A highway emergency dynamic induction and collaborative regulation method and system based on real-time vehicle position

Abstract

This invention discloses a method and system for dynamic guidance and collaborative control of highway emergencies based on real-time vehicle location. The method includes: classifying event types; calculating an event severity index based on road segment traffic conditions; determining the response level based on the severity of the event; automatically selecting appropriate emergency plans based on event location and severity; dynamically generating a three-layer geofence; developing corresponding evacuation or detour strategies for vehicles in different areas; analyzing the types and quantities of resources required for the event; identifying the nearest and adequately stocked supply points; disseminating guidance information to drivers; adjusting traffic light phases; and initiating ramp control measures. The invention also includes real-time tracking of strategy implementation effects, collecting feedback data, calculating a strategy effectiveness index, and adjusting and optimizing subsequent actions. This invention enables collaborative control based on real-time vehicle location information, combined with multi-source data fusion, dynamic area division, second-level strategy generation, intelligent matching of rescue supplies, and road network coordination.

Description

Technical Field

[0001] This invention belongs to the field of intelligent transportation systems (ITS) and emergency management technology, specifically involving a method and system for dynamic guidance and collaborative control of highway emergencies based on real-time vehicle location. When an emergency occurs on a highway (such as a fire or accident), it can combine real-time vehicle location information with multi-source data fusion, dynamic regional division, second-level strategy generation, intelligent matching of rescue materials, and collaborative control of the road network. Background Technology

[0002] Current highway emergency guidance systems largely rely on manual experience or static plans, resulting in problems such as high response delays, a "one-size-fits-all" approach, a lack of coordination with roadside facilities, and low efficiency in resource dispatch. Especially in high-risk events such as fires, the inability to provide differentiated guidance to vehicles in different locations can easily lead to secondary accidents or the spread of congestion. Existing systems typically broadcast the same detour information to all vehicles along the entire route, causing vehicles in unaffected areas to be misguided and high-risk vehicles in controlled areas to receive insufficient intervention, thus reducing road network efficiency and creating safety risks. Current technologies have not yet solved the problem of integrated closed-loop control encompassing "precise zoning - rapid decision-making - dynamic feedback - resource coordination." Summary of the Invention

[0003] The purpose of this invention is to provide a method for dynamic guidance and collaborative control of highway emergencies based on real-time vehicle location. This method can achieve precise dynamic geofencing based on event severity and road network topology; complete the automatic decision-making closed loop from perception to policy issuance within 10 seconds; provide nearby intelligent matching and inventory replenishment of relief supplies; evaluate the effectiveness of guidance strategies and adaptively iterate; and link with facilities such as traffic lights, information boards, and ramps to improve the overall road network resilience.

[0004] Another objective of this invention is to provide a dynamic guidance and collaborative control system for highway emergencies based on real-time vehicle location. It pioneers a "three-layer dynamic geofencing" mechanism to achieve spatial refinement of guidance strategies; it dynamically divides control zones, impact zones, and non-impact zones based on real-time vehicle location to achieve differentiated guidance for each vehicle; and it avoids unnecessary path interference for unrelated vehicles, thereby improving the overall road network traffic efficiency.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The first aspect of this invention provides a method for dynamic guidance and coordinated control of highway emergencies based on real-time vehicle location, comprising the following steps: (1) Use image recognition technology to classify event types, calculate the event severity index in combination with road traffic conditions, and determine the response level based on the severity of the event; (2) Automatically select appropriate emergency plans based on the location and severity of the event, and dynamically generate three-layer geofences, including control zone, impact zone, and no-impact zone; (3) Specify corresponding evacuation or detour strategies for vehicles in different areas, and optimize the guidance plan by taking into account factors such as weather conditions and real-time road conditions. (4) Analyze the types and quantities of resources required for the event, and use a distance-first greedy strategy to clearly identify the nearest and most readily available supply point; (5) Provide guidance information to drivers through V2X communication, variable message signs, etc., adjust the phase of traffic lights, and initiate ramp control measures; (6) Track the strategy execution effect in real time, collect feedback data, calculate the strategy effectiveness index, and adjust and optimize subsequent actions accordingly.

