A sanitation vehicle green wave operation method and system, and a traffic light control system

Abstract

This invention discloses a method, system, and traffic light control system for green wave operation of sanitation vehicles. The method includes: a vehicle management platform creating a work task containing a planned operation route and time window and sending it to the vehicle's smart screen; after driver confirmation, the vehicle terminal collects vehicle speed and real-time location via CAN bus and reports it to the traffic light control system; after system verification, green wave passage right is activated, the vehicle coordinates are compared with pre-stored stop line coordinates to calculate the remaining distance, and the arrival time is calculated based on vehicle speed; the traffic light timing is dynamically adjusted, and the next intersection is updated after the vehicle passes, until the vehicle deviates from the route or exceeds the time window, at which point the green wave passage right is deactivated. This invention achieves precise and dynamic granting of green wave passage right through a dual verification mechanism of planned operation route and time window, solving the problem that existing public transport priority systems cannot adapt to the changing routes and flexible times of sanitation operations; through a three-layer collaborative architecture of cloud-vehicle-roadside, it breaks down data silos between the sanitation operation management system and the traffic control system, achieving full-link closed-loop control.

Description

Technical Field

[0001] This invention relates to the field of intelligent traffic control and sanitation equipment technology, specifically to a green wave operation method and system for sanitation cleaning vehicles and a traffic light control system. Background Technology

[0002] Sanitation vehicles are crucial equipment for ensuring urban environmental sanitation. Their operating routes typically cover main and secondary roads, and their operation is concentrated during peak traffic hours such as early morning and night. During operation, these vehicles frequently encounter traffic lights at intersections, requiring them to stop and wait, leading to the following problems: On the one hand, the operation efficiency is low. When sanitation vehicles are in operation, the drivers cannot predict the status of traffic lights at intersections ahead. Frequent stopping and starting disrupts the continuous operation rhythm, reducing the mileage and cleaning efficiency per unit time.

[0003] On the other hand, energy consumption increases. Frequent start-stop cycles lead to increased fuel consumption or battery depletion, which contradicts the goal of green and environmentally friendly operations.

[0004] Currently, while some sanitation vehicles are equipped with navigation systems, these systems only provide road condition information and cannot be integrated with traffic light control systems. Existing public transport priority systems, although enabling some vehicles to have priority access, are designed for fixed routes and schedules and cannot adapt to the unique operational characteristics of sanitation vehicles, such as their variable routes, flexible operating times, and low speeds (generally 5-15 km / h). Therefore, how to coordinate sanitation vehicle operations with traffic light control systems based on their planned tasks, allowing sanitation vehicles to pass through intersections without stopping during peak and off-peak traffic periods, is a pressing technical problem that needs to be solved in this field. Summary of the Invention

[0005] The technical problem to be solved by the present invention is the low operating efficiency and increased energy consumption of sanitation vehicles due to frequent stops at intersections, as well as the lack of targeted collaborative control solutions in the prior art. In order to solve the above problems, a green wave operation method, system and traffic light control system for sanitation cleaning vehicles are provided.

[0006] The object of this invention is achieved in the following manner: A green wave operation method for sanitation vehicles includes the following steps: Step S1: The vehicle management platform creates a work task that includes a planned work route and a planned work time window, and sends the work task to the vehicle-mounted smart screen via a wireless communication network; Step S2: The driver views and confirms the task through the in-vehicle smart screen, and the in-vehicle smart screen sends the confirmed task information to the vehicle terminal via the CAN bus; Step S3: After the vehicle starts working, the on-board terminal collects the vehicle's real-time location and real-time speed, and sends the vehicle's VIN code, work task ID, planned work route, planned work time window, real-time location and real-time speed to the traffic light control system through the wireless communication network. Step S4: After receiving the information, the traffic light control system verifies the validity of the vehicle's VIN code and the task ID, and determines whether the current time falls within the planned operation time window and whether the vehicle's current location is on the planned operation route. Step S5: After all verifications are passed, the traffic light control system activates the green wave right of way for the vehicle and calculates the estimated arrival time at the next intersection based on the vehicle's real-time location and real-time speed. Step S6: The traffic light control system dynamically adjusts the timing of the traffic light signals at the intersection according to the estimated arrival time, so that the traffic light is green when the vehicle arrives at the intersection; Step S7: After the vehicle passes through the current intersection, the traffic light control system automatically updates the target to the next intersection on the planned operation route, and repeats steps S5 to S6 until the vehicle's current position is no longer on the planned operation route or the current time is no longer within the planned operation time window, at which point the green wave right of way is turned off.

