Emergency vehicle intersection priority cooperative control method under mixed traffic flow

Abstract

The application relates to a novel emergency vehicle intersection priority cooperative control method under mixed traffic flow, which comprises the following steps: collecting vehicle state information, cooperatively controlling emptying of an automatic driving special lane by using an automatic driving special lane emptying algorithm based on vehicle dynamic grouping, and dynamically multiplexing to serve as an emergency lane; an emergency signal priority timing optimization model under a flexible phase sequence framework is constructed, and an optimal signal timing scheme is obtained by solving, which is used for controlling the working state of an intersection signal lamp. Compared with the prior art, the vehicle state information obtained by using the vehicle-road cooperative technology is used for cooperatively optimizing the lane function, vehicle trajectory and signal timing under the novel mixed traffic flow, an optimal cooperative optimization strategy is formulated, the emergency vehicle can safely and quickly pass through the intersection area, and the negative influence on the social vehicle is effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of intelligent traffic control technology, and in particular to a method for priority and coordinated control of emergency vehicles at intersections under mixed traffic flow. Background Technology

[0002] One of the keys to high-quality development of modern urban transportation lies in scientifically and effectively meeting the priority passage needs of emergency vehicles. Existing research and practice both show that emergency rescue time is positively correlated with the severity of damage from sudden events; therefore, minimizing the travel time of emergency vehicles is a core objective for improving public safety. However, in actual road networks, multiple factors such as obstruction by other vehicles and unreasonable signal timing often lead to a significant decrease in the efficiency of emergency vehicle passage. Traditional traffic control relies primarily on traffic lights, and traffic managers have limited means to manage and control emergency traffic during sudden events. Under saturated traffic flow, traditional signal control methods (such as early green light activation, phase extension, and phase insertion) are insufficient to effectively clear vehicles ahead of emergency vehicles and often come at the expense of a large number of other vehicles. In recent years, the continuous development of technologies such as vehicle-to-everything (V2X) and vehicle-road cooperation has provided new solutions for prioritizing emergency vehicle passage. On the one hand, real-time traffic perception and large-scale data sharing enable adaptive optimization of signal timing; on the other hand, the trajectory and path of individual vehicles can be precisely controlled, laying the foundation for coordinated optimization of "signal-path." However, fully automated driving is unlikely to be achieved in the short term. In the foreseeable future, a new type of mixed traffic flow environment where autonomous vehicles and human-driven vehicles coexist will exist for a long time. Related research shows that setting up dedicated lanes for autonomous vehicles in the early stages will effectively improve road capacity and safety. How to prioritize emergency vehicles in this new mixed traffic flow environment, that is, how to ensure the priority of emergency vehicles while minimizing the negative impact on other vehicles, has become an urgent problem to be solved.

[0003] To address the above challenges, in a fully automated driving environment, scholars have conducted extensive research on emergency priority passage. Based on different active control methods, existing research can be mainly divided into the following three categories: signal priority control methods, social vehicle speed adjustment, stopping to avoid and coordinated lane changing, and joint optimization of vehicle trajectory and signal timing. However, the above methods still have the following shortcomings: (1) Most existing methods are based on the assumptions of a fully automated driving environment and cannot be directly applied to mixed traffic flow scenarios. (2) Current lane clearing algorithms often rely on single control methods, such as signal control, speed adjustment and lane changing, which are difficult to achieve timely lane clearing under saturated traffic flow. (3) Many studies usually assume that in mixed traffic flow, CAV (connected and automated vehicle) as the lead vehicle in the platoon has completed platooning with other vehicles and takes minimizing platoon delay time as the objective function. However, in reality, CAVs change to other lanes to avoid emergency vehicles, making this assumption difficult to hold, which in turn leads to a large error in the calculation of platoon delay time. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a collaborative control method for emergency vehicles at intersections under mixed traffic flow. By coordinating and optimizing lane functions, vehicle trajectories and signal timing under the new mixed traffic flow, the method can reduce the negative impact on other vehicles while ensuring the priority of emergency vehicles.

[0005] The objective of this invention can be achieved through the following technical solution: a method for priority cooperative control of emergency vehicles at intersections under mixed traffic flow, which collects vehicle status information and uses an autonomous driving dedicated lane clearing algorithm based on vehicle dynamic grouping to cooperatively control the clearing of autonomous driving dedicated lanes so that they can be dynamically reused as emergency lanes. An optimization model for emergency signal priority timing under a flexible phase sequence framework is constructed, and the optimal signal timing scheme is obtained by solving it, which is used to control the working status of traffic lights at intersections.

[0006] Furthermore, the process of collecting vehicle status information within the intersection area includes: Use roadside equipment to collect status information of human-driven vehicles (HVs); The connected and automated vehicles (CAVs) within the intersection area communicate with the central controller in real time and follow the trajectory instructions transmitted to the CAVs by the central controller.

