Intelligent network connection intersection emergency vehicle priority control method
By collecting vehicle information in the context of intelligent connected intersections, performing trajectory prediction and conflict separation, calculating the exposure time of emergency vehicles, and optimizing vehicle entry time and green light protection phase with the objective function of minimizing the average delay per vehicle at the intersection, the safety and efficiency issues of emergency vehicles at intersections are solved, and the safe and efficient passage of emergency vehicles is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-05
- Publication Date
- 2026-03-13
AI Technical Summary
In the context of intelligent connected intersections, existing emergency vehicle priority control methods are insufficient to ensure the absolute priority passage of emergency vehicles while minimizing the impact on the overall efficiency of other vehicles. Furthermore, they lack precise modeling and strict constraints on the continuous exposure of emergency vehicles to potential dangers in conflict zones.
By collecting vehicle information, performing trajectory prediction and conflict separation, calculating the exposure time of emergency vehicles when passing through intersections, and establishing an optimization model with the objective function of minimizing the average delay per vehicle at intersections, the settings of vehicle entry time and green light protection phase are optimized to achieve safe and efficient passage of emergency vehicles.
It achieves strict control over the safety risks of emergency vehicles at intersections and optimizes the overall efficiency of intersections, reduces delays for other vehicles, and provides a safer and more efficient control method.
Smart Images
Figure CN121661848A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of intelligent traffic control, specifically relating to a method for prioritizing emergency vehicles at intelligent connected intersections. Background Technology
[0002] With the rapid development of vehicle-to-infrastructure (V2I) and autonomous driving technologies, traditional signalized intersections are transforming into intelligent connected, signalless management models. In this model, autonomous vehicles (CAVs) can achieve seamless and efficient passage through intersections through real-time V2V and V2I communication and collaboration, a feat proven by numerous studies to significantly improve traffic capacity and reduce delays. However, emergency vehicles (ambulances, fire trucks, police cars, etc.) have absolute priority passage due to their emergency rescue and relief missions, and their delays and safety risks must be strictly controlled to a minimum. Therefore, in intelligent connected intersection scenarios, how to ensure the absolute priority and safe passage of emergency vehicles while minimizing the impact on the overall efficiency of other vehicles has become a critical technical challenge that urgently needs to be addressed. Existing methods for prioritizing emergency vehicle control are mainly divided into two categories: (1) Signal priority strategies for traditional manual driving environments provide time or space priority for emergency vehicles through methods such as pre-arrival detection, green light extension, and phase insertion. Such methods have been deployed in many cities at home and abroad, but they still rely on traffic lights in essence and cannot be directly transferred to unsignalized intelligent connected intersections; (2) Trajectory coordination and spatial priority strategies for autonomous driving environments mainly achieve priority passage by predicting the trajectory of emergency vehicles, clearing conflict areas in advance, or adjusting the trajectories of social vehicles. In recent years, studies have used methods such as gridded conflict separation, rolling temporal optimization (MPC), and multi-objective genetic algorithm (NSGA-II) to coordinate vehicle entry times, and have achieved good results in terms of delay, throughput, and fuel consumption. However, existing methods for prioritizing emergency vehicles at intelligent connected intersections still have the following shortcomings: (1) Most studies only take the minimization of emergency vehicle delays or travel time as a single objective, or simplify safety risks to discrete indicators such as the number of conflict points and TTC (Time-to-Collision), lacking precise modeling and strict constraints on the continuous and quantifiable risk indicator of "the time that emergency vehicles are continuously exposed to potential dangers in the conflict area". (2) In extreme cases (such as dense conflicts in multiple directions), some solutions can ensure the absolute safety of emergency vehicles by setting up a temporary "green light protection phase", but they do not include whether to activate the protection phase and the start and end times of the protection period in a unified optimization decision variable, resulting in a significant negative impact on the efficiency of social vehicles. (3) Existing methods mostly use heuristic rules, which makes it difficult to achieve a true Pareto optimal equilibrium between "zero risk exposure of emergency vehicles" and "minimum overall delay of social vehicles".