[0007] The method for dynamically adjusting the timing of traffic light signals in step S6 specifically includes: The traffic light control system calculates the time difference Δt between the estimated arrival time and the current time. The time difference Δt is compared with a preset threshold T0; When Δt>T0, the traffic light control system dynamically adjusts the signal phase duration by gradually shortening the red light duration or extending the green light duration, so that the traffic light at the intersection switches to green just as the vehicle arrives. When Δt ≤ T0, the traffic light control system immediately triggers the green light extension or the red light early termination, opening a momentary green light passage window for vehicles.

[0008] The preset threshold T0 ranges from 15 seconds to 25 seconds, preferably 20 seconds.

[0009] The validity of the vehicle VIN code and job task ID verified by the traffic light control system in step S4 specifically includes: the traffic light control system has a pre-stored whitelist of authorized vehicle VIN codes and a whitelist of job task IDs. The verification is successful only when the received VIN code and job task ID match the records in the whitelist.

[0010] In step S2, after the driver views and confirms the work task through the vehicle-mounted smart screen, the vehicle-mounted smart screen also allows the driver to manually modify the planned work route and / or planned work time window in the work task, and send the modified work task information to the vehicle terminal through the CAN bus.

[0011] In step S7, when the vehicle's current location is not on the planned operation route or the current time is not within the planned operation time window, the traffic light control system automatically closes the vehicle's green wave right of way and switches the traffic light control at the intersection back to the normal signal cycle control mode.

[0012] A green wave operation system for sanitation vehicles to implement the green wave operation method of sanitation vehicles, comprising: The vehicle management platform, deployed in the cloud, is used to create work tasks, which include planning work routes and planning work time windows. The in-vehicle smart screen is installed in the driver's cab of the sanitation and cleaning vehicle. It is connected to the vehicle management platform via a wireless communication network to receive and display the work tasks and collect the driver's confirmation instructions. The vehicle-mounted terminal is installed on the sanitation and cleaning vehicle and communicates with the vehicle-mounted smart screen via the CAN bus. It is used to collect the real-time location and real-time speed of the vehicle after the vehicle-mounted smart screen receives the confirmation command. The traffic light control system is deployed at each intersection and communicates with the vehicle terminal via a wireless communication network. It is used to receive information reported by the vehicle terminal and execute steps S4 to S7 of the method according to the received information.

[0013] The wireless communication network between the vehicle management platform and the in-vehicle smart screen is a 4G, 5G, or LTE-V communication network; the wireless communication network between the in-vehicle terminal and the traffic light control system is a 4G, 5G, LTE-V, or DSRC communication network.

[0014] A traffic light control system, comprising: The communication module is used to receive information reported by the vehicle terminal installed on the sanitation and cleaning vehicle through a wireless communication network. The information includes the vehicle VIN code, job task ID, planned job route, planned job time window, real-time location of the vehicle, and real-time speed. The storage module is used to store the authorized vehicle VIN code whitelist and the job task ID whitelist; The verification module, connected to the communication module and the storage module respectively, is used to verify whether the received vehicle VIN code and job task ID match the records in the whitelist, and to determine whether the current time falls within the planned job time window and whether the current position of the vehicle is on the planned job route. The calculation module, connected to the verification module, is used to calculate the estimated arrival time of the vehicle to the next intersection based on the vehicle's real-time location and real-time speed after all verifications have passed. The control module, connected to the calculation module, is used to dynamically adjust the timing of the traffic light signals at the intersection according to the estimated arrival time, so that the traffic light is green when the vehicle arrives at the intersection. The dynamic adjustment includes: dynamically adjusting the signal phase duration when the time difference between the estimated arrival time and the current time is greater than a preset threshold, and immediately triggering green light extension or red light early termination when the time difference is less than or equal to the preset threshold. The update module, connected to the control module, is used to automatically update the target to the next intersection on the planned operation route after the vehicle passes through the current intersection, and trigger the calculation module and the control module to repeatedly perform the corresponding operation until the vehicle's current position is no longer on the planned operation route or the current time is no longer within the planned operation time window, at which point the green wave right of way is closed.

[0015] The beneficial effects of this invention are as follows: This invention achieves precise and dynamic granting of green wave passage rights for sanitation vehicles through a dual verification mechanism of "planned operation route + planned operation time window," solving the technical problem that existing public transport priority systems cannot adapt to the changing routes and flexible times of sanitation operations. Furthermore, this invention, through a three-layer collaborative architecture of "vehicle management platform - in-vehicle smart screen / in-vehicle terminal - traffic light control system," breaks down data silos between the sanitation operation management system and the urban traffic control system, achieving closed-loop control across the entire chain from task generation to precise passage at intersections. Attached Figure Description

[0016] Figure 1 This is an overall schematic diagram of the green wave operation system for sanitation vehicles in an embodiment of the present invention. Detailed Implementation

[0017] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0018] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same technical meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] To facilitate understanding of this invention, the following terms are explained: Smart in-vehicle screen: An intelligent interactive terminal device installed in the cab of a sanitation vehicle. It has touch display, data communication and human-computer interaction functions. It is used to receive and display the work tasks issued by the vehicle management platform and collect the driver's confirmation instructions.

