Intelligent induction method and system for toll station

Abstract

The invention provides an intelligent induction method and system for a toll station. The method comprises the steps that a sensing node layer arranged in an entrance area of the toll station senses vehicle position information and sends the vehicle position information to a roadside control unit; the roadside control unit receives the vehicle position information sent by the intelligent spikes, carries out edge calculation to obtain the vehicle queuing length, and uploads the queuing information to the central control system; the central control system layer receives the queuing information sent by the roadside control unit layer, formulates an induction scheme, and issues a vehicle induction scheme instruction to a roadside control unit; the road side control unit layer receives a vehicle guidance scheme instruction issued by the central control system layer and sends the instruction to the sensing node layer; and the sensing node layer receives and executes the vehicle guidance scheme instruction sent by the roadside control unit layer. According to the toll station intelligent guidance method provided by the invention, the traffic optimization management of the toll station area can be realized by sensing the vehicle queuing condition in real time and dynamically adjusting the lane configuration, the vehicle congestion is reduced, and the traffic efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management and intelligent toll collection, and in particular to a method and system for intelligent induction of toll stations. Background Art

[0002] The current configuration of manual toll lanes and ETC lanes at toll stations is fixed and cannot be adjusted dynamically according to the actual traffic flow. As a result, the manual toll lanes are prone to long queues during peak hours, while the ETC lanes are not fully utilized, resulting in a waste of resources. The traditional guidance system based on video surveillance has detection delays and requires a lot of manual intervention, making it difficult to cope with sudden traffic changes. Therefore, there is an urgent need for an intelligent guidance system for toll stations that responds in real time and adjusts efficiently to adapt to traffic changes and improve vehicle traffic efficiency. Summary of the invention

[0003] The main purpose of the present invention is to overcome the above-mentioned defects in the prior art and to propose a smart induction method for toll stations. The method can achieve effective monitoring of vehicle queues at toll stations and flexible lane configuration through precise perception, real-time analysis, and dynamic induction; while reducing congestion and improving traffic efficiency, it reduces dependence on manual operations and provides a reliable solution for the intelligent management of toll stations.

[0004] The present invention adopts the following technical solution:

[0005] A toll booth intelligent induction method, comprising the following steps:

[0006] The sensing node layer deployed at the entrance area of ​​the toll station senses the vehicle location information and sends it to the roadside control unit;

[0007] The roadside control unit receives the vehicle location information sent by the smart road studs, performs edge computing, obtains the length of the vehicle queue, and uploads the queue information to the central control system;

[0008] The central control system layer receives the queuing information sent by the roadside control unit layer, formulates an induction plan, and issues vehicle induction plan instructions to the roadside control unit;

[0009] The roadside control unit layer receives the vehicle guidance scheme instructions issued by the central control system layer and sends them to the perception node layer;

[0010] The perception node layer receives and executes the vehicle induction scheme instructions sent by the roadside control unit layer.

[0011] Specifically, the sensing node layer deployed at the entrance area of ​​the toll station is as follows:

[0012] In the toll station entrance area, from 105 meters away from the toll station to the entrance, a smart road spike is installed every 15 meters and arranged along each lane line.

[0013] Specifically, the roadside control unit receives the vehicle position information sent by the smart road studs, performs edge computing, obtains the length of the vehicle queue, and uploads the queue information to the central control system. The queue length calculation formula is as follows:

[0014] The queue length L of vehicles can be expressed as:

[0015] L=(N-1)*d+l v

[0016] Where N is the number of consecutive road spikes, d is the spacing between each intelligent road spike, and lv is the length of the last vehicle.

[0017] Specifically, the central control system layer receives the queuing information sent by the roadside control unit layer and formulates an induction plan, which is as follows:

[0018] Default configuration: When the queue length L of the manual toll lane is less than 50 meters, the current lane configuration is maintained;

[0019] 50-meter guidance scheme: When the queue length of the manual toll lane is 50≤L<100 meters, one ETC lane is activated as a temporary manual toll lane, and the guidance spike array 50 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change;

[0020] 100-meter induction scheme: When the queue length L of the manual toll lane is ≥ 100 meters, two ETC lanes are enabled as temporary manual toll lanes, and the induction spike array 100 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change.