[0003] In view of this, there is an urgent need for a priority control method that can simultaneously achieve "quantifiable and strictly controlled risks" and "optimal overall intersection efficiency" for emergency vehicles in intelligent connected and unsignalized intersections. This invention proposes a novel optimization framework based on the aforementioned technical background. By introducing the core safety indicator of emergency vehicle "exposure time" and jointly optimizing it with the average delay of other vehicles, it provides a safer and more efficient technical path for prioritizing emergency vehicle passage at intelligent connected intersections. Summary of the Invention
[0004] This invention designs a priority control method for emergency vehicles at intelligent connected intersections. By collecting information such as the planned arrival time and travel path of vehicles arriving at the intersection, it performs advance trajectory prediction and conflict separation for all vehicles within the intersection. It calculates and constrains the time emergency vehicles are exposed to danger while passing through the intersection, and implements traffic control for autonomous vehicles in conflict directions. Using the minimum average vehicle delay at the intersection as the objective function, an optimization model is established to optimize the timing of vehicle entry into the intersection, whether a green light protection phase is set for emergency vehicles, and the start and end times of the green light, providing a safer and more efficient control method for intelligent connected intersections.
[0005] Technical Problem: In an intelligent connected environment, to ensure the efficient and safe passage of emergency vehicles at intersections, it is necessary to control the logic and sequence of autonomous vehicles entering the intersection, thereby guaranteeing priority passage for emergency vehicles. This invention provides a method for prioritizing emergency vehicle control at intelligent connected intersections. It considers the time emergency vehicles are exposed to danger while passing through the intersection, calculates the entry time of autonomous vehicles that needs to be controlled, and obtains the earliest time that emergency vehicles can enter the intersection while ensuring safety and efficiency. Technical Solution: To solve the above-mentioned technical problems, this invention proposes a method for prioritizing emergency vehicles at intelligent connected intersections, comprising the following steps:
[0006] Step 1: Collect vehicle information arriving at the intersection, including the planned arrival time of the vehicles, their travel routes, and the set of cars in conflicting directions with emergency vehicles; Step 2: Separate all vehicles within the intersection from potential hazards, calculate and constrain the time emergency vehicles are exposed to danger while passing through the intersection, and implement traffic control for cars in the conflicting directions of emergency vehicles. Step 3: Using the minimum average vehicle delay at the intersection as the objective function, establish an optimization model to optimize the timing of vehicle entry into the intersection, whether an emergency vehicle green light protection phase is set, and the start and end times of the green light. In this invention, in step 1, vehicle information arriving at the intersection is collected. Emergency vehicles are represented by ev, cars by a, and A represents the set of all cars arriving at the intersection; r i Let t represent the travel path of vehicle i. i Let K represent the planned arrival time of vehicle i at the intersection, where i ∈ ev ∪ A; ev The set of cars representing the directions of conflict between emergency vehicles, among which, In this invention, step 2 involves conflict separation of all vehicles within the intersection, calculating and constraining the time emergency vehicles are exposed to danger while passing through the intersection, and implementing traffic control for cars in conflicting directions of emergency vehicles. This includes the following steps: Step 21: Perform conflict separation on all vehicles inside the intersection, divide the space inside the intersection into several grids, and stipulate that no two vehicles can occupy the same grid at the same time, as shown in formula (1): In formula (1), G represents the set of all grids inside the intersection, g represents a single grid inside the intersection, g∈G, ev represents an emergency vehicle, a represents a car, and A represents the set of all cars arriving