[0020] Vehicle-mounted terminal (T-Box, Telematics Box): An in-vehicle communication terminal integrated on sanitation and cleaning vehicles. It connects to the in-vehicle smart screen via a CAN bus and has vehicle positioning (GPS / Beidou), vehicle speed collection, and 4G / 5G wireless communication functions. It is used to report the real-time status of the vehicle to the traffic light control system.

[0021] Green wave operation: refers to a sanitation vehicle operation method in which the traffic light control system coordinates with the vehicle to ensure that the traffic light is green when the vehicle arrives at each intersection, thus enabling continuous passage without stopping.

[0022] A green wave operation method for sanitation vehicles includes the following steps: Step S1: The vehicle management platform creates a work task that includes a planned work route and a planned work time window, and sends the work task to the vehicle-mounted smart screen via a wireless communication network; Step S2: The driver views and confirms the task through the in-vehicle smart screen, and the in-vehicle smart screen sends the confirmed task information to the vehicle terminal via the CAN bus; Step S3: After the vehicle starts working, the on-board terminal collects the vehicle's real-time location and real-time speed, and sends the vehicle's VIN code, work task ID, planned work route, planned work time window, real-time location and real-time speed to the traffic light control system through the wireless communication network. Step S4: After receiving the information, the traffic light control system verifies the validity of the vehicle's VIN code and the task ID, and determines whether the current time falls within the planned operation time window and whether the vehicle's current location is on the planned operation route. Step S5: After all verifications are passed, the traffic light control system activates the green wave right of way for the vehicle and calculates the estimated arrival time at the next intersection based on the vehicle's real-time location and real-time speed. Step S6: The traffic light control system dynamically adjusts the timing of the traffic light signals at the intersection according to the estimated arrival time, so that the traffic light is green when the vehicle arrives at the intersection; Step S7: After the vehicle passes through the current intersection, the traffic light control system automatically updates the target to the next intersection on the planned operation route, and repeats steps S5 to S6 until the vehicle's current position is no longer on the planned operation route or the current time is no longer within the planned operation time window, at which point the green wave right of way is turned off.

[0023] The method for dynamically adjusting the timing of traffic light signals in step S6 specifically includes: The traffic light control system calculates the time difference Δt between the estimated arrival time and the current time. The time difference Δt is compared with a preset threshold T0; When Δt>T0, the traffic light control system dynamically adjusts the signal phase duration by gradually shortening the red light duration or extending the green light duration, so that the traffic light at the intersection switches to green just as the vehicle arrives. When Δt ≤ T0, the traffic light control system immediately triggers the green light extension or the red light early termination, opening a momentary green light passage window for vehicles.

[0024] The preset threshold T0 ranges from 15 seconds to 25 seconds, preferably 20 seconds.

[0025] The dynamic adjustment response time of a traffic light control system depends on the data reporting cycle of the onboard terminal. In a standard configuration, the onboard terminal reports vehicle position and speed data to the traffic light control system every 10 seconds. In a high-precision configuration, the data reporting cycle can be shortened to 1 second, allowing the traffic light control system to dynamically adjust signal timing with second-level accuracy. Those skilled in the art can configure the data reporting cycle within the range of 1 to 10 seconds based on actual needs such as intersection traffic flow and sanitation operation density.

[0026] The validity of the vehicle VIN code and job task ID verified by the traffic light control system in step S4 specifically includes: the traffic light control system has a pre-stored whitelist of authorized vehicle VIN codes and a whitelist of job task IDs. The verification is successful only when the received VIN code and job task ID match the records in the whitelist.

[0027] The calculation of the estimated arrival time at the next intersection in step S5 adopts a time calculation model optimized for the low-speed operation characteristics of sanitation vehicles, wherein the vehicle's speed ranges from 5km / h to 15km / h.

[0028] In this application, the core algorithm of the time calculation model optimized for the low-speed operation characteristics of sanitation vehicles is as follows: The traffic light control system has pre-stored the precise location coordinates (stop line coordinates) of each intersection. The system compares the real-time vehicle coordinates reported by the on-board terminal with the stop line coordinates of the next intersection and calculates the straight-line distance D between the two.

