Heterogeneous traffic flow circulation method based on intelligent signal lamp system, storage medium and equipment

Abstract

The invention discloses a heterogeneous traffic flow traffic method based on an intelligent signal lamp system, a storage medium and equipment, and the method comprises the steps: obtaining the traffic flow of a heterogeneous traffic flow of a lane in a certain direction at an intersection through the intelligent signal lamp system, and obtaining the driving information of the heterogeneous traffic flow; for the intelligent network connection vehicle, determining the minimum safe distance between the intelligent network connection vehicle and the front vehicle, driving the intelligent network connection vehicle to the minimum safe distance, optimizing the starting speed of the intelligent network connection vehicle based on a dynamic speed planning algorithm, and obtaining the total delay time of all the intelligent network connection vehicles on the lane when the signal lamp is green; for the manually-driven vehicles, obtaining the total delay time of all the manually-driven vehicles on the lane when the signal lamp is green; according to the total delay time of all the vehicles on the lane, dynamically adjusting the duration of the green light of the signal lamp of the intelligent signal lamp system for the passage of heterogeneous traffic flows. According to the invention, efficient and coordinated passing of the intelligent network connection vehicle and the manual driving vehicle at the intersection is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management and control, and in particular to a method, storage medium and device for passing heterogeneous traffic in an intelligent signal light system. Background Art

[0002] With the gradual popularization of intelligent connected vehicles, the heterogeneous characteristics of traffic flow are becoming more and more obvious, that is, traditional manually driven vehicles coexist with intelligent connected vehicles with vehicle networking communication capabilities. Intelligent connected vehicles can share information such as location, speed, acceleration, etc. in real time through V2V and V2I communication technologies, and make collaborative decisions with other vehicles and infrastructure. Connected vehicles can predict the road conditions ahead and adjust the speed in advance, thereby reducing emergency braking and acceleration behaviors and reducing the propagation effect of congestion.

[0003] However, the existing traffic management system cannot fully utilize the network characteristics of intelligent connected vehicles and cannot achieve efficient coordinated management of heterogeneous vehicles at intersections, resulting in low intersection efficiency, increased traffic congestion and increased safety hazards. Therefore, there is an urgent need for a method that can identify, coordinate and optimize the traffic of the two types of vehicles in real time to improve overall traffic efficiency. Summary of the invention

[0004] In response to the problems existing in the prior art, the present invention provides a heterogeneous traffic flow method, storage medium and device based on an intelligent traffic light system, aiming to achieve efficient and coordinated passage of intelligent connected vehicles and manually driven vehicles at intersections through an intelligent traffic light system and a collaborative control strategy of intelligent connected vehicles and manually driven vehicles.

[0005] To achieve the above technical objectives, the present invention adopts the following technical solution: a method for heterogeneous traffic flow based on an intelligent signal light system, specifically comprising the following steps:

[0006] Step S1, obtaining the traffic flow of heterogeneous traffic flow in a certain lane of an intersection through an intelligent traffic light system, and obtaining driving information of the heterogeneous traffic flow; the heterogeneous traffic flow includes: intelligent networked vehicles and manually driven vehicles;

[0007] Step S2: for an intelligent networked vehicle, determining a minimum safe distance between the intelligent networked vehicle and a preceding vehicle, and driving the intelligent networked vehicle to the minimum safe distance;

[0008] Step S3: Optimize the starting speed of the intelligent networked vehicles at the minimum safety distance based on the dynamic speed planning algorithm, and obtain the total delay time of all intelligent networked vehicles on the lane when the signal light of the intelligent signal light system is green;

[0009] Step S4: for manually driven vehicles, the total delay time of all manually driven vehicles on the lane when the signal light of the intelligent traffic light system is green is obtained;

[0010] Step S5: dynamically adjust the duration of the green light of the intelligent traffic light system according to the total delay time of all intelligent connected vehicles and the total delay time of all manually driven vehicles on the lane, so as to facilitate the passage of heterogeneous traffic flows.