[0007] Furthermore, the working process of the autonomous driving dedicated lane clearing algorithm includes: Implement a conflict-based vehicle dynamic grouping strategy, dividing vehicles into speed adjustment groups and cooperative lane-changing groups. For vehicles in the speed adjustment group, adjust vehicle speed to avoid emergency vehicles in the intersection area. For vehicles in the coordinated lane-changing group, a coordinated lane-changing strategy that meets lane-changing safety constraints is implemented to avoid obstructing emergency vehicles. For each grouped vehicle, its status is described to update its speed and position.

[0008] Furthermore, the conflict-based vehicle dynamic grouping strategy specifically includes: Compare the minimum time taken for CAVs and emergency vehicles to pass through the intersection area, when When the CAV is in a certain condition, it is classified into the speed regulation group; otherwise, it is classified into the coordinated lane changing group. The relevant calculation formula is as follows: In the formula, the function Indicates vehicle type initial velocity and maximum speed, acceleration Under the constraint of distance The shortest time spent, These represent vehicle serial numbers respectively. i The initial position and initial velocity of the CAV These are the initial position and initial speed of the emergency vehicle. For 0-1 variables, This indicates that the vehicle belongs to the speed regulation group; otherwise, it belongs to the coordinated lane-changing group.

[0009] Furthermore, the cooperative lane-changing strategy specifically includes: When a CAV is assigned to a coordinated lane-changing group, it will attempt to change to the target lane. If a safe gap cannot be found, a safe gap will be actively created by coordinating the speed of the lane-changing group and the CAV in the target lane. The lane-changing safety constraints are specifically as follows: When the CAV needs to change from the dedicated autonomous driving lane to the target lane at time t, the CAV must meet the safe distance constraint with adjacent vehicles in the target lane: In the formula, These represent the distances of the front, middle, and rear vehicles from the lane start point at time t, respectively. Vehicle type The length of the vehicle body; These are the minimum safe following distances for the CAV and the vehicles in front and behind in the target lane, respectively. The minimum safe following distance is determined by the maximum value between the minimum safe headway and the minimum safe distance, to ensure the safety of lane changes. Considering the reaction time and deceleration performance of various vehicle types, calculate the minimum safe distance for each vehicle type: In the formula, It is a vehicle i The velocity at time t; Vehicle type The reaction time; Vehicle type The maximum deceleration.

[0010] Furthermore, the vehicle state is specifically described using an intelligent driver following model and an adaptive cruise control model to correspond to the vehicle state of HV and CAV. The relevant formulas of the intelligent driver following model are as follows: In the formula, It is the acceleration of the following vehicle at time t; The expected speed of the following vehicle; Let be the net distance between the front of the rear vehicle and the rear of the front vehicle at time t. This is the desired safe distance. It is the expected minimum following distance; For maximum comfort deceleration of the vehicle; The relevant formulas for the adaptive cruise control model are as follows: In the formula, These are the acceleration and velocity of the following vehicle at time t, respectively. These are the distance and speed control gain coefficients, respectively. Minimum safe distance; This is the desired safe distance. It is the expected minimum following distance; To achieve the vehicle's maximum comfort deceleration.

[0011] For safety reasons, the following constraints are imposed on vehicle dynamics: .

[0012] Furthermore, the process of constructing the emergency signal priority timing optimization model under the flexible phase sequence framework includes: designing a three-level phase structure of "emergency dedicated - manual driving - automatic driving phase", that is, dividing the intersection phase into a three-level phase structure that includes emergency dedicated, automatic driving and manual driving phases; Taking the minimum travel delay time of all social vehicles in the intersection area as the optimization objective, and combining the constraints corresponding to emergency dedicated phases, autonomous driving phases and manual driving phases, as well as the conflict constraints between the three phases, an emergency signal priority timing optimization model is established.

[0013] Furthermore, the signs of the autonomous driving phases are defined starting with the left-turn phase of the westbound approach lane, and proceeding counterclockwise as follows: The manual driving phases are also defined sequentially as follows: ; The emergency-specific phase is defined in only one direction. .

[0014] Furthermore, the optimization objective is specifically as follows: In the formula, It is the travel delay time of the i-th vehicle; The types of the i-th vehicle are respectively: in actual and ideal states. The earliest time the vehicle arrives at the stop line; The ideal time for a vehicle to pass the intersection stop line Based on vehicle type, there are two categories: CAV and HV. If the vehicle type is CAV, since its speed is controllable, it will accelerate rapidly to its maximum speed with maximum acceleration and maintain it. If the vehicle type is HV, in order to ensure safety and efficiency in mixed traffic flow, HV should maintain a stable speed as much as possible, as shown in the following formula: For the actual time it takes for a vehicle to pass the intersection stop line... The car-following model is used to describe the impact of the preceding vehicle on the following vehicle, and a fixed headway is used instead of a time-varying distance: Considering the impact of the vehicle in front, the influence of the red light on vehicles is also included in the analysis. The time for the first vehicle to cross the stop line should be the maximum of the green light start time plus the driver's reaction time, and the earliest time the vehicle can cross the intersection. For the remaining vehicles, the time to cross the stop line will depend on the maximum of the time under the influence of the vehicle in front, and the time for the vehicle in front to cross the stop line under the influence of the red light plus the minimum following distance. The specific formula is as follows: .