[0029] Simultaneously, the system will convert the real-time vehicle speed V (unit: km / h) read from the CAN bus into meters per second: V mps = V ÷ 3.6. Taking a typical sanitation operation speed of 5km / h as an example, the distance moved per second is 5 ÷ 3.6 ≈ 1.3888 meters.

[0030] Estimated arrival time T arrival Calculate using the following formula: T arrival = T now + D ÷ V mps ; Among them, T now Where is the current time, D is the remaining distance (meters), and V is the distance to be covered. mps Real-time vehicle speed (m / s).

[0031] The calculation model executes once per data reporting cycle, updating the estimated arrival time in real time. As vehicle speed decreases, the distance traveled per unit time is shorter, and the system adjusts the estimated arrival time more frequently, thus ensuring prediction accuracy in low-speed operating scenarios.

[0032] In this application, the criterion for determining "vehicle arrival at intersection" is: the distance between the vehicle's real-time location coordinates and the geographical coordinates of the stop line at the traffic light intersection is less than a preset threshold (e.g., 5 meters). The traffic light control system stores the precise coordinates (latitude and longitude) of the stop lines at each intersection. When the distance between the vehicle's reported position and the coordinates of that stop line is ≤ 5 meters, the system determines that the vehicle has "arrived at the intersection" and accordingly performs the update operation for the next intersection or closes the green wave right-of-way. This criterion differs from methods that use the intersection center point or the intersection entrance lane as the criterion, enabling more precise triggering of signal switching and avoiding premature or delayed switching due to inconsistent criterion settings.

[0033] In step S2, after the driver views and confirms the work task through the vehicle-mounted smart screen, the vehicle-mounted smart screen also allows the driver to manually modify the planned work route and / or planned work time window in the work task, and send the modified work task information to the vehicle terminal through the CAN bus.

[0034] In step S7, when the vehicle's current location is not on the planned operation route or the current time is not within the planned operation time window, the traffic light control system automatically closes the vehicle's green wave right of way and switches the traffic light control at the intersection back to the normal signal cycle control mode.

[0035] In step S3, the vehicle terminal connects to the vehicle electronic control unit (ECU) via the CAN bus and reads the vehicle's real-time speed signal from the CAN bus at 100-millisecond intervals. Simultaneously, it obtains the vehicle's real-time geographic coordinates via the GPS / BeiDou module. Compared to GPS speed measurement, the speed data read from the CAN bus offers higher real-time performance and accuracy (error ≤ ±0.5 km / h), providing accurate input parameters for the arrival time prediction model.

[0036] A green wave operation system for sanitation vehicles to implement the green wave operation method of sanitation vehicles, comprising: The vehicle management platform, deployed in the cloud, is used to create work tasks, which include planning work routes and planning work time windows. The in-vehicle smart screen is installed in the driver's cab of the sanitation and cleaning vehicle. It is connected to the vehicle management platform via a wireless communication network to receive and display the work tasks and collect the driver's confirmation instructions. The vehicle-mounted terminal is installed on the sanitation and cleaning vehicle and communicates with the vehicle-mounted smart screen via the CAN bus. It is used to collect the real-time location and real-time speed of the vehicle after the vehicle-mounted smart screen receives the confirmation command. The traffic light control system is deployed at each intersection and communicates with the vehicle terminal via a wireless communication network. It is used to receive information reported by the vehicle terminal and execute steps S4 to S7 of the method according to the received information.

[0037] The wireless communication network between the vehicle management platform and the in-vehicle smart screen is a 4G, 5G, or LTE-V communication network; the wireless communication network between the in-vehicle terminal and the traffic light control system is a 4G, 5G, LTE-V, or DSRC communication network.

[0038] A traffic light control system, comprising: The communication module is used to receive information reported by the vehicle terminal installed on the sanitation and cleaning vehicle through a wireless communication network. The information includes the vehicle VIN code, job task ID, planned job route, planned job time window, real-time location of the vehicle, and real-time speed. The storage module is used to store the authorized vehicle VIN code whitelist and the job task ID whitelist; The verification module, connected to the communication module and the storage module respectively, is used to verify whether the received vehicle VIN code and job task ID match the records in the whitelist, and to determine whether the current time falls within the planned job time window and whether the current position of the vehicle is on the planned job route. The calculation module, connected to the verification module, is used to calculate the estimated arrival time of the vehicle to the next intersection based on the vehicle's real-time location and real-time speed after all verifications have passed. The control module, connected to the calculation module, is used to dynamically adjust the timing of the traffic light signals at the intersection according to the estimated arrival time, so that the traffic light is green when the vehicle arrives at the intersection. The dynamic adjustment includes: dynamically adjusting the signal phase duration when the time difference between the estimated arrival time and the current time is greater than a preset threshold, and immediately triggering green light extension or red light early termination when the time difference is less than or equal to the preset threshold. The update module, connected to the control module, is used to automatically update the target to the next intersection on the planned operation route after the vehicle passes through the current intersection, and trigger the calculation module and the control module to repeatedly perform the corresponding operation until the vehicle's current position is no longer on the planned operation route or the current time is no longer within the planned operation time window, at which point the green wave right of way is closed.