[0011] Furthermore, step S1 includes the following sub-steps:

[0012] Step S1.1, the intelligent traffic light system measures the driving speed of each vehicle and the distance between adjacent vehicles through sound wave reflection as the driving information of the heterogeneous traffic flow;

[0013] Step S1.2: The intelligent traffic light system identifies the intelligent connected vehicles through the V2X communication equipment, and the other unidentified vehicles are manually driven vehicles, and the traffic flow of the intelligent connected vehicles and manually driven vehicles is obtained.

[0014] Furthermore, the minimum safe distance d between the intelligent connected vehicle and the preceding vehicle in step S2 is safe The calculation process is:

[0015]

[0016] Among them, v CAV (t) represents the driving speed of the intelligent connected vehicle, t r represents the reaction time of the intelligent connected vehicle, a CAV (t) represents the maximum deceleration of the intelligent connected vehicle.

[0017] Furthermore, the optimization process of the startup speed of the intelligent connected vehicle is as follows:

[0018]

[0019] Among them, v opt (t) represents the optimized startup speed of the intelligent connected vehicle, and α represents a CAV (t) weight coefficient, β represents d safe The weight coefficient, γ represents v CAV The weight coefficient of (t), T represents the starting time of the intelligent connected vehicle.

[0020] Furthermore, the total delay time T of all intelligent connected vehicles on the lane in step S3 is CAV The calculation process is:

[0021]

[0022] Among them, λCAV (t) represents the traffic flow of intelligent connected vehicles on a certain lane of the intersection.

[0023] Furthermore, the total delay time T of all manually driven vehicles on the lane in step S4 is HDV The calculation process is:

[0024] T HDV =T HDV,末

[0025] Among them, T HDV,末 Indicates the delay time of the last manually driven vehicle in a certain lane of an intersection.

[0026] Furthermore, the adjustment process of the duration of the green light of the signal light of the intelligent signal light system is as follows:

[0027]

[0028] Among them, T green is the duration of the green light of the intelligent traffic light system, C is the total signal cycle of the traffic light of the intelligent traffic light system, α is the dynamically adjusted weight coefficient,

[0029] Furthermore, if the number of lanes in a certain direction of the intersection is more than 3, lanes are allocated to intelligent networked vehicles and manually driven vehicles during peak hours, and the intelligent signal light system reminds intelligent networked vehicles and manually driven vehicles to switch lanes accordingly through electronic signs, signal lights and lane change indication devices;

[0030] The specific process of lane allocation is as follows:

[0031]

[0032] Among them, N CAV represents the number of lanes allocated to intelligent connected vehicles, Indicates rounding down; N HDV represents the number of lanes allocated to human-driven vehicles, Indicates rounding up, N a represents the number of lanes in a certain direction at the intersection, λ CAV represents the traffic flow of intelligent connected vehicles in a certain lane of the intersection at the peak time, λ HDV It represents the traffic flow of manually driven vehicles in a certain lane of an intersection during peak hours.

[0033] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the heterogeneous traffic flow travel method based on the intelligent signal light system.

[0034] Furthermore, the present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the heterogeneous traffic flow method based on the intelligent traffic light system is implemented.

[0035] Compared with the prior art, the present invention has the following beneficial effects: the heterogeneous traffic flow passage method based on the intelligent signal light system of the present invention is to better optimize the traffic efficiency of the intersection. By analyzing the delay time of the heterogeneous traffic flow when the signal light of the intelligent signal light system is green, and optimizing the delay time of the intelligent connected vehicle based on the safe distance and the optimized starting speed, it can start quickly at the green light and pass through the intersection in the best acceleration mode, while closely following the convoy with a dynamically adjusted minimum spacing under the premise of ensuring safety. This optimization method significantly reduces the time waste caused by fixed start delay in traditional signal control technology, avoids the loss of traffic efficiency under the traditional "fixed safety distance" strategy, shortens the distance between intelligent connected vehicles when waiting, and greatly increases the number of passing vehicles per unit time, effectively improving the intersection. Traffic efficiency; at the same time, the present invention also adjusts the green light duration based on the delay time. By real-time collection and analysis of the delay time of vehicles in heterogeneous traffic flows, the green light duration is dynamically adjusted to make the green light duration more in line with the actual needs of the current traffic status. When the traffic pressure in a certain direction of the intersection is relatively large, extending the green light time can effectively reduce vehicle detention and improve traffic capacity; when the traffic pressure is relatively small, shortening the green light time can avoid wasting the green light period. This method can maximize the use of traffic resources at the intersection and achieve more efficient traffic diversion; in addition, the present invention also allocates lanes for intelligent connected vehicles and manually driven vehicles according to the number of lanes in a certain direction of the intersection. By allocating lane resources, the delay of the intelligent connected vehicle fleet is significantly reduced. At the same time, more smooth traffic conditions are provided for manually driven vehicles, avoiding the bottleneck effect caused by resource conflicts. Finally, the average delay of vehicles at the entire intersection is minimized and traffic efficiency is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The figure is a flow chart of a heterogeneous traffic flow passing method based on an intelligent signal light system according to the present invention. DETAILED DESCRIPTION