at the intersection; t i,g t f,g Let T represent the times when vehicles i and f enter grid g, respectively. i,g T f,g Indicates the time when vehicles i and f leave grid g; For two parameters, This indicates that vehicle i has passed through grid g; otherwise, It is also a binary parameter. This indicates that vehicle f has passed through grid g; otherwise, γ i,f For a binary variable, γ i,f =0 indicates that vehicle i has a priority over vehicle f; otherwise, γ = 0. i,f =1; when and When γ indicates that vehicles i and f pass through the same grid g, then if γ i,f =0, meaning that vehicle i's passage order is before vehicle f, then formula (1) is equivalent to T i,g -t f,g ≤0, meaning the time when vehicle f enters grid g must not be earlier than the time when vehicle i leaves grid g, if γ i,f=1, meaning that vehicle f's passage order is before vehicle i, then formula (1) is equivalent to T f,g -t i,g ≤0, meaning the time when vehicle i enters grid g must not be earlier than the time when vehicle f leaves grid g; when or When, it means that vehicles i and f do not pass through grid g at the same time, and there is no need to separate the two vehicles at grid g. At this time, formula (1) always holds. Step 22: To ensure the priority right-of-way for emergency vehicles at intelligent connected intersections, calculate the earliest time when emergency vehicles can enter the intersection; Let β be the earliest time when vehicle j can enter the intersection. j Assuming that all vehicles in the conflict direction yield to vehicle j, the earliest time that vehicle j can enter the intersection is only affected by the vehicle in front of it in the same approach lane, β. j The calculation method is shown in formula (2): In formula (2), t j Indicates the planned arrival time of vehicle j at the intersection; vehicle i represents the vehicle preceding vehicle j in the same entrance lane; l i Let v be the length of the vehicle in front (i). i Let β be the speed of the vehicle in front, i. i The earliest time that vehicle i can enter the intersection; r * This represents the driving trajectories of vehicles i and j inside the intersection. For two parameters, The vehicle's trajectory r * Press over the grid g, otherwise, This represents the set of grids crossed by the trajectories of vehicles i and j. This indicates the earliest time when the vehicle in front can cross the stop line, where l i v represents the body length of vehicle i. i This represents the speed of vehicle i. Let represent the time required for vehicle i to travel from entering the intersection to entering grid g. This indicates the earliest time that the preceding vehicle i can leave the grid g. This indicates the time required for vehicle j to travel from entering the intersection to entering grid g; To ensure emergency vehicles have the right-of-way at intersections, the time T when an emergency vehicle enters the intersection... ev It should satisfy formula (3): T ev =β ev (3) In formula (3), β evIndicates the earliest time that emergency vehicles can enter the intersection; Step 23: Calculate and constrain the time that emergency vehicles are exposed to danger when passing through intersections; K ev A group of cars representing the direction of conflict between emergency vehicles. Let k represent the car that collides with the emergency vehicle, where k∈K ev G ev,k Let g represent the set of conflict grids between the emergency vehicle and car k; for a conflict between the emergency vehicle and car k at grid g, calculate the exposure time TE of the emergency vehicle. ev,k,g That is, the time interval from when the emergency vehicle or the car k with the first passage order enters grid g to when it exits grid g, as shown in formula (4): In formula (4), γ ev,k Let γ be a binary variable representing the passage order between the emergency vehicle and the car k. ev,k =1 indicates that the passage order of car k is higher than that of emergency vehicles, γ ev,k =0 indicates that emergency vehicles have priority over cars (k); PET * Indicates the danger threshold, PET ev,k,g This represents the time difference between the emergency vehicle and the car k passing through the conflict grid g; when PET ev,k,g PET * At that time, there was no significant danger between the emergency vehicle and the car k at the conflict grid g. Therefore, for the conflict between the emergency vehicle and the car k at grid g, the exposure time TE of the emergency vehicle is... ev,k,g empty set When PET ev,k,g ≤PET * At that time, there is a significant danger between the emergency vehicle and the car k at the conflict grid