[0039] Example: Basic Operation Process (Taking a Sweeper Truck as an Example) This embodiment uses a sweeper truck with chassis number YTRC23001 performing a morning sweeping task along Jingguang Road in a certain city as an example for illustration.

[0040] (I) Task Preparation Phase At 4:00 AM sharp, the vehicle management platform created a work task for the YTRC23001 sweeper truck: Task ID 20241015-JGL-001, planned route from the intersection of Jingguang Road and South Third Ring Road to the intersection of Jingguang Road and Huanghe Road (7 intersections in total), total route length 12.6 kilometers, planned work time window from 4:30 AM to 6:30 AM. The vehicle management platform distributed this work task to the vehicle's smart screen via the 5G network.

[0041] Driver Li entered the vehicle at 4:15, viewed and confirmed the work task through the vehicle's smart screen, and the smart screen sent the confirmed task information to the vehicle terminal (T-Box) via the CAN bus.

[0042] (II) Operation Start-up Phase At 4:30 sharp, the vehicle started operation. The onboard terminal collects real-time location and speed every 100 milliseconds, and sends the vehicle's VIN code, task ID, planned route, time window, real-time location, and speed to the traffic light control systems at the intersections ahead via the 5G network every second.

[0043] After receiving the information, the traffic light control system performs VIN verification, task ID verification, time window verification, and route verification in sequence. Once all verifications pass, the system activates green wave passage rights for the vehicle.

[0044] (iii) Green wave passage at each intersection Taking the first intersection (from Jingguang Road and South Third Ring Road to Changjiang Road) as an example: The vehicle is currently 520 meters away from the Changjiang Road intersection, and its current speed is 10 km / h (2.78 m / s). The system uses a time calculation model to calculate the estimated arrival time: T arrival = T now + (520 / 2.78) × 1.0 ≈ T now+ 187 seconds. The current time difference Δt = 187 seconds, which is greater than the preset threshold T0 = 20 seconds. The system adopts a long-distance pre-adjustment mode to dynamically adjust the signal cycle at the Changjiang Road intersection so that the traffic light turns green just as the vehicle arrives. The vehicle arrives at the Changjiang Road intersection at 4:33:12 and can pass through without stopping.

[0045] The above process is repeated at subsequent intersections, with the system updating the target at each intersection on a rolling basis.

[0046] This invention also provides a complete exception handling mechanism, including: (1) Communication interruption handling: The vehicle terminal sends a heartbeat packet to the traffic light control system every 200ms. If no heartbeat packet is received for 3 consecutive cycles, the communication is considered interrupted. During the interruption, the vehicle terminal caches the location data (records once per second, with a maximum cache time of 5 minutes). After communication is restored, the data is automatically uploaded and re-verified. After successful verification, the green wave right of way is reactivated. If the duration of the communication interruption exceeds 50% of the remaining time of the planned operation window or exceeds 10 minutes, the green wave right of way is permanently closed.

[0047] Example: At 4:38:00, a vehicle enters the Jingguang Road underpass, and the wireless communication signal is interrupted. The traffic light control system determines that communication is interrupted after not receiving a heartbeat packet for 600ms, marks the vehicle's green wave right-of-way as "suspended," and the traffic lights at the intersection switch back to normal mode. The in-vehicle smart screen displays a "Communication Interrupted" message. At 4:39:15, the vehicle exits the tunnel, communication is restored, and the system re-verifies and reactivates the green wave right-of-way, with a restoration time of 3 seconds.

[0048] (2) The traffic light control system compares the real-time location of the vehicle with the planned operation route every 1 second. When the vertical distance exceeds 30 meters for more than 3 seconds, a deviation is determined. A temporary deviation (30-50 meters) sends a prompt to the vehicle's smart screen; a continuous deviation (>50 meters or >10 seconds) immediately closes the green wave right of way. The driver can initiate a route change application through the vehicle's smart screen. After the vehicle management platform approves the application, the route is updated and the green wave right of way is reactivated.

[0049] Example: At 4:45:00, due to road construction at the intersection of Jingguang Road and Longhai Road, the vehicle actually turned onto Zhengtong Road. The system detected that the current location did not match "Longhai Road" in the planned route, but matched the driver's modified route (Zhengtong Road), and determined it to be a proactive route change, automatically switching to Zhengtong Road as the next target intersection.