[0006] Optionally, in step (1), the event severity index S∈[0,1] is defined: in: f type Event type factor: Fire: f type =1.0 Major casualty accidents: f type =0.7 General traffic accidents: f type =0.4 Vehicle breakdowns and other common incidents: f type =0.2 n affected Number of lanes affected; n total : Total number of lanes in this section of road; w1 and w2 are weighting coefficients, satisfying w1+w2=1, with the default values ​​being w1=0.6 and w2=0.4.

[0007] When S≥0.7, it is determined to be a "serious event" and the highest level of emergency response is triggered.

[0008] Optionally, in step (2), based on the event location and severity, the system dynamically calculates the upstream boundary lengths of the control area and the affected area: L control =α × v free × T evac L impact =β×L control in: L controlControl zone length (unit: meters), which is the maximum distance from the incident point upstream to the first evacuation node (service area / interchange / toll station); L impact Length of the affected area (unit: meters); v free Free-flow velocity (m / s) in this section; T evac : Preset evacuation time (seconds), 120s for fire, and linear interpolation of other events using S (e.g., Tevac=60+60×S). α∈[0.8,1.2]: Safety redundancy coefficient, adjusted in real time according to visibility and weather; β∈[1.5,3.0]: The expansion factor of the influence area. The larger S is, the larger β is (e.g., β=1.5+1.5×S).

[0009] The system searches for evacuation nodes along the upstream direction. If the actual distance is less than the calculated value, the actual node is used as the boundary; otherwise, the calculated value is used as the cutoff.

[0010] Optionally, in step (3), a customized instruction is pushed based on the region to which the vehicle belongs: Controlled area: Depart quickly according to on-site instructions; Affected area: Recommended evacuation detour routes + dynamic speed limits (e.g., V) limit =max(30,0.5×v free (km / h); No impact zone: Event briefing only.

[0011] The misleading information is simultaneously distributed via WeChat messages, variable message signs (with dynamically generated content), and navigation platform interfaces.

[0012] Optionally, in step (4), let the total amount of materials required for the event be Q, and the set of available material points be {P}. i The inventory at each point is q. i The distance from the event point is d i The system uses a distance-first greedy matching strategy: 1. Sort the material points in ascending order of distance: P(1), P(2), ..., P(n), satisfying d(1)≤d(2)≤...≤d(n); 2. Find the smallest integer k such that: ; 3. Allocation of material quantities: ; Generate dispatch instructions and push them to the emergency command center to ensure that supplies arrive in the shortest possible time.

[0013] Optionally, in step (5), the induction effect is continuously monitored, and the strategy effectiveness index E(t) is defined: ; in: N complied (t): The number of vehicles that have left the control area as instructed at time t; N target (t): Total number of vehicles that should respond within the target area; V delay (t): Average travel delay of vehicles within the control area (seconds); V max Maximum tolerable delay (default 300 seconds); γ∈[0.5,0.8]: Compliance rate weight.

[0014] If E(t) < θ (a threshold is set, such as 0.6), then a policy update is triggered: Increase the strength of speed limit constraints; Close more upstream ramps; Activate secondary evacuation nodes; Adjust the emergency level of the information board prompts.

[0015] At the same time, the system will link the updated strategy with traffic light phases and variable lane directions to achieve network-level coordinated control.