g. If γ ev,k =0, meaning the emergency vehicle's passage order is first. Therefore, for a conflict between the emergency vehicle and the car k at grid g, the emergency vehicle's exposure time TE is... ev,k,g This equals the time interval from when the emergency vehicle enters grid g to when it exits grid g, i.e., [t] ev,g ,T ev,g If γ ev,k =1, meaning the car's passage order is first. Therefore, for a conflict between the emergency vehicle and car k at grid g, the emergency vehicle's exposure time TE is... ev,k,g This is equal to the time interval from when the car enters grid g to when it exits grid g, i.e., [t] k,g ,T k,g ]; According to formula (4), for the conflict between the emergency vehicle and the car k at each grid point, the exposure time of the emergency vehicle is calculated sequentially, i.e. Where g1, g2, g3…∈G ev,k Based on the above calculation results, for the conflict between the emergency vehicle and the car k, the exposure time period TE′ of the emergency vehicle is calculated. ev,k Take the union of the calculation results of emergency vehicle and car k at all conflict grids in formula (4), as shown in formula (5): According to formula (5), for each conflict between an emergency vehicle and a car, the exposure time of the emergency vehicle is calculated sequentially, i.e. Where k1, k2, k3…∈K ev Based on formula (5), the exposure time Ω of emergency vehicles passing through the intersection is calculated. ev Take the union of the calculation results of the emergency vehicle and all cars in conflict directions in formula (10), as shown in formula (6): χ min Indicates the start time of the exposure period for emergency vehicles passing through the intersection, χ max This represents the end time of the exposure period for emergency vehicles passing through the intersection. According to formula (6), the exposure time Δ(Ω) for emergency vehicles passing through the intersection is obtained. ev As shown in formula (7). Δ(Ω ev )=χ max -χ min (7) The exposure time of emergency vehicles passing through intersections is constrained, as shown in formula (8): In formula (8), Δ(Ω) ev T′ represents the exposure time of emergency vehicles passing through the intersection. ev -T ev T represents the total time an emergency vehicle spends traveling through an intersection. ev Indicates the moment when an emergency vehicle enters the intersection, T′ ev The value represents the moment when the emergency vehicle leaves the intersection. ε is a parameter that represents the upper limit of the ratio of the emergency vehicle's exposure time at the intersection to the total time the emergency vehicle spends at the intersection. Step 24: Implement traffic control for cars traveling in the conflicting directions with emergency vehicles; When a green light protection phase is set for emergency vehicles to pass through an intersection, traffic control should be implemented for cars in the conflict direction of the emergency vehicles during the green light time. Cars whose passage order is after the emergency vehicles should not enter the intersection until after the green light ends, as shown in formula (9). σ(1-γ ev,k )(t end -T k )≤0k∈K ev (9) In formula (14), t end This indicates the end time of the green light protection phase for emergency vehicles; σ is a binary variable, σ = 1 indicates that the green light protection phase for emergency vehicles is set, otherwise σ = 0; when σ = 1, if γ ev,k =0, meaning the car's passage order is after the emergency vehicle, then formula (9) is equivalent to t end -T k ≤0, meaning that the time when the car enters the intersection should be after the end of the green light; when σ=0, it means that no green light protection phase for emergency vehicles is set. At this time, there is no need to carry out traffic control on cars in the conflict direction of emergency vehicles, and formula (9) always holds true. In this invention, in step 3, an optimization model is established to optimize the timing of vehicle entry into the intersection, whether an emergency vehicle green light protection phase is set, the start time of the green light, and the end time of the green light. The objective function is to minimize the average vehicle delay at the intersection, denoted by f, as shown in formula (10): In formula (10), A represents the set of all cars arriving at the intersection, emergency vehicles are represented by ev, N represents the number of vehicles arriving at the intersection, and T... i t represents the time when vehicle i enters the intersection. i This indicates the planned arrival time of vehicle i at the intersection.