[0021] The embodiment of the present invention also provides a toll station intelligent guidance system, including: a perception node layer, a roadside control unit layer and a central control system layer;

[0022] Perception node layer: including intelligent road studs deployed at the entrance area of ​​the toll station and arranged along each lane line. The intelligent road studs send the sensed vehicle position information to the roadside control unit; and receive and execute the vehicle induction plan instructions sent by the roadside control unit layer;

[0023] Roadside control unit layer: includes edge servers set up on the roadside, which receive vehicle location information sent by smart road studs, perform edge computing, calculate the length of vehicle queues, and upload the queue information to the central control system; receive vehicle induction program instructions issued by the central control system layer and send them to the perception node layer;

[0024] Central control system layer: receives queuing information sent by the roadside control unit layer, formulates induction plans, and issues vehicle induction plan instructions to the roadside control unit.

[0025] Specifically, the smart road studs installed at the entrance area of ​​the toll station are:

[0026] In the toll station entrance area, from 105 meters away from the toll station to the entrance, a smart road spike is installed every 15 meters and arranged along each lane line.

[0027] Specifically, the vehicle position information sent by the smart road studs is received, edge computing is performed, the length of the vehicle queue is obtained, and the queue information is uploaded to the central control system. The queue length calculation formula is as follows:

[0028] The queue length L of vehicles can be expressed as:

[0029] L=(N-1)*d+l v

[0030] Where N is the number of consecutive road spikes, d is the spacing between each intelligent road spike, and lv is the length of the last vehicle.

[0031] Specifically, the queuing information sent by the roadside control unit layer is received and an induction plan is formulated, which is as follows:

[0032] Default configuration: When the queue length L of the manual toll lane is less than 50 meters, the current lane configuration is maintained;

[0033] 50-meter guidance scheme: When the queue length of the manual toll lane is 50≤L<100 meters, one ETC lane is activated as a temporary manual toll lane, and the guidance spike array 50 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change;

[0034] 100-meter induction scheme: When the queue length L of the manual toll lane is ≥ 100 meters, two ETC lanes are enabled as temporary manual toll lanes, and the induction spike array 100 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change.

[0035] On the other hand, the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of a toll booth intelligent induction method when executing the computer program.

[0036] Yet another aspect of the present invention provides a computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, a method step of intelligent induction at a toll booth is implemented.

[0037] It can be seen from the above description of the present invention that, compared with the prior art, the present invention has the following beneficial effects:

[0038] 1) The present invention proposes a smart induction method for toll stations, comprising the following steps: the sensing node layer arranged in the entrance area of ​​the toll station senses the vehicle position information and sends it to the roadside control unit; the roadside control unit receives the vehicle position information sent by the intelligent road studs, performs edge calculation, obtains the length of the vehicle queue, and uploads the queue information to the central control system; the central control system layer receives the queue information sent by the roadside control unit layer, formulates an induction plan, and issues a vehicle induction plan instruction to the roadside control unit; the roadside control unit layer receives the vehicle induction plan instruction issued by the central control system layer and sends it to the sensing node layer; the sensing node layer receives the vehicle induction plan instruction sent by the roadside control unit layer and executes it. The present invention proposes a smart induction method for toll stations, which can achieve traffic optimization management in the toll station area, reduce vehicle congestion, and improve traffic efficiency by sensing the vehicle queue situation in real time and dynamically adjusting the lane configuration.

[0039] 2) The present invention can realize efficient edge computing. Through the edge computing function of the roadside unit, the system can quickly process vehicle queuing information and make corresponding induced decisions, reducing the delay problem caused by AI video detection.