[0015] Furthermore, the constraints on the emergency dedicated phase include the activation and duration of the emergency dedicated phase: To ensure that emergency vehicles can pass through intersections with priority and are not obstructed by traffic lights, the green light for the emergency-only phase should turn on earlier than the time when emergency vehicles pass the intersection stop line. The relevant formula is as follows: To minimize the occupation of intersection space and time resources, the duration of the green light for the emergency-dedicated phase is equal to the sum of the time it takes for the first vehicle to pass through the intersection and the following distance of subsequent emergency vehicles, as shown in the following formula: In the formula, The duration of the green light for the emergency-dedicated phase; The number of emergency vehicles; The trajectory of the emergency vehicle within the intersection area is a straight line in the straight-ahead phase and a quarter circle in the left-turn phase. The speed at which emergency vehicles travel at intersections; Allow time for safe clearing of the intersection; The constraints on the manual driving phase include the activation and duration of the manual driving phase: The traffic flow in manually driven phases is a mixed traffic flow. When the leading vehicle is a CAV (Continuing Active Vehicle), its speed is controllable, and the green light opening time of the phase should be greater than the minimum time required for it to reach the stop line. When the leading vehicle is a HV (Hard Vehicle), the HV will reduce its speed as it passes through the intersection, therefore the earliest green light opening time of the phase should be greater than the time required for other vehicles to reach the stop line at a constant speed. The relevant formulas are as follows: In the formula, When the vehicle is manually driven, the lead vehicle in the phase is a CAV; otherwise, it is an HV. To ensure all vehicles pass through the intersection area, the green light duration is... The time taken for a vehicle to pass through the intersection must be greater than the time it takes for the green light to be on. Therefore, the sum of the green light duration and the actual time it takes for the last vehicle to pass the stop line at the intersection should be greater than the time it takes for the last vehicle to pass through the intersection. As a constraint, to ensure that the last vehicle can pass through the intersection smoothly under actual conditions: In the formula, These represent the number of manually driven vehicles and autonomous vehicles in the manual driving phase, respectively. The constraints of the autonomous driving phase include the activation and duration of the autonomous driving phase: The traffic flow in the autonomous driving phase consists entirely of autonomous vehicles. The green light duration is the same as in the case where the lead vehicle is a CAV (Autonomous Vehicle) in the manual driving phase. The green light duration in the autonomous driving phase should be at least the sum of the time required for the lead vehicle to pass through the intersection and the minimum safe following distance for all vehicles behind it. The relevant formula is as follows: Specifically, the sum of the activation and duration of the automatic driving phase required for the speed regulation group vehicles must be less than the activation time of the emergency dedicated phase to ensure that emergency vehicles are not obstructed in traffic flow. The conflict constraint between the three-level phases is specifically as follows: To ensure vehicles do not conflict within the intersection area, the conflict relationship between signal phases is analyzed when emergency lanes, dedicated autonomous driving lanes, and regular lanes coexist. Based on this relationship, constraints need to be placed on the green light activation and duration for conflicting phases, changing the order of conflicting phases from 0-1 variables. To indicate; This indicates that manual driving phase 1 is activated before emergency-dedicated phase 2; otherwise... To prevent overlapping durations of conflicting phases, the relationship between the on-time and duration of conflicting phases is constrained as follows: .

[0016] Compared with the prior art, the present invention has the following advantages: This invention first acquires vehicle status information and designs an algorithm for clearing dedicated lanes for autonomous driving based on dynamic vehicle grouping. This algorithm can collaboratively clear lanes in multiple ways and dynamically reuse them as emergency lanes. Furthermore, it constructs an emergency signal priority timing optimization model under a flexible phase sequence framework to solve for the optimal signal timing scheme. Thus, on the one hand, it clears dedicated lanes for autonomous driving through collaborative control; on the other hand, it designs a flexible phase sequence framework to ensure that emergency vehicles are not obstructed by other vehicles in mixed traffic environments and have priority passage through intersection areas. Therefore, by collaboratively optimizing lane functions, vehicle trajectories, and signal timing under new mixed traffic flows, it can reduce the negative impact on other vehicles while ensuring priority for emergency vehicles.