[0016] A second aspect of the present invention provides a dynamic guidance and collaborative control system for highway emergencies based on real-time vehicle location, comprising: Event Recognition and Severity Assessment Module: Uses image recognition technology to classify event types, calculates the event severity index in combination with road traffic conditions, and determines the response level based on the severity of the event; Three-layer dynamic fence generation module: used to automatically select the appropriate emergency plan based on the location and severity of the event, and dynamically generate three-layer geofences, including control zone, impact zone, and no-impact zone; Differentiated guidance strategy generation module: used to specify corresponding evacuation or detour strategies for vehicles in different areas, while taking into account factors such as weather conditions and real-time traffic conditions to optimize the guidance plan; Rescue supplies matching module: used to analyze the types and quantities of resources required for an event, and use a distance-first greedy strategy to clearly determine the nearest supply point with sufficient inventory; Strategy distribution and roadside coordination module: used to distribute guidance information to drivers through V2X communication, variable message signs and other means, adjust traffic light phases, and initiate ramp control measures, etc. The execution effect feedback and strategy optimization module is used to track the strategy execution effect in real time, collect feedback data, calculate the strategy effectiveness index, and adjust and optimize subsequent actions accordingly.

[0017] All of the above calculation modules (severity assessment, fence delineation, resource matching, and strategy generation) adopt lightweight algorithm design to ensure that the end-to-end processing time does not exceed 10 seconds, meeting the timeliness requirements of emergency response.

[0018] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention can achieve precise dynamic geofencing based on event severity and road network topology; complete the automatic decision-making closed loop from perception to policy issuance within 10 seconds; provide nearby intelligent matching and inventory replenishment of relief supplies; evaluate the effectiveness of guidance strategies and adaptively iterate; and link with facilities such as traffic lights, information boards, and ramps to improve the overall road network resilience. This invention proposes a three-layer dynamic geofencing model based on event points, combined with real-time vehicle GPS location, to achieve spatial granularity accurate to the "road segment level" for zoned management; abandons the extensive mode of "uniform across the entire road segment," and dynamically divides control zones, impact zones, and non-impact zones based on real-time vehicle location to achieve differentiated guidance for "one vehicle, one policy"; the fence boundary is jointly determined by event severity, free flow velocity, and evacuation node distribution, combining scientific rigor and adaptability; avoids unnecessary path interference for unrelated vehicles, and improves the overall road network traffic efficiency. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the steps of a method for dynamic induction and coordinated control of highway emergencies based on real-time vehicle location provided by the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the specific implementation process of this method will be described in detail below with reference to two typical application scenarios. Example 1

[0021] A method for dynamic guidance and collaborative control of highway emergencies based on real-time vehicle location, see [link / reference]. Figure 1 This includes the following steps: (1) Event identification and severity assessment: The event type is classified using image recognition technology, and the event severity index is calculated in combination with the traffic conditions of the road segment. The response level is determined according to the severity of the event. In step (1), to scientifically determine the event severity level, the event severity index S∈[0,1] is defined: in: f type Event type factor: Fire: ftype =1.0 Major casualty accidents: f type =0.7 General traffic accidents: f type =0.4 Vehicle breakdowns and other common incidents: f type =0.2 n affected Number of lanes affected; n total : Total number of lanes in this section of road; w1 and w2 are weighting coefficients, satisfying w1+w2=1, with the default values ​​being w1=0.6 and w2=0.4.

[0022] When S≥0.7, it is determined to be a "serious event" and the highest level of emergency response is triggered.

[0023] (2) Algorithm matching budget: Automatically select appropriate emergency plans based on the location and severity of the event, and dynamically generate three-layer geofences, including control zone, impact zone and no impact zone; In step (2), based on the event location and severity, the system dynamically calculates the upstream boundary lengths of the control area and the affected area: L control =α × v free × T evac L impact =β×L control in: L control Control zone length (unit: meters), which is the maximum distance from the incident point upstream to the first evacuation node (service area / interchange / toll station); L impact Length of the affected area (unit: meters); v free Free-flow velocity (m / s) in this section; T evac Preset evacuation time (seconds): 120s for fire, and other events are interpolated linearly using S (e.g., T). evac =60+60×S); To avoid the problem of policy jumps in traditional hierarchical control, this invention introduces a linear interpolation mechanism based on severity index to dynamically determine the evacuation time parameter T. evac .