[0040] 3) The present invention can automatically adjust lanes and induction signals according to real-time changes in vehicle queues, reducing manual intervention and ensuring the smooth operation of toll stations.

[0041] 4) The present invention enables the ETC lane as a temporary manual toll lane when the queue length reaches a threshold, effectively utilizing resources and alleviating the pressure on the manual toll lane. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flow chart of a toll station intelligent induction method provided by an embodiment of the present invention;

[0043] Figure 2 A structural diagram of a toll station intelligent guidance system provided by an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention;

[0045] Figure 4 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The present invention is further described below through specific implementation modes.

[0047] The present invention proposes a smart induction method for toll stations, which can achieve effective monitoring of vehicle queues at toll stations and flexible lane configuration through precise perception, real-time analysis, and dynamic induction; while reducing congestion and improving traffic efficiency, it reduces reliance on manual operations and provides a reliable solution for the intelligent management of toll stations.

[0048] like Figure 1 The present invention provides a toll station intelligent induction method, which specifically comprises the following steps:

[0049] A toll booth intelligent induction method, comprising the following steps:

[0050] S101: The sensing node layer deployed at the entrance area of ​​the toll station senses the vehicle position information and sends it to the roadside control unit;

[0051] Specifically, the sensing node layer deployed at the entrance area of ​​the toll station is as follows:

[0052] In the toll station entrance area, from 105 meters away from the toll station to the entrance, a smart road spike is installed every 15 meters and arranged along each lane line.

[0053] Smart road studs are a type of intelligent traffic equipment based on Internet of Things technology. Their working principle is to collect road information, vehicle information, and traffic flow information in real time through built-in sensors and GPS positioning systems, and transmit the data to the server for processing and analysis.

[0054] The laying range is from 105 meters to the entrance of the toll station, which is obtained based on the historical vehicle queue information. The laying spacing of the smart road studs is one every 15 meters, which is set based on comprehensive considerations of vehicle length, vehicle spacing and the perception range of the smart road studs.

[0055] S102: The roadside control unit receives the vehicle position information sent by the intelligent road studs, performs edge computing, obtains the length of the vehicle queue, and uploads the queue information to the central control system;

[0056] Most existing systems are based on the architecture of smart road spikes and central servers. The architecture of the solution of the present invention is based on smart road spikes, edge servers and central control systems. It uses the principle of distribution to reduce the computing pressure of the central server and facilitates precise control.

[0057] Specifically, the roadside control unit receives the vehicle position information sent by the smart road studs, performs edge computing, obtains the length of the vehicle queue, and uploads the queue information to the central control system. The queue length calculation formula is as follows:

[0058] Assume that the layout interval of each intelligent road stud is d meters. In the embodiment of the present invention, d=15 meters. If on a certain lane line, N road studs sense that vehicles are queued in a certain direction of the lane line (always on the left (indicating that there is always a vehicle in the lane to the left of this lane line) or always on the right) (i.e., N consecutive road studs detect the presence of vehicles in a certain lane), the queue length L of the vehicles can be expressed as:

[0059] L=(N-1)*d+l v

[0060] Where N is the number of consecutive road spikes, d is the spacing between each intelligent road spike, and lv is the length of the last vehicle, which is usually about 4.5 meters.

[0061] S103: The central control system layer receives the queuing information sent by the roadside control unit layer, formulates an induction plan, and issues a vehicle induction plan instruction to the roadside control unit;

[0062] Specifically, the central control system layer receives the queuing information sent by the roadside control unit layer and formulates an induction plan, which is as follows:

[0063] Default configuration: When the queue length L of the manual toll lane is less than 50 meters, the current lane configuration is maintained;

[0064] 50-meter guidance scheme: When the queue length of the manual toll lane is 50≤L<100 meters, one ETC lane is activated as a temporary manual toll lane, and the guidance spike array 50 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change;

[0065] 100-meter induction scheme: When the queue length L of the manual toll lane is ≥ 100 meters, two ETC lanes are enabled as temporary manual toll lanes, and the induction spike array 100 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change.