[0037] The technical solution of the present invention is further explained below in conjunction with the accompanying drawings.

[0038] like Figure 1 The flowchart of the heterogeneous traffic flow passing method based on the intelligent signal light system of the present invention is as follows:

[0039] Step S1: obtaining the traffic flow of heterogeneous traffic flow in a certain lane of an intersection through an intelligent traffic light system, wherein the heterogeneous traffic flow includes: intelligent networked vehicles and manually driven vehicles; and obtaining driving information of the heterogeneous traffic flow; specifically,

[0040] Step S1.1, the intelligent traffic light system measures the driving speed of each vehicle and the distance between adjacent vehicles through sound wave reflection as the driving information of the heterogeneous traffic flow;

[0041] Step S1.2: The intelligent traffic light system identifies the intelligent connected vehicles through the V2X communication equipment, and the other unidentified vehicles are manually driven vehicles, and the traffic flow of the intelligent connected vehicles and manually driven vehicles is obtained.

[0042] Step S2: For intelligent connected vehicles, determine the minimum safe distance between the intelligent connected vehicle and the vehicle in front, and drive the intelligent connected vehicle to the minimum safe distance. The intelligent connected vehicle transmits the acceleration or deceleration intention of the vehicle in front through the V2V technology of the Internet of Vehicles, thereby dynamically adjusting the safe distance of the intelligent connected vehicle, making the fleet more compact and improving road traffic efficiency.

[0043] The minimum safe distance d between the intelligent networked vehicle and the vehicle ahead in the present invention safe The calculation process is:

[0044]

[0045] Among them, v CAV (t) represents the driving speed of the intelligent connected vehicle, t r represents the reaction time of the intelligent connected vehicle, a CAV (t) represents the maximum deceleration of the intelligent connected vehicle, which is used to ensure safe parking in an emergency.

[0046] Step S3: Optimize the starting speed of the intelligent connected vehicle at the minimum safety distance based on the dynamic speed planning algorithm, so as to maximize the traffic efficiency of the intelligent connected vehicle under the premise of a safe distance, and minimize energy consumption by reducing the frequent changes in the acceleration of the intelligent connected vehicle, thereby maintaining a high traffic efficiency.

[0047] The optimization process of the startup speed of the intelligent networked vehicle in the present invention is:

[0048]

[0049] Among them, v opt (t) represents the optimized startup speed of the intelligent connected vehicle, and α represents a CAV (t) weight coefficient, β represents d safe The weight coefficient, γ represents v CAVThe weight coefficient of (t) is used, where T represents the start-up time of the intelligent connected vehicle. By adjusting the weight γ, the traffic efficiency and driving comfort of the intelligent connected vehicle at low speed are balanced, ensuring that the intelligent connected vehicle maintains an efficient speed in the intersection while complying with the safety distance requirements to reduce potential collision risks.

[0050] At the same time, according to the optimized startup speed of the intelligent connected vehicles, the total delay time of all intelligent connected vehicles on the lane when the signal light of the intelligent signal light system is green is obtained. The total delay time T of all intelligent connected vehicles on the lane is CAV The calculation process is:

[0051]

[0052] Among them, λ CAV (t) represents the traffic flow of intelligent connected vehicles on a certain lane of the intersection.