[0050] (3) Handling of Multi-Vehicle Conflicts: When multiple sanitation vehicles simultaneously request green wave passage rights at the same intersection within the same time window, the system uses a priority scoring algorithm to determine the passage order. The scoring formula is: Total Priority Score = 40% × Task Urgency + 30% × Distance from Intersection + 20% × Operation Continuity + 10% × Historical Waiting Times. The system adopts staggered passage, queue passage, or directional coordination strategies according to the conflict situation, and ensures that the single signal cycle offset does not exceed 30% of the original cycle length.

[0051] Example: At 4:55:00, three sanitation vehicles simultaneously approached the Zhongyuan Road intersection. The system performed a priority scoring: YTRC23001 scored 61 points (95 minutes remaining window, 80 meters distance, and having passed through 3 intersections consecutively), YTRC23002 scored 55 points, and YTRC23005 scored 27 points. The system adopted a directional coordination strategy, prioritizing the passage of YTRC23001 and YTRC23005 traveling from north to south. After YTRC23001 passed, YTRC23005 followed immediately, and then the direction was switched to allow YTRC23002 to pass. YTRC23001 passed without waiting, while YTRC23002 waited for approximately 10 seconds.

[0052] (iv) Completion of assignments At 5:15:20, the vehicle arrived at the destination, Huanghe Road intersection, and the system automatically closed the green wave passage right. The entire route involved 7 intersections with 0 stops, and the total operation time was 45 minutes (excluding the starting time), saving approximately 12 minutes compared to traditional operations.

[0053] Compared with the prior art, the present invention has the following advantages: 1. This invention achieves precise and dynamic granting of green wave passage rights for sanitation vehicles through a dual verification mechanism of "planned operation route + planned operation time window", solving the technical problem that the existing public transport priority system cannot adapt to the changing sanitation operation routes and flexible time.

[0054] Specifically, this invention uses the planned work routes and planned work time windows created by the vehicle management platform as the core basis for the traffic light control system to determine right-of-way. Green wave right-of-way is only activated when the vehicle's reported current location is on the planned route and the current time falls within the planned time window. This technology allows the system to automatically adapt to the daily changing work tasks of sanitation vehicles without manual intervention or fixed configuration. Simultaneously, when a vehicle actively changes its route or exceeds its work time, the system automatically deactivates its priority, preventing the unnecessary occupation of traffic resources.

[0055] 2. This invention solves the technical problem of inaccurate arrival time prediction caused by sanitation vehicles operating at low speeds (5-15km / h) by using a time calculation model of "CAN bus vehicle speed acquisition + parking line coordinate comparison + low speed correction".

[0056] Specifically, this invention reads the vehicle speed (accuracy ±0.5 km / h) from the CAN bus at a high frequency of 100 milliseconds; compares the vehicle's real-time coordinates with the pre-stored intersection stop line coordinates, using a distance ≤5 meters as the criterion for "arrival at the intersection"; and incorporates this information into the traditional time calculation model T. arrival = T now Based on the D / V calculation, refined calculations are performed for low-speed scenarios such as 5 km / h (1.3888 meters per second). This technique fully considers the actual movement characteristics of sanitation vehicles under low-speed operating conditions, avoiding calculation errors based solely on instantaneous speed or GPS speed measurement. Real-world testing shows that after adopting the optimized model of this invention, the arrival time prediction error is reduced from ±5.2 seconds to ±1.8 seconds.

[0057] 3. This invention employs a dual-mode dynamic phase adjustment strategy of "long-distance pre-adjustment + short-distance emergency handling" to ensure priority passage for sanitation vehicles while minimizing interference with the normal passage of other vehicles.

[0058] Specifically, this invention sets a preset threshold T0 (preferably 20 seconds). When the difference between the estimated arrival time and the current time Δt > T0, a long-distance pre-adjustment mode is adopted, which smoothly transitions the signal phase by gradually shortening the red light duration or extending the green light duration. When Δt ≤ T0, a short-distance emergency processing mode is adopted, which immediately triggers the extension of the green light or the early termination of the red light. Simultaneously, the response time of the dynamic adjustment can be configured according to the data reporting cycle of the vehicle terminal (typically 10 seconds, with high precision down to 1 second), achieving signal control with second-level precision. The substantial effect of this technique is that in the long-distance pre-adjustment mode, the rate of change of the signal cycle is no more than 1% of the original cycle per second, and social vehicles hardly perceive the signal change; in the short-distance emergency processing mode, although the signal changes abruptly, the impact on social vehicles is limited to a very short period due to the short time window (≤20 seconds). Actual measurements show that after adopting the dual-mode strategy of this invention, the reduction in intersection capacity is controlled within 1.5%, far lower than the 5-10% impact of existing bus priority systems.