[0066] During this process, the central control system dynamically adjusts the induction plan according to the changes in the real-time queue length, and controls the signal status of the road studs through the roadside unit to ensure the efficient operation of the toll station.

[0067] In addition, when the system is started, the road spike array enters standby mode, each lane works according to the default configuration, the ETC lane remains in electronic toll collection status, and the manual toll collection lane is open normally.

[0068] S104: The roadside control unit layer receives the vehicle induction scheme instruction issued by the central control system layer and sends it to the perception node layer;

[0069] S105: The perception node layer receives and executes the vehicle induction scheme instruction sent by the roadside control unit layer.

[0070] The intelligent road stud receives the vehicle guidance program instructions sent by the roadside control unit layer and starts to execute them. The intelligent road stud can keep lights on or flash lights of different colors, which can achieve vehicle guidance.

[0071] like Figure 2 The embodiment of the present invention further provides a system for intelligent guidance of toll booths, including:

[0072] The embodiment of the present invention further provides a toll station intelligent guidance system 200, comprising: a perception node layer 210, a roadside control unit layer 220 and a central control system layer 230;

[0073] Sensing node layer 210: includes intelligent road studs arranged at the entrance area of ​​the toll station and arranged along each lane line. The intelligent road studs send the sensed vehicle position information to the roadside control unit; and receive and execute the vehicle induction scheme instructions sent by the roadside control unit layer;

[0074] Specifically, the smart road studs installed at the entrance area of ​​the toll station are:

[0075] In the toll station entrance area, from 105 meters away from the toll station to the entrance, a smart road spike is installed every 15 meters and arranged along each lane line.

[0076] Smart road studs are a type of intelligent traffic equipment based on Internet of Things technology. Their working principle is to collect road information, vehicle information, and traffic flow information in real time through built-in sensors and GPS positioning systems, and transmit the data to the server for processing and analysis.

[0077] The laying range is from 105 meters to the entrance of the toll station, which is obtained based on the historical vehicle queue information. The laying spacing of the smart road studs is one every 15 meters, which is set based on comprehensive considerations of vehicle length, vehicle spacing and the perception range of the smart road studs.

[0078] Roadside control unit layer 220: includes edge servers set up on the roadside, receives vehicle location information sent by smart road studs, performs edge computing, obtains vehicle queue length, and uploads queue information to the central control system; receives vehicle induction scheme instructions issued by the central control system layer, and sends them to the perception node layer;

[0079] Most existing systems are based on the architecture of smart road spikes and central servers. The architecture of the solution of the present invention is based on smart road spikes, edge servers and central control systems. It uses the principle of distribution to reduce the computing pressure of the central server and facilitates precise control.

[0080] Specifically, the vehicle position information sent by the smart road studs is received, edge computing is performed, the length of the vehicle queue is obtained, and the queue information is uploaded to the central control system. The queue length calculation formula is as follows:

[0081] Assume that the spacing between each intelligent road stud is d meters. In the embodiment of the present invention, d=15 meters. If N road studs sense a queue of vehicles in a certain direction of a lane (always on the left (indicating that there is always a vehicle in the lane to the left of this lane) or always on the right) (i.e., N consecutive road studs detect the presence of vehicles in a certain lane), the queue length L of the vehicles can be expressed as:

[0082] L=(N-1)*d+l v

[0083] Where N is the number of consecutive road spikes, d is the spacing between each intelligent road spike, and lv is the length of the last vehicle.

[0084] The intelligent road stud receives the vehicle guidance program instructions sent by the roadside control unit layer and starts to execute them. The intelligent road stud can keep lights on or flash lights of different colors, which can achieve vehicle guidance.

[0085] Central control system layer 230: receives the queuing information sent by the roadside control unit layer, formulates an induction plan, and issues vehicle induction plan instructions to the roadside control unit.

