AI-powered intelligent traffic clearing system for emergency vehicles

Abstract

An AI-based traffic control system consisting of a real-time data acquisition module, an AI decision engine to calculate an optimal emergency route and priority plan for intersections, a V2I / V2V communication module to transmit emergency approach and priority instructions, and a signal control interface to establish a rolling green corridor, with a recovery module to return the traffic lights to coordinated operation after the emergency passage.

Description

Application area of ​​the invention

[0001] The invention relates to intelligent transport systems that prioritize emergency vehicles using artificial intelligence, vehicle-infrastructure and vehicle-to-vehicle communication, and adaptive signal control to create temporary green corridors and virtual rescue lanes. Background of the invention

[0002] Emergency vehicle priority systems allow traffic lights, ambulances, and fire engines to be given right-of-way, thus reducing response times through traffic light sequences based on vehicle detection and communication. Research and standards describe V2I / V2V messages (e.g., CAM-based siren / emergency light status) for coordinating priority signaling. Practical methods combine detection, dynamic phase control, and route optimization to create clear lanes while minimizing overall traffic flow. AI-powered approaches also utilize real-time traffic information, event data, and weather data to select optimal routes and phase schedules. "Virtual emergency lanes" dynamically redistribute lane usage to create space for emergency vehicles to proceed.There is still a need for an integrated, AI-coordinated system that coordinates route selection, traffic light priority switching, V2X warnings to vehicles, and the orderly restoration of normal traffic flow after passage. Summary of the invention

[0003] The invention comprises a system with the following components: a real-time data acquisition layer for traffic conditions, disruptions, and weather data; an AI decision engine for calculating optimal emergency routes and phase plans for intersections; a V2I / V2V communication module for signaling right-of-way rules and driver warnings; a traffic light control interface for issuing green phase commands; and a recovery module for adjusting the traffic light phases after the emergency vehicle has passed. The system instructs connected / autonomous vehicles to yield the right-of-way via V2V messages and warns human drivers via vehicle alerts, thereby creating a virtual emergency lane for unimpeded passage.

[0004] In some implementations, the decision engine assesses congestion, predicted queues, and safety risks to create a corridor plan that incorporates phase extensions, early green phases, or phase insertions along the route; road units send priority messages; and a feedback loop tracks the responding vehicle to adjust switching windows and prevent traffic gridlock. Once cleared, the controller switches to normal coordination mode to minimize any remaining congestion. Detailed description

[0005] A sensor and data module aggregates data from induction loops, cameras, emergency vehicles, incident reports, and weather APIs. A map-based tracker follows the emergency vehicle using low-latency GNSS and V2X beacons. The AI ​​decision engine consists of a routing component and a signal optimization component. The former calculates the time-dependent shortest path, taking into account turning restrictions and traffic-related blockages, while the latter selects priority strategies at the intersection level (e.g., green extension, red shortening, phase skipping) and corridor offsets to generate a smooth green phase.

[0006] The V2I / V2V module uses broadcast messages to inform roadside emergency personnel and nearby vehicles about approaching emergency vehicles and the status of the incident route. Standards describe messages that include the status of the siren / blue lights and the direction of approach; the system sends right-of-way instructions to compatible vehicles and can interact with the vehicle's human-machine interface (HMI) to display the right-of-way to drivers in appropriately equipped fleets or provide haptic feedback (e.g., through steering wheel vibration).

[0007] At each equipped intersection, a control interface transmits priority and right-of-way commands to the signal control system, which can execute make-be-break phases within the safety limits for pedestrian clearance and overlapping traffic flows. Safety interlocks ensure compliance with minimum green and clearance times. The control system logs all interventions for auditing purposes.

[0008] A virtual emergency lane function dynamically redistributes lane usage along the corridor by signaling lane control states on overhead sign gantries or VMS and issuing V2V recommendations to clear a through lane; the lane status normalizes after the vehicle has passed. The recovery module then resolves congestion using temporary offset plans and restores coordinated travel times to stabilize traffic.

[0009] Cybersecurity and reliability measures include authenticated V2X messaging, protection against replay attacks, and a fail-safe fallback to standard coordination in case of data transmission disruptions. Redundant communication channels (cellular and ITS-G5 / DSRC) ensure continuity. A performance monitor calculates response time savings and the impact of network congestion to optimize AI policies.

[0010] During operation, the control center reports an emergency; the system calculates a route and issues priority plans for intersections along the route; road units send V2X alerts to create a virtual lane; traffic lights form a rolling green corridor; the vehicle travels the route with minimal stops; and after passing through, the system switches to normal plans while simultaneously reducing remaining congestion.

Claims

[1] An AI-based traffic control system comprising a real-time data acquisition module, an AI decision engine for calculating an optimal emergency route and priority plan for intersections, a V2I / V2V communication module for transmitting emergency approach and priority instructions, and a signal control interface for establishing a rolling green corridor, wherein a recovery module returns the traffic lights to coordinated operation after the emergency passage. [2] System according to claim 1, wherein the V2I / V2V communication module emits standardized messages, including the status of sirens or warning lights and approach vectors, to instruct connected and autonomous vehicles to yield the right-of-way and to warn human drivers in the vehicle. [3] System according to claim 1, wherein the decision engine selects priority strategies comprising at least green extension, early green, phase insertion or phase skipping, and coordinates offsets along the track to maintain a virtual emergency lane. [4] System according to claim 1, wherein the system logs pre-events and applies a post-event recovery plan to minimize remaining congestion and restore normal coordination.