[0024] Specifically, the system uses the baseline time (60s) for minor events as the lower bound and the maximum safe time (120s) for serious events as the upper bound. Based on the real-time calculated event severity index S (0<=S<=1), it uses a linear mapping function T.evac (S) = 60 + 60 × S, continuously and smoothly adjusting the evacuation duration. α∈[0.8,1.2]: Safety redundancy coefficient, which is adjusted in real time according to visibility and weather, as shown in Table 1.

[0025] Table 1 Safety Redundancy Coefficient β∈[1.5,3.0]: The expansion factor of the influence area. The larger S is, the larger β is (e.g., β=1.5+1.5×S).

[0026] The system searches for evacuation nodes along the upstream direction. If the actual distance is less than the calculated value, the actual node is used as the boundary; otherwise, the calculated value is used as the cutoff.

[0027] (3) Differentiated guidance strategy formulation: formulate corresponding evacuation or detour strategies for vehicles in different areas, and optimize the guidance plan by taking into account factors such as weather conditions and real-time road conditions. In step (3), a customized instruction is sent based on the region to which the vehicle belongs: Controlled area: Forced guidance to the nearest exit + dynamic speed limiting (e.g., V) limit =max(30,0.5×v free (km / h); Affected area: Recommended detour route + ramp closure warning; No impact zone: Event briefing only.

[0028] The misleading information is simultaneously distributed via WeChat messages, variable message signs (with dynamically generated content), and navigation platform interfaces.

[0029] Weather conditions and real-time road conditions are the main factors affecting the length of the affected area; Calculation of the final influence zone length: Assume the length of the basic influence zone is L. base =5km; L impact =L base × (1 + β); where β = β weather + β traffic The maximum value of β is 1, where β weather β represents the weather risk coefficient. traffic This indicates the road condition risk coefficient.

[0030] The weather risk coefficients are shown in Table 2 below, and the road condition risk coefficients are shown in Table 3 below.

[0031] Table 2 Weather Risk Coefficient Table 3 Road Condition Risk Coefficient (4) Intelligent matching of relief supplies: Analyze the types and quantities of resources required for the event, and use a distance-first greedy strategy to clearly identify the nearest supply point with sufficient inventory; In step (4), let the total amount of materials required for the event be Q, and the set of available material points be {P}. i The inventory at each point is q. i The distance from the event point is d i The system uses a distance-first greedy matching strategy: 1. Sort the material points in ascending order of distance: P(1), P(2), ..., P(n), satisfying d(1)≤d(2)≤...≤d(n); 2. Find the smallest integer k such that: ; 3. Allocation of material quantities: ; Generate dispatch instructions and push them to the emergency command center to ensure that supplies arrive in the shortest possible time.

[0032] (5) Strategy execution and information dissemination: Provide guidance information to drivers through V2X communication, variable message signs, etc., adjust traffic light phases, and initiate ramp control measures; In step (5), the induction effect is continuously monitored, and the strategy effectiveness index E(t) is defined: ; in: N complied (t): The number of vehicles that have left the control area as instructed at time t; N target (t): Total number of vehicles that should respond within the target area; V delay (t): Average travel delay of vehicles within the control area (seconds); V max Maximum tolerable delay (default 300 seconds); γ∈[0.5,0.8]: Compliance rate weight.

[0033] If E(t) < θ (θ is a set threshold, such as 0.6), then a policy update is triggered: Increase the strength of speed limit constraints; Close more upstream ramps; Activate secondary evacuation nodes; Adjust the emergency level of the information board prompts.

[0034] At the same time, the system will link the updated strategy with traffic light phases and variable lane directions to achieve network-level coordinated control.

[0035] (6) Effect evaluation and iterative optimization: Track the effect of strategy execution in real time, collect feedback data, calculate the strategy effectiveness index, and adjust and optimize subsequent actions accordingly.