[0007] Compared with the prior art, the present invention has the following outstanding advantages: 1. This invention proposes for the first time "emergency vehicle exposure time" as a continuous and quantifiable safety risk indicator. By performing layer-by-layer union calculation and proportional constraints on the time overlap within the conflict grid, the potential risks of emergency vehicles passing through intersections can be more comprehensively and accurately characterized and controlled. Compared with existing methods that only rely on discrete indicators such as the number of conflict points, TTC, or PET, this invention can more realistically reflect the safety status of emergency vehicles throughout the entire crossing process. 2. This invention incorporates whether to set a green light protection phase for emergency vehicles and its start and end times as optimizable decision variables, and integrates them with constraints on vehicle entry time and exposure time into a unified optimization framework. The objective function minimizes the average intersection delay, thereby significantly reducing the negative impact on the overall traffic efficiency of social vehicles while ensuring the safety priority of emergency vehicles, and achieving a better balance between safety and efficiency. 3. This invention employs a genetic algorithm solution model with an elite strategy, which can quickly generate a set of Pareto optimal solutions that balance safety and efficiency. This allows the actual system to flexibly select the optimal solution based on management strategies or real-time requirements, and has strong adaptability and engineering feasibility. Attached Figure Description
[0008] Figure 1 The flowchart of the method of the present invention
[0009] Figure 2 Diagram showing the exposure time of emergency vehicles
[0010] Figure 3 This is a schematic diagram of an embodiment.
[0011] Figure 4 To solve the algorithm flowchart Detailed Implementation
[0012] The following is in conjunction with the appendix Figure 1-4 The present invention will be further described in detail with reference to the embodiments, but the implementation of the present invention is not limited thereto. The implementation of the present invention is not limited to the embodiments described herein, and any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and are included within the protection scope of the present invention.
[0013] A method for prioritizing emergency vehicles at intelligent connected intersections, comprising the following steps: Step 1: Collect vehicle information arriving at the intersection, including the planned arrival time of the vehicles, their travel routes, and the set of cars in conflicting directions with emergency vehicles; Step 2: Separate all vehicles within the intersection from potential hazards, calculate and constrain the time emergency vehicles are exposed to danger while passing through the intersection, and implement traffic control for cars in the conflicting directions of emergency vehicles. Step 3: Using the minimum average vehicle delay at the intersection as the objective function, establish an optimization model to optimize the timing of vehicle entry into the intersection, whether an emergency vehicle green light protection phase is set, and the start and end times of the green light.
[0014] Step 1: Collect vehicle information arriving at the intersection, including the planned arrival time, travel route, and the set of cars facing conflicting directions with emergency vehicles. In this example, vehicles arriving at the intersection include... Figure 3 As shown, the emergency vehicle is an ambulance (white car as an example), and the other vehicles are autonomous vehicles (gray car as an example). Information such as the planned arrival time at the intersection, driving direction, and vehicle attributes for each vehicle is shown in Table 1. Table 1: Vehicle Direction of Travel, Planned Time to Arrive at the Intersection, and Vehicle Attributes
[0015] Step 2 involves conflict separation for all vehicles within the intersection, calculating and constraining the time emergency vehicles are exposed to danger while passing through the intersection, and implementing traffic control for cars in conflicting directions. In Step 21, conflict separation is performed for all vehicles within the intersection, dividing the intersection space into several grids, and stipulating that no two vehicles can simultaneously occupy the same grid. For example,... Figure 3 As shown, the intersection is divided into 64 equal grids. According to formula (1), each grid is ensured to be occupied by at most one vehicle at any given time. In step 22, to ensure the priority right-of-way for emergency vehicles at the intelligent connected intersection, the earliest time when an emergency vehicle can enter the intersection is calculated. In the example, the emergency vehicle is