[0086] Specifically, the queuing information sent by the roadside control unit layer is received and an induction plan is formulated, which is as follows:

[0087] Default configuration: When the queue length L of the manual toll lane is less than 50 meters, the current lane configuration is maintained;

[0088] 50-meter guidance scheme: When the queue length of the manual toll lane is 50≤L<100 meters, one ETC lane is activated as a temporary manual toll lane, and the guidance spike array 50 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change;

[0089] 100-meter induction scheme: When the queue length L of the manual toll lane is ≥ 100 meters, two ETC lanes are enabled as temporary manual toll lanes, and the induction spike array 100 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change.

[0090] During this process, the central control system dynamically adjusts the induction plan according to the changes in the real-time queue length, and controls the signal status of the road studs through the roadside unit to ensure the efficient operation of the toll station.

[0091] In addition, when the system is started, the road spike array enters standby mode, each lane works according to the default configuration, the ETC lane remains in electronic toll collection status, and the manual toll collection lane is open normally.

[0092] like Figure 3 As shown, an embodiment of the present invention provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, a toll station intelligent induction method provided by an embodiment of the present invention is implemented.

[0093] In the specific implementation process, when the processor 320 executes the computer program 311, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0094] Since the electronic device introduced in this embodiment is a device used to implement a data processing device in the embodiment of the present invention, based on the method introduced in the embodiment of the present invention, technical personnel in this field can understand the specific implementation method of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present invention is not introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present invention falls within the scope of protection of the present invention.

[0095] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention.

[0096] like Figure 4 As shown, this embodiment provides a computer-readable storage medium 400, on which a computer program 411 is stored. When the computer program 411 is executed by a processor, a toll station intelligent induction method provided by an embodiment of the present invention is implemented;

[0097] In a specific implementation process, when the computer program 411 is executed by a processor, Figure 1 Any implementation manner in the corresponding embodiments.

[0098] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] 1) The present invention proposes a smart induction method for toll stations, comprising the following steps: the sensing node layer arranged in the entrance area of ​​the toll station senses the vehicle position information and sends it to the roadside control unit; the roadside control unit receives the vehicle position information sent by the intelligent road studs, performs edge calculation, obtains the length of the vehicle queue, and uploads the queue information to the central control system; the central control system layer receives the queue information sent by the roadside control unit layer, formulates an induction plan, and issues a vehicle induction plan instruction to the roadside control unit; the roadside control unit layer receives the vehicle induction plan instruction issued by the central control system layer and sends it to the sensing node layer; the sensing node layer receives the vehicle induction plan instruction sent by the roadside control unit layer and executes it. The present invention proposes a smart induction method for toll stations, which can achieve traffic optimization management in the toll station area, reduce vehicle congestion, and improve traffic efficiency by sensing the vehicle queue situation in real time and dynamically adjusting the lane configuration.

[0101] 2) The present invention can realize efficient edge computing. Through the edge computing function of the roadside unit, the system can quickly process vehicle queuing information and make corresponding induced decisions, reducing the delay problem caused by AI video detection.

[0102] 3) The present invention can automatically adjust lanes and induction signals according to real-time changes in vehicle queues, reducing manual intervention and ensuring the smooth operation of toll stations.

[0103] 4) The present invention enables the ETC lane as a temporary manual toll lane when the queue length reaches a threshold, effectively utilizing resources and alleviating the pressure on the manual toll lane.

[0104] The above is only a specific implementation of the present invention, but the design concept of the present invention is not limited to this. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. A toll booth intelligent induction method, characterized in that: The steps include: The sensing node layer deployed at the entrance area of ​​the toll station senses the vehicle location information and sends it to the roadside control unit; The roadside control unit receives the vehicle location information sent by the smart road studs, performs edge computing, obtains the length of the vehicle queue, and uploads the queue information to the central control system; The central control system layer receives the queuing information sent by the roadside control unit layer, formulates an induction plan, and issues vehicle induction plan instructions to the roadside control unit; The roadside control unit layer receives the vehicle guidance scheme instructions issued by the central control system layer and sends them to the perception node layer; The perception node layer receives and executes the vehicle induction scheme instructions sent by the roadside control unit layer.