[0036] System collaborative control enables information interaction and coordinated control between vehicles, roads, and the cloud, thereby improving the overall road network operation efficiency and service level. Example 2

[0037] A dynamic guidance and collaborative control system for highway emergencies based on real-time vehicle location, comprising: Event Recognition and Severity Assessment Module: Uses image recognition technology to classify event types, calculates the event severity index in combination with road traffic conditions, and determines the response level based on the severity of the event; Three-layer dynamic fence generation module: used to automatically select the appropriate emergency plan based on the location and severity of the event, and dynamically generate three-layer geofences, including control zone, impact zone, and no-impact zone; Differentiated guidance strategy generation module: used to specify corresponding evacuation or detour strategies for vehicles in different areas, while taking into account factors such as weather conditions and real-time traffic conditions to optimize the guidance plan; Rescue supplies matching module: used to analyze the types and quantities of resources required for an event, and use a distance-first greedy strategy to clearly determine the nearest supply point with sufficient inventory; Strategy distribution and roadside coordination module: used to distribute guidance information to drivers through V2X communication, variable message signs and other means, adjust traffic light phases, and initiate ramp control measures, etc. The execution effect feedback and strategy optimization module is used to track the strategy execution effect in real time, collect feedback data, calculate the strategy effectiveness index, and adjust and optimize subsequent actions accordingly.

[0038] All of the above computing modules adopt lightweight algorithm design to ensure that the end-to-end processing time does not exceed 10 seconds, meeting the timeliness requirements of emergency response. Example 3

[0039] Fire incident inside a tunnel (high severity scenario): Background: Inside a six-lane highway tunnel, a truck caught fire due to a short circuit, blocking the two left lanes and filling the tunnel with thick smoke. The incident was automatically triggered by the tunnel's video fire detection system.

[0040] Processing flow: 1. Event identification and severity assessment The system identified the event type as "fire". type =1.0; Number of lanes affected n affected =2, total number of lanes n total =3 (one-way); Calculate the severity index: S=0.6×1.0+0.4×2 / 3≈0.87≥0.7 It was determined to be a "serious incident".

[0041] 2. Dynamic fence generation: Free flow velocity v free =25 m / s (90 km / h), take T evac =120 s, α=1.1 (tunnel environment, to improve redundancy); Control area length: L control =1.1×25×120=3300 m The system searches upstream and finds a service area (evacuation node) 3.2 km away. Therefore, the control area is set from the event point to the entrance of the service area. The affected area, calculated at β=2.5, extends to the second interchange upstream (approximately 8 km away).

[0042] Taking into account weather conditions and road conditions, the following calculations are performed according to the reference table; L impact =L base × (1 + β); where β = β weather + β traffic Assuming normal weather and average speed, and the length of the affected area remains unchanged; L impact = 8 × (1 + 0) = 8 km; 3. Distribution of induction strategies: Vehicles within the controlled area: The following announcement will be made via tunnel broadcasts and information boards: "Fire ahead. Please immediately find the nearest vehicular crosswalk (or pedestrian crosswalk) to move to the opposite tunnel, or follow instructions to reverse to the tunnel entrance."

[0043] Vehicles within the affected area: Navigation apps and upstream information boards will send a notification: "Tunnel closed. Please immediately enter the service area ahead to wait or take an alternate route."

[0044] Three upstream ramps were closed to prevent new vehicles from entering the congested area.

[0045] 4. Resource Matching: The contingency plan requires: 10 fire extinguishers and 5 fire hoses; The nearest supply point A (2 km from the event) has the following inventory: 6 fire extinguishers; Nearest Point B (5 km from the event): 8 fire extinguishers; The system schedules 6 items at point A and 4 items at point B, for a total of 10 items, to be delivered within 5 minutes.