a white car, and the others are autonomous vehicles. The time proximity between the emergency vehicle and the autonomous vehicle in passing through the conflicting grid is as follows: Figure 2 As shown in Table 2, the time when the autonomous vehicle that conflicts with the emergency vehicle enters the intersection is calculated by formulas (2)-(3), thus obtaining the time period for the emergency vehicle to enter the intersection. In step 23, the time when the emergency vehicle is exposed to danger while passing through the intersection is calculated and constrained. In the example, as shown in Table 3, the scattered danger time periods of the emergency vehicle are calculated by formulas (4)-(7) to obtain a final total exposure time period, and the length of this total time period is constrained not to exceed a safety upper limit. Table 2: Comparison of the times when cars from conflicting directions enter the intersection for emergency vehicles Table 3: Comparison of Exposure Time Periods for Emergency Vehicles
[0016] Step 3: Using the minimum average vehicle delay at the intersection as the objective function, establish an optimization model to optimize the timing of vehicle entry into the intersection, whether an emergency vehicle green light protection phase is set, and the start and end times of the green light. For example, in the example... Figure 4As shown, a genetic algorithm with an elitist strategy is used to solve this optimization problem, generating a set of Pareto optimal solutions that achieve different balances between efficiency and safety. The decision-making system selects the optimal solution from the solution set based on actual needs, determining the precise traffic dispatch instructions for each vehicle and the traffic light control strategy for emergency vehicles.
Claims
1. A method for prioritizing emergency vehicles at intelligent connected intersections, characterized in that, The method includes the following steps: Step 1: Collect vehicle information arriving at the intersection, including the planned arrival time of the vehicles, their travel routes, and the set of cars in conflicting directions with emergency vehicles; Step 2: Separate all vehicles within the intersection from potential hazards, calculate and constrain the time emergency vehicles are exposed to danger while passing through the intersection, and implement traffic control for cars in the conflicting directions of emergency vehicles. Step 3: Using the minimum average vehicle delay at the intersection as the objective function, establish an optimization model to optimize the timing of vehicle entry into the intersection, whether an emergency vehicle green light protection phase is set, and the start and end times of the green light.
2. The method for prioritizing emergency vehicles at intelligent connected intersections according to claim 1, characterized in that, In step 2, conflict separation is performed on all vehicles within the intersection, the time that emergency vehicles are exposed to danger while passing through the intersection is calculated and constrained, and traffic control is implemented for cars in the conflict direction of emergency vehicles, including the following steps: Step 21: Separate all vehicles inside the intersection by dividing the space inside the intersection into several grids and stipulating that no two vehicles may occupy the same grid at the same time. Step 22: To ensure the priority right-of-way for emergency vehicles at intelligent connected intersections, calculate the earliest time when emergency vehicles can enter the intersection; If all vehicles in the conflict direction give way to emergency vehicles, the earliest time an emergency vehicle can enter the intersection is only affected by the vehicle in front of it in the same entrance lane. Therefore, the earliest time an emergency vehicle can enter the intersection is the maximum of the following three factors: the time when it plans to arrive at the intersection, the time when the vehicle in front can cross the stop line, the time when the vehicle in front can leave the conflict grid, and the time required for the following vehicle to enter the intersection and then enter the conflict grid. Step 23: Calculate and constrain the time that emergency vehicles are exposed to danger when passing through intersections; K ev A group of cars representing the direction of conflict between emergency vehicles. Let k represent the car that collides with the emergency vehicle, where k∈K ev G ev,k Let g represent the set of conflict grids between the emergency vehicle and car k; for a conflict between the emergency vehicle and car k at grid g, calculate the exposure time TE of the emergency vehicle. ev,k,g , that is, the time interval from when the emergency vehicle or the car k passes through grid g to when it exits grid g, as shown in formula (1): In formula (1), γ ev,k Let γ be a binary variable