[0017] This invention proposes an algorithm for clearing dedicated lanes for autonomous driving based on dynamic vehicle grouping. Considering that speed adjustment alone cannot ensure that CAVs can successfully avoid emergency vehicles in the intersection area, some CAVs need to change lanes to avoid obstructing emergency vehicles. Therefore, the design divides vehicles into speed adjustment groups and coordinated lane-changing groups, and performs corresponding vehicle control to achieve a coordinated clearing strategy. By dynamically reusing dedicated lanes for autonomous driving and clearing in multiple modes, it can balance the efficiency of emergency vehicle passage and the quality of passage for social vehicles, effectively avoiding the phenomenon of emergency vehicles being "trapped" in traffic flow. By dynamically grouping vehicles based on vehicle information in the road segment area, the dedicated lanes for autonomous driving can be cleared quickly, enabling priority passage for emergency vehicles.

[0018] This invention proposes a dedicated emergency phase and a three-level phase structure within an intersection. The three-level phase structure—emergency-dedicated, manual-driving, and automatic-driving—utilizes the dedicated emergency phase to ensure the safety and efficiency of emergency vehicles within the intersection. Furthermore, based on the conflict relationships between phases, and with the goal of minimizing delays for other vehicles, the invention improves the fleet delay calculation method and flexibly optimizes the phase sequence, activation, and duration of each phase. This significantly reduces the negative impact on other vehicles while ensuring emergency vehicle priority and improving emergency vehicle efficiency, thus balancing the relationship between emergency priority and the efficiency of other vehicle traffic. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram showing the distance and position between vehicles in the embodiment; Figure 3 This is a phase conflict relationship diagram in the embodiment; Figure 4 This is a schematic diagram of an intersection scene in the embodiment. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0021] Example like Figure 1 As shown, a method for priority cooperative control of emergency vehicles at intersections under mixed traffic flow first collects vehicle status information and then uses an autonomous driving dedicated lane clearing algorithm based on vehicle dynamic grouping to cooperatively control the clearing of autonomous driving dedicated lanes so that they can be dynamically reused as emergency lanes. An optimization model for emergency signal priority timing under a flexible phase sequence framework is constructed, and the optimal signal timing scheme is obtained by solving it, which is used to control the working status of traffic lights at intersections.

[0022] This embodiment applies the above solution, and the main process steps include: S1: Collect vehicle information; S2: Design an algorithm for clearing dedicated lanes for autonomous driving based on vehicle dynamic grouping; S3: Construct an emergency signal priority timing optimization model under a flexible phase sequence framework; S4: Model Solving.

[0023] Specifically, in step S1, the vehicle status information obtained using vehicle-road cooperative technology is used to collect the status of HVs (vehicles) on the one hand, by using roadside equipment (such as radar, cameras, etc.) on the other hand, the CAVs in the intersection area need to communicate with the central controller in real time and follow the trajectory instructions transmitted to the vehicles by the central controller.

[0024] Step S2 includes: S21: Conflict-based vehicle dynamic grouping This plan takes into account that speed adjustment alone cannot ensure that CAVs can successfully avoid emergency vehicles in the intersection area. Therefore, in order to avoid obstructing emergency vehicles, some CAVs need to change lanes.

[0025] By comparing the minimum time taken for CAVs and emergency vehicles to pass through the intersection area, when When the CAV changes speed, it is classified into the speed regulation group; otherwise, it is classified into the coordinated lane-changing group. The relevant calculation formula is as follows: In the formula, the function Indicates vehicle type initial velocity and maximum speed, acceleration Under the constraint of distance The shortest time spent, These represent vehicle serial numbers respectively. iThe initial position and initial velocity of the CAV These are the initial position and initial speed of the emergency vehicle. For 0-1 variables, This indicates that the vehicle belongs to the speed regulation group; otherwise, it belongs to the coordinated lane-changing group.

[0026] S22: Cooperative lane-changing strategy: When a CAV is assigned to a coordinated lane-changing group, it will attempt to change to the target lane. If a safe gap cannot be found, a safe gap will be proactively created by coordinating the speed of the lane-changing group and the CAV in the target lane.

[0027] S23: Lane changing safety constraints: When an autonomous vehicle needs to change from the dedicated autonomous driving lane to the target lane at time t, the CAV must meet the safe distance constraints with adjacent vehicles in the target lane. In the formula, Each as Figure 2 The distances of the vehicles in front, in the middle, and behind from the starting point of the lane at time t; Vehicle type The length of the vehicle body; These are the minimum safe following distances for the CAV and the vehicles in front and behind in the target lane, respectively.

[0028] At low speeds, the following distance defined based on the minimum safe headway is too small to guarantee vehicle safety. Therefore, this solution uses the maximum value between the following distance defined by the minimum safe headway and the minimum safe distance as the minimum safe following distance to ensure lane changing safety. The minimum safe distance between different types of vehicles in mixed traffic flow varies and is usually determined based on reaction time. Therefore, this scheme calculates the minimum safe distance for each vehicle type by considering the reaction time and deceleration performance of each type of vehicle. The specific formula is as follows: In the formula, It is a vehicle i The velocity at time t; Vehicle type The reaction time; Vehicle type The maximum deceleration.