[0053] Step S4: For manually driven vehicles, obtain the total delay time T of all manually driven vehicles on the lane when the signal light of the intelligent traffic light system is green. HDV , the specific calculation process is:

[0054] T HDV =T HDV,末

[0055] Among them, T HDV,末 Indicates the delay time of the last manually driven vehicle in a certain lane of an intersection.

[0056] Step S5: dynamically adjust the green light duration of the intelligent traffic light system according to the total delay time of all intelligent connected vehicles and the total delay time of all manually driven vehicles on the lane, so as to facilitate the passage of heterogeneous traffic flows. By dynamically adjusting the weight coefficient to balance the passage needs of intelligent connected vehicles and manually driven vehicles, the green light duration of the traffic lights at the intersection can be flexibly adjusted to cope with real-time traffic flow changes, thereby improving traffic efficiency.

[0057] The process of adjusting the duration of the green light of the signal light of the intelligent signal light system of the present invention is as follows:

[0058]

[0059] Among them, T green is the duration of the green light of the intelligent traffic light system, C is the total signal cycle of the traffic light of the intelligent traffic light system, α is the dynamically adjusted weight coefficient, If the delay time of manually driven vehicles is longer, the weight coefficient α will increase, so that the green light time will be allocated more to manually driven vehicles; conversely, if the delay time of intelligent connected vehicles is longer, α will decrease, thereby giving priority to allocating green light time to intelligent connected vehicles.

[0060] In one technical solution of the present invention, if the number of lanes in a certain direction at an intersection is more than 3, in order to improve traffic efficiency, lanes are allocated to intelligent connected vehicles and manually driven vehicles during peak hours, which can reduce mutual interference between different types of vehicles, so that intelligent connected vehicles can use their collaborative driving capabilities to pass more efficiently, while manually driven vehicles can also maintain normal driving behavior in independent lanes. The intelligent traffic light system reminds intelligent connected vehicles and manually driven vehicles to make corresponding lane switches through electronic signs, signal lights and lane change indication devices.

[0061] The specific process of lane allocation is as follows:

[0062]

[0063] Among them, N CAV represents the number of lanes allocated to intelligent connected vehicles, Indicates rounding down; N HDV represents the number of lanes allocated to human-driven vehicles, Indicates rounding up, N a represents the number of lanes in a certain direction at the intersection, λ CAV represents the traffic flow of intelligent connected vehicles in a certain lane of the intersection at the peak time, λ HDV It represents the traffic flow of manually driven vehicles in a certain lane of an intersection during peak hours.

[0064] After lane allocation, the intelligent connected vehicles are optimized through the scheduling of the virtual fleet. The intelligent connected vehicles travel in coordination through V2V communication to form a virtual fleet. The speed of the intelligent connected vehicles in the virtual fleet remains consistent, reducing the speed fluctuation of each vehicle in the fleet, reducing startup delays, and shortening waiting time at intersections, thereby increasing the number of intelligent connected vehicles passing through per unit time and reducing the occurrence of traffic congestion.

[0065] In a technical solution of the present invention, a computer-readable storage medium is further provided, storing a computer program, wherein the computer program enables a computer to execute the heterogeneous traffic flow travel method based on the intelligent signal light system.

[0066] In a technical solution of the present invention, an electronic device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the heterogeneous traffic flow method based on the intelligent traffic light system is implemented.

[0067] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0068] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0069] The above are only preferred embodiments of the present invention, and 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.

Claims

1. A method for heterogeneous traffic flow based on an intelligent signal light system, characterized in that: The specific steps include: Step S1, obtaining the traffic flow of heterogeneous traffic flow in a certain lane of an intersection through an intelligent traffic light system, and obtaining driving information of the heterogeneous traffic flow; the heterogeneous traffic flow includes: intelligent networked vehicles and manually driven vehicles; Step S2: for an intelligent networked vehicle, determining a minimum safe distance between the intelligent networked vehicle and a preceding vehicle, and driving the intelligent networked vehicle to the minimum safe distance; Step S3: Optimize the starting speed of the intelligent networked vehicles at the minimum safety distance based on the dynamic speed planning algorithm, and obtain the total delay time of all intelligent networked vehicles on the lane when the signal light of the intelligent signal light system is green; Step S4: for manually driven vehicles, the total delay time of all manually driven vehicles on the lane when the signal light of the intelligent traffic light system is green is obtained; Step S5: dynamically adjust the duration of the green light of the intelligent traffic light system according to the total delay time of all intelligent connected vehicles and the total delay time of all manually driven vehicles on the lane, so as to facilitate the passage of heterogeneous traffic flows.