[0046] 5. Feedback on Results: Ten minutes later, 85% of the vehicles in the controlled area had left, with an average delay of 180 seconds; The calculation shows that E(t) = 0.7 × 0.85 + 0.3 × (1 - 180 / 300) = 0.695 > 0.6, indicating that the strategy is effective and the current plan should be maintained. Example 4

[0047] Illegal parking incident on the main lane (low severity scenario): Background: On the outer lane of a three-lane highway, a car was illegally parked due to a malfunction, without its hazard lights on, occupying one lane. The incident was reported by the driver via a road sign scan.

[0048] Processing flow: 1. Event identification and severity assessment The system identified the event type as "anchoring". type =0.2; Number of lanes affected n affected =1, total number of lanes n total =3 (one-way); Calculate the severity index: S=0.6×0.2+0.4×1 / 3≈0.25<0.7 It was determined to be a "minor incident".

[0049] 2. Dynamic fence generation: T evac =60 + 60 × 0.25 = 75 s, α = 0.9; L control =0.9×27.8(100km / h)×75≈1870 m; There is an emergency parking lane 1.5 km upstream (considered an evacuation node), and the control zone extends to this point; The affected area extends to the next toll station (approximately 3 km away) at β=1.6. Taking into account weather conditions and road conditions, the following calculations are performed according to the reference table; L impact =L base × (1 + β); where β = β weather + β traffic Assuming rain and normal average speed; L impact = 3×(1+0.2) = 3.6km; 3. Distribution of induction strategies: Vehicles within the controlled area: Information boards display "Disabled vehicle ahead, please change lanes with caution"; speed limit reduced to 80 km / h; In and outside the affected area: Only text reminders are pushed to the navigation app, with no route intervention; Do not close the ramps or activate the traffic lights.

[0050] 4. Resource Matching: The contingency plan only requires 4 warning cones; The maintenance station (1 km) has sufficient inventory recently and can be directly dispatched.

[0051] 5. Feedback on Results: The broken-down vehicle was towed away 15 minutes later, with no traffic congestion during the process; The strategy effectiveness E(t) = 0.92, and the system automatically terminates the emergency state.

[0052] The above embodiments demonstrate that the present invention can adaptively adjust the response strategy according to the event type and severity, combining strong intervention capabilities in high-risk scenarios with lightweight processing efficiency in low-risk scenarios.

[0053] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described herein. Although the present invention has been described in detail with reference to the above embodiments, the present invention is not limited to the specific embodiments described above. Therefore, any modifications or equivalent substitutions to the present invention, as well as all technical solutions and improvements that do not depart from the spirit and scope of the invention, are covered within the scope of the claims of the present invention.

Claims

1. A method for dynamic guidance and coordinated control of highway emergencies based on real-time vehicle location, characterized in that, Includes the following steps: (1) Use image recognition technology to classify event types, calculate the event severity index in combination with road traffic conditions, and determine the response level based on the severity of the event; (2) Automatically select appropriate emergency plans based on the location and severity of the event, and dynamically generate three-layer geofences, including control zone, impact zone, and no-impact zone; (3) Specify corresponding evacuation or detour strategies for vehicles in different areas; (4) Analyze the types and quantities of resources required for the event, and use a distance-first greedy strategy to clearly identify the nearest and most readily available supply point; (5) Issue guidance information to drivers, adjust traffic light phases, and initiate ramp control measures; (6) Track the strategy execution effect in real time, collect feedback data, calculate the strategy effectiveness index, and adjust and optimize subsequent actions.

2. The method according to claim 1, characterized in that, In step (1), the event severity index S∈[0,1] is defined: ； in: f type For event type factor: Fire: f type = 1.0; Major casualty accident: f type = 0.7; General traffic accident: f type = 0.4; Routine events such as vehicle breakdown: f type = 0.2; n affected : number of affected lanes; n total : total number of lanes of the road segment; w1 and w2 are weighting coefficients that satisfy w1 + w2 = 1, with the default values ​​being w1 = 0.6 and w2 = 0.