[0029] S24: Vehicle Status Description: Without speed adjustment and coordinated lane changing, and referring to relevant research, this scheme uses an intelligent driver following model and an adaptive cruise control model to describe the vehicle states of HV and CAV, respectively.

[0030] The relevant formulas for the intelligent driver car-following model are as follows: In the formula, It is the acceleration of the following vehicle at time t; The expected speed of the following vehicle; Let be the net distance between the front of the rear vehicle and the rear of the front vehicle at time t. This is the desired safe distance. It is the expected minimum following distance; To achieve the vehicle's maximum comfort deceleration.

[0031] The relevant formulas for the adaptive cruise control model are as follows: In the formula, These are the acceleration and velocity of the following vehicle at time t, respectively. These are the distance and speed control gain coefficients, respectively. Minimum safe distance; This is the desired safe distance. It is the expected minimum following distance; To achieve the vehicle's maximum comfort deceleration.

[0032] For safety reasons, the following constraints are imposed on vehicle dynamics: .

[0033] Step S3 includes: S31: Signalized Intersection Phase Settings. Intersection phases are divided into a three-tiered phase structure: emergency-only, automated driving, and manual driving phases. The symbols for automated driving phases are defined starting with the left-turn phase of the westbound approach lane, proceeding counter-clockwise as follows: The manual driving phases are also defined sequentially. Since this scheme only considers the situation of emergency vehicles or convoys passing through signalized intersections in one direction, only one direction of the dedicated emergency phase is defined as follows. .

[0034] S32: Set the objective function of the optimization model: Minimize the travel delay time of all social vehicles within the intersection area. In the formula, It is the travel delay time of the i-th vehicle; The types of the i-th vehicle are respectively: in actual and ideal states. The earliest time a vehicle arrives at the stop line.

[0035] S33: Vehicle Delay Calculation Existing research typically defines vehicle delay as the difference between the actual time a convoy takes to cross the intersection stop line and the ideal time. However, in emergency vehicle priority scenarios, to avoid emergency vehicles being obstructed by CAVs (Autonomous Vehicles), multiple autonomous vehicles need to switch from the dedicated autonomous driving lane to the target lane within a short period. In this situation, vehicles in the target lane cannot maintain a convoy formation. This solution considers the impact of the preceding vehicle and traffic lights on the time it takes for a vehicle to cross the stop line, thus providing a more accurate estimate of the actual time a single vehicle takes to cross the intersection stop line under real-world conditions, thereby reducing the deviation in delay time for other vehicles.

[0036] The ideal time for a vehicle to pass the intersection stop line Depending on the vehicle type, there are two scenarios: CAV and HV. If the vehicle type is CAV, since its speed is controllable, it will rapidly accelerate to its maximum speed with maximum acceleration and maintain that speed. If the vehicle type is HV, in order to ensure safety and efficiency in mixed traffic flow, HV should maintain a stable speed as much as possible, as shown in the following formula: This scheme uses a car-following model to describe the impact of the preceding vehicle on the following vehicle, and to improve computational efficiency, a fixed headway is used instead of a time-varying distance. Based on the consideration of the impact of the vehicle ahead, this plan further incorporates the impact of red lights on vehicles into the analysis. The time for the first vehicle to cross the stop line should be the maximum of the green light start time plus the driver's reaction time, and the earliest time the vehicle can cross the intersection. For the remaining vehicles, the time to cross the stop line will depend on the maximum of the time under the influence of the vehicle ahead, and the time for the vehicle ahead to cross the stop line under the influence of red lights plus the minimum following distance. The specific formula is as follows: S34: Add constraint 1 to the optimization model: Emergency dedicated phase activation and duration To ensure emergency vehicles have priority passage through intersections without being obstructed by traffic lights, the green light for the dedicated emergency phase should turn on earlier than the time emergency vehicles cross the intersection stop line. The relevant formula is as follows: To minimize the occupation of intersection space and time resources, the duration of the green light for the emergency-dedicated phase is equal to the sum of the time it takes for the first vehicle to pass through the intersection and the following distance of subsequent emergency vehicles, as shown in the following formula: In the formula, The duration of the green light for the emergency-dedicated phase; The number of emergency vehicles; The trajectory of the emergency vehicle within the intersection area is a straight line in the straight-ahead phase and a quarter circle in the left-turn phase. The speed at which emergency vehicles travel at intersections; Allow time for safe clearing of the intersection.

[0037] S35: Add constraint 2 to the optimization model: manual driving phase activation and duration The traffic flow in manually driven phases is a mixed traffic flow. Therefore, the earliest arrival time of the leading vehicle at the stop line needs to be discussed in two cases: When the leading vehicle is a CAV (Continuing Active Vehicle), its speed is controllable, and the green light opening time of the phase should be greater than the minimum time required for it to reach the stop line; when the leading vehicle is a HV (Hard Vehicle), the HV will reduce its speed as it passes through the intersection, so the earliest green light opening time of the phase is greater than the time required for other vehicles to reach the stop line at a constant speed. The relevant formulas are as follows: In the formula, When the vehicle is manually driven, the lead vehicle in the phase is CAV; otherwise, it is HV.

