; express Time Vehicle acceleration; In the speed coordination area, when the number of vehicles queuing in the lane where the abnormal event occurs reaches a preset number, the speed of the vehicle in the lane where the abnormal event occurs is compared with the speed of the vehicle in the adjacent lane, and the intelligent connected vehicle in the corresponding lane is decelerated according to the preset deceleration rule, including: when the speed of the vehicle in the lane where the abnormal event occurs is greater than the speed of the vehicle in the adjacent lane, calculating the first quotient of the speed difference between the two vehicles and the time step; when the first quotient is greater than the maximum deceleration, determining whether the vehicle in the lane where the abnormal event occurs can pass safely at the maximum deceleration; if the safety constraint condition cannot be met, adopting the intelligent driving model The intelligent driving model rules are used to update its speed; when the first quotient is not greater than the maximum deceleration, it is determined whether the vehicle in the lane where the abnormal event occurs can safely pass with the first quotient as the deceleration; if the safety constraint condition cannot be met, the intelligent driving model rules are used to update its speed; when the speed of the vehicle in the lane where the abnormal event occurs is less than the speed of the vehicle in its adjacent lane, a second quotient of the speed difference between the two vehicles and the time step is calculated; when the second quotient is less than the maximum deceleration, the speed of the vehicle in the adjacent lane is decelerated to the speed of the vehicle in the lane where the abnormal event occurs; otherwise, the intelligent driving model rules are used to update its speed.

2. The intelligent connected vehicle speed calculation method considering bottleneck area traffic fairness according to claim 1 is characterized in that: Collecting statistics on vehicle movement information in the flow restriction area and the speed coordination area includes: Traffic detectors are used to capture the vehicle movement trajectories in the flow restriction area and the speed coordination area, including the travel speeds and locations of vehicles in different lanes in the flow restriction area and the speed coordination area; and the number of vehicles queuing in the lane where the abnormal event is located in the speed coordination area is counted.

3. The intelligent connected vehicle speed calculation method considering bottleneck area traffic fairness according to claim 1 is characterized in that: In the traffic restriction area, the current traffic demand is calculated based on the average vehicle speed and traffic density in the traffic restriction area, wherein the calculation formula of the traffic demand is: ； in, express Traffic demand in the traffic restriction area at the time; express The average speed of vehicles passing through the traffic restriction area at the time; express The traffic density in the traffic restriction area at the moment.

4. The intelligent connected vehicle speed calculation method considering bottleneck area traffic fairness according to claim 1 is characterized in that: By comparing the traffic demand and the traffic capacity of the bottleneck area, the speed of the intelligent connected vehicle is adjusted, including: If the traffic demand is greater than the traffic capacity of the bottleneck area, reducing the speed of the intelligent connected vehicle; If the traffic demand is less than the traffic capacity of the bottleneck area, the speed of the intelligent connected vehicle is increased.

5. The intelligent connected vehicle speed calculation method considering bottleneck area traffic fairness according to claim 1 is characterized in that: When the vehicle maintains a safe distance from the vehicle ahead, the method further includes: When the preceding vehicle of the target intelligent connected vehicle is a manually driven vehicle, the manually driven vehicle follows the following formula: ； ； in, express The acceleration of the manually driven vehicle at the time; represents the maximum acceleration; represents the free flow speed; express The speed of the manually driven vehicle at the time; Indicates the desired headway; Indicates the speed difference between the target intelligent connected vehicle and the preceding manually driven vehicle; Indicates safe headway; Indicates the expected headway; Indicates the maximum deceleration.

6. A speed calculation system for intelligent connected vehicles that considers fairness in bottleneck area traffic, characterized by: The system comprises: The input layer is used to collect traffic information of the bottleneck area formed by the abnormal event, and to set a flow restriction area and a speed coordination area upstream of the bottleneck area according to the scale of the abnormal event, and to collect traffic information of the flow restriction area and the speed coordination area; a model layer, configured to calculate the speed of a target intelligent connected vehicle based on the traffic information obtained by the input layer and using the intelligent connected vehicle speed calculation method considering bottleneck area traffic fairness as described in any one of claims 1 to 5; The output layer is used to output the speed of the target intelligent connected vehicle calculated by the model layer.

7. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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