[0059] 4. This invention achieves continuous green wave passage for sanitation vehicles along the entire operation route through the "intersection-by-intersection rolling prediction and status feedback update" mechanism.

[0060] Specifically, after a vehicle passes through the current intersection, the traffic light control system automatically updates the target to the next intersection on the planned route, using the actual time the vehicle passed the previous intersection as the starting point for predicting the next intersection, thus forming a rolling prediction mechanism. This technique differs from the one-time path planning of existing technologies, enabling real-time correction of deviations caused by traffic conditions, driving behavior, and other factors, ensuring vehicles continuously obtain green light windows at multiple intersections. Real-world testing shows that, using the rolling prediction mechanism of this invention, on a typical operating route containing 7 intersections, the continuous green light pass rate increases from 65% with the traditional green wave scheme to 92.9%.

[0061] 5. This invention breaks down data silos between the sanitation operation management system and the urban traffic control system through a three-layer collaborative architecture of "vehicle management platform - vehicle smart screen / vehicle terminal - traffic light control system", achieving full-link closed-loop control.

[0062] Specifically, this invention constructs a three-layer architecture: cloud (task creation and distribution) → vehicle (task confirmation and status collection and reporting) → roadside (green wave control and signal adjustment). These layers are interconnected via standardized wireless communication protocols (4G / 5G / LTE-V / DSRC). This technology transforms task planning, vehicle status, and traffic control from being independent processes into a collaborative system: the cloud transmits task intentions to the roadside, the roadside executes control based on the real-time status reported by the vehicle, and the control results are fed back to the cloud via the actual time it takes for vehicles to pass through intersections for task optimization. This closed-loop mechanism is not present in existing public transport priority systems or ordinary navigation systems.

[0063] 6. This invention significantly improves the robustness of the system in real and complex traffic environments through a three-level anomaly handling mechanism (communication interruption, deviation from the route, and multi-vehicle conflict).

[0064] Specifically, this invention designs differentiated processing strategies for common scenarios in sanitation operations, such as communication blind spots (tunnels, underpasses), route changes (road construction, temporary traffic control), and concurrent multi-vehicle traffic. Actual tests show that the communication interruption recovery success rate reaches 98.5% (recovery time ≤ 3 seconds), and the multi-vehicle conflict handling success rate is 99.2% (average additional waiting time for vehicles ≤ 10 seconds).

[0065] 7. By combining the above-mentioned technical means, the present invention achieves a significant improvement in technical effect.

[0066] Based on the synergistic effect of the above-mentioned technical means, the present invention obtained the following measured data in a 30-day comparative test on 5 sanitation operation routes in a provincial capital city:

[0067] The above data fully demonstrates that this invention solves the technical problem of frequent stops of sanitation vehicles at intersections by organically combining a series of technical means, namely, "task planning and verification → CAN bus vehicle speed acquisition → parking line coordinate comparison → low speed optimization prediction → dual-mode phase adjustment (1-10 second configurable response) → rolling update at each intersection → three-level anomaly handling". It ensures priority passage efficiency while taking into account the normal passage of social vehicles, and has made significant and substantial progress.

[0068] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several changes and improvements without departing from the overall concept of the present invention, and these should also be considered within the scope of protection of the present invention.

Claims

1. A green wave operation method for sanitation vehicles, characterized in that: Includes the following steps: Step S1: The vehicle management platform creates a work task that includes a planned work route and a planned work time window, and sends the work task to the vehicle-mounted smart screen via a wireless communication network; Step S2: The driver views and confirms the task through the in-vehicle smart screen, and the in-vehicle smart screen sends the confirmed task information to the vehicle terminal via the CAN bus; Step S3: After the vehicle starts working, the on-board terminal collects the vehicle's real-time location and real-time speed, and sends the vehicle's VIN code, work task ID, planned work route, planned work time window, real-time location and real-time speed to the traffic light control system through the wireless communication network. Step S4: After receiving the information, the traffic light control system verifies the validity of the vehicle's VIN code and the task ID, and determines whether the current time falls within the planned operation time window and whether the vehicle's current location is on the planned operation route. Step S5: After all verifications are passed, the traffic light control system activates the green wave right of way for the vehicle and calculates the estimated arrival time at the next intersection based on the vehicle's real-time location and real-time speed. Step S6: The traffic light control system dynamically adjusts the timing of the traffic light signals at the intersection according to the estimated arrival time, so that the traffic light is green when the vehicle arrives at the intersection; Step S7: After the vehicle passes through the current intersection, the traffic light control system automatically updates the target to the next intersection on the planned operation route, and repeats steps S5 to S6 until the vehicle's current position is no longer on the planned operation route or the current time is no longer within the planned operation time window, at which point the green wave right of way is turned off.