2. The method for heterogeneous traffic flow based on intelligent signal light system according to claim 1, characterized in that: Step S1 includes the following sub-steps: Step S1.1, the intelligent traffic light system measures the driving speed of each vehicle and the distance between adjacent vehicles through sound wave reflection as the driving information of the heterogeneous traffic flow; Step S1.2: The intelligent traffic light system identifies the intelligent connected vehicles through the V2X communication equipment, and the other unidentified vehicles are manually driven vehicles, and the traffic flow of the intelligent connected vehicles and manually driven vehicles is obtained.

3. The method for heterogeneous traffic flow based on intelligent signal light system according to claim 1, characterized in that: The minimum safe distance d between the intelligent connected vehicle and the vehicle ahead in step S2 safe The calculation process is: Among them, v CAV (t) represents the driving speed of the intelligent connected vehicle, t r represents the reaction time of the intelligent connected vehicle, a CAV (t) represents the maximum deceleration of the intelligent connected vehicle.

4. The method for heterogeneous traffic flow based on intelligent signal light system according to claim 3 is characterized in that: The optimization process of the startup speed of the intelligent connected vehicle is as follows: Among them, v opt (t) represents the optimized startup speed of the intelligent connected vehicle, and α represents a CAV (t) weight coefficient, β represents d safe The weight coefficient, γ represents v CAV The weight coefficient of (t), T represents the starting time of the intelligent connected vehicle.

5. The method for controlling heterogeneous traffic flow based on an intelligent signal light system according to claim 4, characterized in that: The total delay time T of all intelligent connected vehicles on the lane in step S3 CAV The calculation process is: Among them, λ CAV (t) represents the traffic flow of intelligent connected vehicles on a certain lane of the intersection.

6. The method for heterogeneous traffic flow based on intelligent signal light system according to claim 5, characterized in that: The total delay time T of all manually driven vehicles on the lane in step S4 HDV The calculation process is: T HDV =T HDV,末 Among them, T HDV,末 Indicates the delay time of the last manually driven vehicle in a certain lane of an intersection.

7. The method for heterogeneous traffic flow based on intelligent signal light system according to claim 6, characterized in that: The adjustment process of the duration of the green light of the intelligent traffic light system is as follows: Among them, T green is the duration of the green light of the intelligent traffic light system, C is the total signal cycle of the traffic light of the intelligent traffic light system, α is the dynamically adjusted weight coefficient, 8. The method for heterogeneous traffic flow based on intelligent signal light system according to claim 7, characterized in that: If the number of lanes in a certain direction of the intersection is more than 3, lanes will be allocated to intelligent connected vehicles and manually driven vehicles during peak hours. The intelligent signal light system will remind intelligent connected vehicles and manually driven vehicles to switch lanes accordingly through electronic signs, signal lights and lane change indication devices; The specific process of lane allocation is as follows: Among them, N CAV represents the number of lanes allocated to intelligent connected vehicles, Indicates rounding down; N HDV represents the number of lanes allocated to human-driven vehicles, Indicates rounding up, N a represents the number of lanes in a certain direction at the intersection, λ CAV represents the traffic flow of intelligent connected vehicles in a certain lane of the intersection at the peak time, λ HDV It represents the traffic flow of manually driven vehicles in a certain lane of an intersection during peak hours.

9. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the heterogeneous traffic flow travel method based on the intelligent signal light system as described in any one of claims 1 to 8.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for heterogeneous traffic flow based on the intelligent signal light system as described in any one of claims 1 to 8 is implemented.

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