4. When S≥0.7, it is determined to be a serious event, triggering the highest level of emergency response.

3. The method according to claim 1, characterized in that, In step (2), the upstream boundary lengths of the control zone and the affected zone are dynamically calculated based on the event location and severity: L control =α × v free × T evac ; L impact =β×L control ; in: L control : Control zone length, in meters, which is the upper limit of the distance extending upstream from the event point to the first evacuation node; L impact : Length of the affected area, in meters; v free Free-flow velocity on this section of road, m / s; T evac : Preset evacuation time, in seconds; 120 seconds for fire; other events are interpolated linearly using S. α∈[0.8,1.2]: Safety redundancy coefficient, adjusted in real time according to visibility and weather; β∈[1.5,3.0]: The expansion factor of the influence area; the larger S is, the larger β is.

4. The method according to claim 3, characterized in that, Search for evacuation nodes along the upstream direction. If the actual distance is less than the calculated value, use the actual node as the boundary; otherwise, cut off according to the calculated value.

5. The method according to claim 1, characterized in that, In step (3), a customized instruction is sent based on the region to which the vehicle belongs: Controlled area: Forced guidance to the nearest exit + dynamic speed limit; Affected area: Recommended detour route + ramp closure warning; No impact zone: Event briefing only.

6. The method according to claim 5, characterized in that, The misleading information is simultaneously distributed via WeChat messages, variable message signs, and navigation platform interfaces.

7. The method according to claim 1, characterized in that, In step (4), let the total amount of materials required for the event be Q, and the set of available material points be {P}. i The inventory at each point is q. i The distance from the event point is d i A distance-first greedy matching strategy is used: (1) Sort the material points in ascending order of distance: P(1), P(2), ..., P(n), satisfying d(1)≤d(2)≤...≤d(n); (2) Find the smallest integer k such that: ; (3) Allocation of material quantities: ; Generate dispatch instructions and push them to the emergency command center.

8. The method according to claim 1, characterized in that, In step (5), the strategy effectiveness index E(t) is defined: ； in: N complied (t): The number of vehicles that have left the control area as instructed at time t; N target (t): Total number of vehicles that should respond within the target area; V delay (t): Average travel delay of vehicles within the controlled area, in seconds; V max Maximum tolerable delay; γ∈[0.5,0.8]: Compliance rate weight.

9. The method according to claim 7, characterized in that, If E(t) < θ, where θ is a set threshold, then a policy update is triggered: Increase the strength of speed limit constraints; Close more upstream ramps; Activate secondary evacuation nodes; Adjust the emergency level of the information board prompts; The updated strategy will be linked with traffic light phases and variable lane directions to achieve network-level coordinated control.

10. A system for dynamic guidance and coordinated control of highway emergencies based on real-time vehicle location according to any one of claims 1-9, characterized in that, include: Event Recognition and Severity Assessment Module: Uses image recognition technology to classify event types, calculates the event severity index in combination with road traffic conditions, and determines the response level based on the severity of the event; Three-layer dynamic fence generation module: used to automatically select the appropriate emergency plan based on the location and severity of the event, and dynamically generate three-layer geofences, including control zone, impact zone, and no-impact zone; Differentiated guidance strategy generation module: used to specify corresponding evacuation or detour strategies for vehicles in different areas, while taking into account weather conditions and real-time traffic conditions to optimize the guidance plan; Rescue supplies matching module: used to analyze the types and quantities of resources required for an event, and use a distance-first greedy strategy to clearly determine the nearest supply point with sufficient inventory; Strategy distribution and roadside coordination module: used to distribute guidance information to drivers via V2X communication and variable message signs, adjust traffic light phases, and initiate ramp control measures; The execution effect feedback and strategy optimization module is used to track the strategy execution effect in real time, collect feedback data, calculate the strategy effectiveness index, and adjust and optimize subsequent actions accordingly.

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