[0038] To ensure all vehicles pass through the intersection area, the green light duration is... The time taken for a vehicle to pass through the intersection must be greater than the time it takes for the vehicle to pass through the intersection. Many existing studies typically assume that in mixed traffic flow, the CAV (Caravan Driver) as the lead vehicle in the platoon has already formed a platoon with other vehicles. Therefore, the time for a vehicle to pass through the intersection includes the sum of the time required for the lead vehicle to pass through the intersection area and the minimum safe following distance for the following vehicles. However, in emergency priority scenarios in mixed traffic flow, the CAV may switch to other lanes to yield to emergency vehicles, making this assumption difficult to hold. Therefore, this proposal suggests that the sum of the green light's on time and duration should be greater than the actual time it takes for the last vehicle to pass through the intersection stop line. As a constraint, it ensures that the last vehicle can pass through the intersection smoothly under actual conditions. In the formula, These represent the number of manually driven vehicles and autonomous vehicles in the manual driving phase, respectively.

[0039] S36: Add constraint 3 to the optimization model: autonomous driving phase activation and duration The traffic flow in the autonomous driving phase consists entirely of autonomous vehicles, and the green light duration is the same as in the manual driving phase where the lead vehicle is a CAV. The green light duration in the autonomous driving phase should be at least the sum of the time required for the lead vehicle to pass through the intersection and the minimum safe following distance for all vehicles behind it. The relevant formula is as follows: Specifically, the sum of the activation and duration of the automatic driving phase required for speed regulation vehicles must be less than the activation time of the emergency-dedicated phase to ensure that emergency vehicles are not obstructed in traffic flow. This requirement is crucial for preventing emergency vehicles from being blocked during emergency priority passage and effectively ensures their smooth passage. S37: Add constraint 4 to the optimization model: inter-phase conflict relationship To ensure that vehicles do not collide in the intersection area, such as Figure 3 As shown, the conflict relationship between different signal phases is analyzed when emergency lanes, dedicated lanes for autonomous driving, and regular lanes coexist. Based on this relationship, constraints need to be imposed on the green light activation and duration for conflicting phases.

[0040] The order of conflicting phases is determined by a 0-1 variable. To indicate; This indicates that manual driving phase 1 is activated before emergency-dedicated phase 2; otherwise... To prevent overlapping durations of conflicting phases, the relationship between the on-time and duration of conflicting phases is constrained as follows: S4: Model Solving.

[0041] Figure 4The diagram illustrates the basic scenario of this embodiment. When constructing the MILP model, the relevant parameters are pre-set as follows: the entrance lane length is 300m, and the maximum speeds of manual driving, autonomous driving, and emergency vehicles are 14, 20, and 25 m / s, respectively. The reaction times for manual driving and autonomous driving vehicles are 2 and 1 second, respectively. The model is compiled using AMPL and solved quickly using the IPOPT solver. The processor is an Intel(R) Core(TM) Ultra 5 125H, 1.20 GHz, with 32.0GB of memory. The average solution time is less than 50ms, meeting real-time requirements.

[0042] The model results demonstrate that, compared to methods that do not include dedicated autonomous driving lanes and employ a greedy signal preemption scheme based on a dual-ring structure for signal timing, the proposed cooperative control method reduces the average travel time of emergency vehicles by 38.64% and the delay time of other vehicles by 64.91%. Compared to existing methods that employ speed-adjustment-based autonomous driving lane clearing algorithms and signal timing optimization models that balance emergency priority and social benefits, this method reduces the average travel time of emergency vehicles by 15.52% and the delay time of other vehicles by 7.90%.

[0043] In summary, this solution utilizes vehicle status information obtained through vehicle-road cooperative technology and employs an autonomous driving lane-clearing algorithm based on dynamic vehicle grouping. It uses multiple methods to collaboratively clear lanes and dynamically reuses them as emergency lanes. Simultaneously, to ensure the safety and efficiency of emergency vehicles passing through intersections, a dedicated emergency phase is established to prioritize their right-of-way. Based on this, a three-level phase structure—emergency-dedicated, manual driving, and autonomous driving—is designed. Based on the conflict relationships between phases and aiming to minimize delays for other vehicles, the phase sequence, activation, and duration are flexibly optimized. This effectively reduces the negative impact on other vehicles while ensuring emergency priority.