2. The green wave operation method of a sanitation vehicle according to claim 1, characterized in that: The method for dynamically adjusting the timing of traffic light signals in step S6 specifically includes: The traffic light control system calculates the time difference Δt between the estimated arrival time and the current time. The time difference Δt is compared with a preset threshold T0; When Δt > T0, the traffic light control system dynamically adjusts the signal phase duration by gradually shortening the red light duration or extending the green light duration, so that the traffic light at the intersection switches to green just as the vehicle arrives. When Δt ≤ T0, the traffic light control system immediately triggers the green light extension or the red light early termination, opening a momentary green light passage window for vehicles.

3. The sanitation vehicle green wave operation method according to claim 2, characterized in that: The preset threshold T0 ranges from 15 seconds to 25 seconds, preferably 20 seconds.

4. The sanitation vehicle green wave operation method of claim 1, wherein: The validity of the vehicle VIN code and job task ID verified by the traffic light control system in step S4 specifically includes: the traffic light control system has a pre-stored whitelist of authorized vehicle VIN codes and a whitelist of job task IDs. The verification is successful only when the received VIN code and job task ID match the records in the whitelist.

5. The sanitation vehicle green wave operation method of claim 1, wherein: In step S2, after the driver views and confirms the work task through the vehicle-mounted smart screen, the vehicle-mounted smart screen also allows the driver to manually modify the planned work route and / or planned work time window in the work task, and send the modified work task information to the vehicle terminal through the CAN bus.

6. The sanitation vehicle green wave operation method of claim 1, wherein: In step S7, when the vehicle's current location is not on the planned operation route or the current time is not within the planned operation time window, the traffic light control system automatically closes the vehicle's green wave right of way and switches the traffic light control at the intersection back to the normal signal cycle control mode.

7. A green wave operation system for sanitation vehicles used to implement the green wave operation method for sanitation vehicles according to any one of claims 1 to 6, characterized in that: include: The vehicle management platform, deployed in the cloud, is used to create work tasks, which include planning work routes and planning work time windows. The in-vehicle smart screen is installed in the driver's cab of the sanitation and cleaning vehicle. It is connected to the vehicle management platform via a wireless communication network to receive and display the work tasks and collect the driver's confirmation instructions. The vehicle-mounted terminal is installed on the sanitation and cleaning vehicle and communicates with the vehicle-mounted smart screen via the CAN bus. It is used to collect the real-time location and real-time speed of the vehicle after the vehicle-mounted smart screen receives the confirmation command. The traffic light control system is deployed at each intersection and communicates with the vehicle terminal via a wireless communication network. It is used to receive information reported by the vehicle terminal and execute steps S4 to S7 of the method according to any one of claims 1 to 6 based on the received information.

8. The green wave operation system for sanitation vehicles according to claim 7, characterized in that: The wireless communication network between the vehicle management platform and the in-vehicle smart screen is a 4G, 5G, or LTE-V communication network; the wireless communication network between the in-vehicle terminal and the traffic light control system is a 4G, 5G, LTE-V, or DSRC communication network.

9. A traffic light control system, characterized in that: include: The communication module is used to receive information reported by the vehicle terminal installed on the sanitation and cleaning vehicle through a wireless communication network. The information includes the vehicle VIN code, job task ID, planned job route, planned job time window, real-time location of the vehicle, and real-time speed. The storage module is used to store the authorized vehicle VIN code whitelist and the job task ID whitelist; The verification module, connected to the communication module and the storage module respectively, is used to verify whether the received vehicle VIN code and job task ID match the records in the whitelist, and to determine whether the current time falls within the planned job time window and whether the current position of the vehicle is on the planned job route. The calculation module, connected to the verification module, is used to calculate the estimated arrival time of the vehicle to the next intersection based on the vehicle's real-time location and real-time speed after all verifications have passed. The control module, connected to the calculation module, is used to dynamically adjust the timing of the traffic light signals at the intersection according to the estimated arrival time, so that the traffic light is green when the vehicle arrives at the intersection. The dynamic adjustment includes: dynamically adjusting the signal phase duration when the time difference between the estimated arrival time and the current time is greater than a preset threshold, and immediately triggering green light extension or red light early termination when the time difference is less than or equal to the preset threshold. The update module, connected to the control module, is used to automatically update the target to the next intersection on the planned operation route after the vehicle passes through the current intersection, and trigger the calculation module and the control module to repeatedly perform the corresponding operation until the vehicle's current position is no longer on the planned operation route or the current time is no longer within the planned operation time window, at which point the green wave right of way is closed.

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