2. A toll station intelligent induction method according to claim 2, characterized in that: The sensing node layer deployed at the entrance area of ​​the toll station is as follows: In the toll station entrance area, from 105 meters away from the toll station to the entrance, a smart road spike is installed every 15 meters and arranged along each lane line.

3. A toll station intelligent induction method according to claim 2, characterized in that: The roadside control unit receives the vehicle location information sent by the smart road studs, performs edge computing, obtains the length of the vehicle queue, and uploads the queue information to the central control system. The queue length calculation formula is as follows: The queue length L of vehicles can be expressed as: L=(N-1)*d+l v Where N is the number of consecutive road spikes, d is the spacing between each intelligent road spike, and lv is the length of the last vehicle.

4. A toll station intelligent induction method according to claim 2, characterized in that: The central control system layer receives the queuing information sent by the roadside control unit layer and formulates an induction plan, which is as follows: Default configuration: When the queue length L of the manual toll lane is less than 50 meters, the current lane configuration is maintained; 50-meter guidance scheme: When the queue length of the manual toll lane is 50≤L<100 meters, one ETC lane is activated as a temporary manual toll lane, and the guidance spike array 50 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change; 100-meter induction scheme: When the queue length L of the manual toll lane is ≥ 100 meters, two ETC lanes are enabled as temporary manual toll lanes, and the induction spike array 100 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change.

5. A toll station intelligent guidance system, characterized in that: include: Perception node layer, roadside control unit layer and central control system layer; Perception node layer: including intelligent road studs deployed at the entrance area of ​​the toll station and arranged along each lane line. The intelligent road studs send the perceived vehicle position information to the roadside control unit; And receive and execute the vehicle induction scheme instructions sent by the roadside control unit layer; Roadside control unit layer: includes edge servers set up on the roadside, which receive vehicle location information sent by smart road studs, perform edge computing, calculate the length of vehicle queues, and upload the queue information to the central control system; receive vehicle induction program instructions issued by the central control system layer and send them to the perception node layer; Central control system layer: receives queuing information sent by the roadside control unit layer, formulates induction plans, and issues vehicle induction plan instructions to the roadside control unit.

6. The intelligent guidance system for toll booths according to claim 5 is characterized in that: The smart road studs installed at the entrance of the toll station are as follows: In the toll station entrance area, from 105 meters away from the toll station to the entrance, a smart road spike is installed every 15 meters and arranged along each lane line.

7. The intelligent guidance system for toll booths according to claim 5 is characterized in that: Receive the vehicle location information sent by the smart road studs, perform edge computing, obtain the length of the vehicle queue, and upload the queue information to the central control system. The queue length calculation formula is as follows: The queue length L of vehicles can be expressed as: L=(N-1)*d+l v Where N is the number of consecutive road spikes, d is the spacing between each intelligent road spike, and lv is the length of the last vehicle.

8. The intelligent induction method for toll booths according to claim 2 is characterized in that: Receive the queue information sent by the roadside control unit layer and formulate an induction plan, specifically: Default configuration: When the queue length L of the manual toll lane is less than 50 meters, the current lane configuration is maintained; 50-meter guidance scheme: When the queue length of the manual toll lane is 50≤L<100 meters, one ETC lane is activated as a temporary manual toll lane, and the guidance spike array 50 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change; 100-meter induction scheme: When the queue length L of the manual toll lane is ≥ 100 meters, two ETC lanes are enabled as temporary manual toll lanes, and the induction spike array 100 meters away is activated to guide the queued vehicles to the temporary manual toll lane for ETC lane change.

9. 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 the processor implements the method steps of any one of claims 1 to 4 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps of any one of claims 1 to 4 are implemented.

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