Claims

1. A method for priority cooperative control of emergency vehicles at intersections under mixed traffic flow, characterized in that, Collect vehicle status information and use an autonomous driving lane clearing algorithm based on vehicle dynamic grouping to coordinate the clearing of autonomous driving lanes so that they can be dynamically reused as emergency lanes. An optimization model for emergency signal priority timing under a flexible phase sequence framework is constructed, and the optimal signal timing scheme is obtained by solving it, which is used to control the working status of traffic lights at intersections. The specific optimization objective of the emergency signal priority timing optimization model under the flexible phase sequence framework is as follows: In the formula, It is the travel delay time of the i-th vehicle; The types of the i-th vehicle are respectively: in actual and ideal states. The earliest time the vehicle arrives at the stop line; The ideal time for a vehicle to pass the intersection stop line Based on vehicle type, there are two categories: CAV and HV. If the vehicle type is CAV, since its speed is controllable, it will accelerate rapidly to its maximum speed with maximum acceleration and maintain it. If the vehicle type is HV, in order to ensure safety and efficiency in mixed traffic flow, HV should maintain a stable speed as much as possible, as shown in the following formula: For the actual time it takes for a vehicle to pass the intersection stop line... The car-following model is used to describe the impact of the preceding vehicle on the following vehicle, and a fixed headway is used instead of a time-varying distance: Considering the impact of the vehicle in front, the influence of the red light on vehicles is also included in the analysis. The time for the first vehicle to cross the stop line should be the maximum of the green light start time plus the driver's reaction time, and the earliest time the vehicle can cross the intersection. For the remaining vehicles, the time to cross the stop line will depend on the maximum of the time under the influence of the vehicle in front, and the time for the vehicle in front to cross the stop line under the influence of the red light plus the minimum following distance. The specific formula is as follows: The constraints of the emergency signal priority timing optimization model under the flexible phase sequence framework include constraints on emergency dedicated phases, constraints on manual driving phases, constraints on autonomous driving phases, and conflict constraints between the three phase levels. The constraints of the emergency dedicated phase include the activation and duration of the emergency dedicated phase: To ensure that emergency vehicles can pass through intersections with priority and are not obstructed by traffic lights, the green light for the emergency-only phase should turn on earlier than the time when emergency vehicles pass the intersection stop line. The relevant formula is as follows: To minimize the occupation of intersection space and time resources, the duration of the green light for the emergency-dedicated phase is equal to the sum of the time it takes for the first vehicle to pass through the intersection and the following distance of subsequent emergency vehicles, as shown in the following formula: In the formula, The duration of the green light for the emergency-dedicated phase; The number of emergency vehicles; The trajectory of the emergency vehicle within the intersection area is a straight line in the straight-ahead phase and a quarter circle in the left-turn phase. The speed at which emergency vehicles travel at intersections; Allow time for safe clearing of the intersection; The constraints on the manual driving phase include the activation and duration of the manual driving phase: The traffic flow in manually driven phases is a mixed traffic flow. When the leading vehicle is a CAV (Continuing Active Vehicle), its speed is controllable, and the green light opening time of the phase should be greater than the minimum time required for it to reach the stop line. When the leading vehicle is a HV (Hard Vehicle), the HV will reduce its speed as it passes through the intersection, therefore the earliest green light opening time of the phase should be greater than the time required for other vehicles to reach the stop line at a constant speed. The relevant formulas are as follows: In the formula, When the vehicle is manually driven, the lead vehicle in the phase is a CAV; otherwise, it is an HV. To ensure all vehicles pass through the intersection area, the green light duration is... The time taken for a vehicle to pass through the intersection must be greater than the time it takes for the green light to be on. Therefore, the sum of the green light duration and the actual time it takes for the last vehicle to pass the stop line at the intersection should be greater than the time it takes for the last vehicle to pass through the intersection. As a constraint, to ensure that the last vehicle can pass through the intersection smoothly under actual conditions: In the formula, These represent the number of manually driven vehicles and autonomous vehicles in the manual driving phase, respectively. The constraints of the autonomous driving phase include the activation and duration of the autonomous driving phase: The traffic flow in the autonomous driving phase consists entirely of autonomous vehicles. The green light duration is the same as in the case where the lead vehicle is a CAV (Autonomous Vehicle) in the manual driving phase. The green light duration in the autonomous driving phase should be at least the sum of the time required for the lead vehicle to pass through the intersection and the minimum safe following distance for all vehicles behind it. The relevant formula is as follows: Specifically, the sum of the activation and duration of the automatic driving phase required for the speed regulation group vehicles must be less than the activation time of the emergency dedicated phase to ensure that emergency vehicles are not obstructed in traffic flow. The conflict constraint between the three-level phases is specifically as follows: To ensure vehicles do not conflict within the intersection area, the conflict relationship between signal phases is analyzed when emergency lanes, dedicated autonomous driving lanes, and regular lanes coexist. Based on this relationship, constraints need to be placed on the green light activation and duration for conflicting phases, changing the order of conflicting phases from 0-1 variables. To indicate; This indicates that manual driving phase 1 is activated before emergency-dedicated phase 2; otherwise... To prevent overlapping durations of conflicting phases, the relationship between the on-time and duration of conflicting phases is constrained as follows: The working process of the autonomous driving dedicated lane clearing algorithm includes: Implement a conflict-based vehicle dynamic grouping strategy, dividing vehicles into speed adjustment groups and cooperative lane-changing groups. For vehicles in the speed adjustment group, adjust vehicle speed to avoid emergency vehicles in the intersection area. For vehicles in the coordinated lane-changing group, a coordinated lane-changing strategy that meets lane-changing safety constraints is implemented to avoid obstructing emergency vehicles. For each grouped vehicle, its status is described to update its speed and position. The conflict-based vehicle dynamic grouping strategy is specifically as follows: Compare the minimum time taken for CAVs and emergency vehicles to pass through the intersection area, when When the CAV is in a certain condition, it is classified into the speed regulation group; otherwise, it is classified into the coordinated lane changing group. The relevant calculation formula is as follows: In the formula, the function Indicates vehicle type initial velocity and maximum speed, acceleration Under the constraint of distance The shortest time spent, These represent vehicle serial numbers respectively. i The initial position and initial velocity of the CAV These are the initial position and initial speed of the emergency vehicle. For 0-1 variables, This indicates that the vehicle belongs to the speed regulation group; otherwise, it belongs to the coordinated lane-changing group.