representing the passage order between the emergency vehicle and the car k. ev,k =1 indicates that the passage order of car k is higher than that of emergency vehicles, γ ev,k =0 indicates that emergency vehicles have priority over cars (k); PET * Indicates the danger threshold, PET ev,k,g This represents the time difference between the emergency vehicle and the car k passing through the conflict grid g; when PET ev,k,g PET * At that time, there was no significant danger between the emergency vehicle and the car k at the conflict grid g. Therefore, for the conflict between the emergency vehicle and the car k at grid g, the exposure time TE of the emergency vehicle is... ev,k,g empty set When PET ev,k,g ≤PET * At that time, there is a significant danger between the emergency vehicle and the car k at the conflict grid g. If γ ev,k =0, meaning the emergency vehicle's passage order is first. Therefore, for a conflict between the emergency vehicle and the car k at grid g, the emergency vehicle's exposure time TE is... ev,k,g This equals the time interval from when the emergency vehicle enters grid g to when it exits grid g, i.e., [t] ev,g ,T ev,g If γ ev,k =1, meaning the car's passage order is first. Therefore, for a conflict between the emergency vehicle and car k at grid g, the emergency vehicle's exposure time TE is... ev,k,g This is equal to the time interval from when the car enters grid g to when it exits grid g, i.e., [t] k,g ,T k,g ]; According to formula (1), for the conflict between the emergency vehicle and the car k at each grid point, the exposure time of the emergency vehicle is calculated sequentially, i.e. Where g1, g2, g3…∈G ev,k Based on the above calculation results, for the conflict between the emergency vehicle and the car k, the exposure time period TE′ of the emergency vehicle is calculated. ev,k The union of the calculation results of emergency vehicle and car k at all conflict grids in formula (1) is shown in formula (2): According to formula (2), for each conflict between an emergency vehicle and a car, the exposure time of the emergency vehicle is calculated sequentially, i.e. Where k1, k2, k3…∈K ev Based on formula (2), the exposure time Ω of emergency vehicles passing through the intersection is calculated. ev Take the union of the calculation results of the emergency vehicle and all cars in conflict directions in formula (2), as shown in formula (3): χ min Indicates the start time of the exposure period for emergency vehicles passing through the intersection, χ max This represents the end time of the exposure period for emergency vehicles passing through the intersection. According to formula (3), the exposure time Δ(Ω) for emergency vehicles passing through the intersection is obtained. ev As shown in formula (4). D(Oh ev )=x max -x min (4) The exposure time of emergency vehicles passing through intersections is constrained, as shown in formula (5): In formula (5), Δ(Ω) ev T′ represents the exposure time of emergency vehicles passing through the intersection. ev -T ev T represents the total time an emergency vehicle spends traveling through an intersection. ev Indicates the moment when an emergency vehicle enters the intersection, T′ ev The value represents the moment when the emergency vehicle leaves the intersection. ε is a parameter that represents the upper limit of the ratio of the emergency vehicle's exposure time at the intersection to the total time the emergency vehicle spends at the intersection. Step 24: Implement traffic control for cars traveling in the conflicting directions with emergency vehicles; When a green light protection phase is set for emergency vehicles to pass through an intersection, traffic control should be implemented for automated vehicles in the conflict direction of the emergency vehicles during the green light period. It should be stipulated that cars whose passage order is after the emergency vehicles should not enter the intersection until the green light ends. If the passage order of automated vehicles is after the emergency vehicles, a green light protection phase for emergency vehicles should be set.
3. The method for prioritizing emergency vehicles at intelligent connected intersections according to claim 1, characterized in that, In step 3, an optimization model is established to optimize the timing of vehicle entry into the intersection, whether an emergency vehicle green light protection phase is set, and the start and end times of the green light. The objective function is to minimize the average vehicle delay at the intersection, denoted by f, as shown in formula (6): In formula (6), A represents the set of all cars arriving at the intersection, emergency vehicles are represented by ev, N represents the number of vehicles arriving at the intersection, and T... i t represents the time when vehicle i enters the intersection. i This indicates the planned arrival time of vehicle i at the intersection.