2. The method for priority coordinated control of emergency vehicles at intersections under mixed traffic flow according to claim 1, characterized in that, The process of collecting vehicle status information within the intersection area includes: Use roadside equipment to collect HV (human-driven vehicle) status information of human-driven vehicles; The autonomous vehicles (CAVs) within the intersection area communicate with the central controller in real time and follow the trajectory instructions transmitted to the CAVs by the central controller.

3. The method for priority cooperative control of emergency vehicles at intersections under mixed traffic flow according to claim 1, characterized in that, The coordinated lane-changing strategy is specifically as follows: When a CAV is assigned to a coordinated lane-changing group, it will attempt to change to the target lane. If a safe gap cannot be found, a safe gap will be actively created by coordinating the speed of the lane-changing group and the CAV in the target lane. The lane-changing safety constraints are specifically as follows: When the CAV needs to change from the dedicated autonomous driving lane to the target lane at time t, the CAV must meet the safe distance constraint with adjacent vehicles in the target lane: In the formula, These represent the distances of the front, middle, and rear vehicles from the lane start point at time t, respectively. Vehicle type The length of the vehicle body; These are the minimum safe following distances for the CAV and the vehicles in front and behind in the target lane, respectively. The minimum safe following distance is determined by the maximum value between the minimum safe headway and the minimum safe distance, to ensure the safety of lane changes. Considering the reaction time and deceleration performance of various vehicle types, calculate the minimum safe distance for each vehicle type: In the formula, It is a vehicle i The velocity at time t; Vehicle type The reaction time; Vehicle type The maximum deceleration.

4. The method for priority cooperative control of emergency vehicles at intersections under mixed traffic flow according to claim 3, characterized in that, The description of vehicle status specifically employs the intelligent driver following model and the adaptive cruise control model to describe the vehicle status of HV and CAV respectively. The relevant formulas for the intelligent driver following model are as follows: In the formula, It is the acceleration of the following vehicle at time t; The expected speed of the following vehicle; Let be the net distance between the front of the rear vehicle and the rear of the front vehicle at time t. This is the desired safe distance. It is the expected minimum following distance; For maximum comfort deceleration of the vehicle; The relevant formulas for the adaptive cruise control model are as follows: In the formula, These are the acceleration and velocity of the following vehicle at time t, respectively. These are the distance and speed control gain coefficients, respectively. Minimum safe distance; This is the expected safe distance; For safety reasons, the following constraints are imposed on vehicle dynamics: 。 5. The method for priority coordinated control of emergency vehicles at intersections under mixed traffic flow according to claim 1, characterized in that, The process of constructing the emergency signal priority timing optimization model under the flexible phase sequence framework includes: designing a three-level phase structure of emergency-dedicated, manual driving, and automatic driving phases, that is, dividing the intersection phases into a three-level phase structure that includes emergency-dedicated, automatic driving, and manual driving phases; Taking the minimum travel delay time of all social vehicles in the intersection area as the optimization objective, and combining the constraints corresponding to emergency dedicated phases, autonomous driving phases and manual driving phases, as well as the conflict constraints between the three phases, an emergency signal priority timing optimization model is established.

6. The method for priority cooperative control of emergency vehicles at intersections under mixed traffic flow according to claim 5, characterized in that, The symbols for the autonomous driving phases are defined starting with the left-turn phase of the westbound entrance, and proceeding counterclockwise as follows: The manual driving phases are also defined sequentially as follows: ; The emergency-specific phase is defined in only one direction. .

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